Embed Size (px)
Citation preview
Identification and Characterization of Common Bacterial Blight
Resistance Genes in the Resistant Common Bean (Phaseolus
vulgaris) Variety OAC Rex
By
Denise M. Cooper
A Thesis
Presented to
The University of Guelph
In partial fulfilment of requirements
for the degree of
Master of Science
in
Plant Agriculture
Guelph, Ontario, Canada
© Denise Cooper, July, 2015
ABSTRACT
Identification and Characterization of Common Bacterial Blight Resistance
Genes in the Resistant Common Bean (Phaseolus vulgaris) Variety OAC Rex
Denise M. Cooper Advisor: University of Guelph, 2015 Dr. K. Peter Pauls Common bacterial blight (CBB), caused by the bacterium, Xanthomonas
axonopodis pv. phaseoli (Xap), is a major disease of common bean (Phaseolus
vulgaris L.). CBB resistance candidate genes (CGs) were identified in the
genomic library sequence of resistant variety OAC Rex based on pathogen
resistance gene homology. Four CGs (CBB1-4) and other genes in the
surrounding sequence were characterized. The CGs had homology to a putative
leucine-rich-repeat disease resistance gene in Oryza sativa and
retrotransposons. CG expression was not observed in either OAC Rex or OAC
Seaforth (susceptible variety) after Xap or water treatment, indicating they are
unlikely to be involved in CBB resistance. The other genes encoded ascorbate
oxidase, callose synthase and hypothetical proteins. To test Xap susceptibility of
Arabidopsis thaliana, detached leaves were inoculated with bacteria. Chlorosis
and bacterial growth were observed, suggesting it may be a useful system for
testing CGs.
iii
ACKNOWLEDGEMENTS
Over the long course of this project, I have been blessed with the help of many
individuals. I would like to acknowledge the help of my advisor Dr. Peter Pauls, whose
guidance lead me to get the most of my work and results. Dr. Gregory Perry was a
constant and invaluable source of help in the lab, especially during the bioinformatics
analyses, and my “technical difficulties”. I would also like to thank Drs. Alireza Navabi
and Paul Goodwin for their assistance and feedback on my thesis.
I would like to thank all of the Pauls lab members, who helped me learn new
procedures and perspectives. Our discussions improved my knowledge on many things
inside and out of the lab, and made my time here truly a world class education. I must
mention Jerlene Nessia, Mahbuba Siddiqua, Loo-Sar Chia, Weilong Xie and Jan
Brazolot, who were my troubleshooting pals throughout my lab experiments.
I would like to thank my family and friends for their encouragement and support
throughout my research and personal struggles. My husband Peter was a constant
source of support in many ways during my studies, and I thank you for all your love and
encouragement.
I am grateful to the various forms and sources of financial support provided by
the University of Guelph, making it possible for me to complete this phase of my
education.
iv
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ……………………………………………………………….. iii
TABLE OF CONTENTS ………………………………………………………………..... iv
LIST OF TABLES ………………………………………………………………………… x
LIST OF FIGURES ……………………………………………………………………….. xii
LIST OF ABBREVIATIONS……………………………………………………………… xiv
1.0 Literature Review ……………………………………….………………………....
1.1 Common Bean ……………………………………………………………....
1.1.1 Nutritional Importance of Dry Bean …………………………....
1.1.2 Centres of Origin …………………………………………………
1.1.2.1 Middle American Landraces ………………………..
1.1.2.2 Andean Cultivated Landraces ………………………
1.1.2.3 Common Bean Diversity and Domestication ……..
1.1.3 Common Bean Genetics ………………………………………..
1.2 Common Bacterial Blight of P. vulgaris …………………………………...
1.2.1 Pathogen Spread, Infection and Symptoms in P. vulgaris …..
1.2.2 CBB Mode of Pathogenicity …………………………………….
1.2.3 Disease Prevention ……………………………………………..
1.3 CBB Resistance in P. vulgaris ……………………………………………..
1.3.1 CBB Resistance Quantitative Trait Loci ……………….………
1.3.1.1 Frequently Used CBB Resistance QTL Markers …
1.3.1.2 Other Significant CBB Resistance Markers ………
1.4 OAC Rex ……………………………………………………………………..
1.4.1 Genetics of CBB Resistance in OAC Rex ………………….....
1.4.2 Major CBB Resistance QTL in OAC Rex ……………………..
1.5 Plant-Pathogen Interactions ………………………………………………..
1.5.1 Mechanisms of Plant Pathogen Resistance …………………..
1.5.1.1 Pathogen Associated Molecular Pattern Triggered
Immunity ……………………………………………...
1
1
1
2
3
4
5
6
6
7
8
9
9
10
11
13
15
15
16
17
17
18
v
1.5.1.1.1 Recognition of Flagellin: An Example of PTI
1.5.1.2 Effector Triggered Immunity ………………………..
1.5.1.2.1 Downy Mildew Resistance in Arabidopsis:
An Example of ETI …………………………..
1.5.2 Diversity in Plant Pathogen Interactions ………………………
1.5.2.1 Genetic Variability and Pathogen Resistance …….
1.5.2.2 Transposable Elements and Pathogen Resistance
1.5.2.2.1 Classifications of Transposable Elements ..
1.5.2.2.2 Retrotransposons and R Gene Function .....
1.5.2.3 Genetic by Environmental Interaction and
Pathogen Resistance ………………………………..
1.5.2.4 R Gene Expression at Different Developmental
Stages …………………………………………………
1.6 R Genes Classes …………….……………………………………………..
1.6.1 Nucleotide Binding Site-Leucine Rich Repeat Proteins ……..
1.6.1.1 NBS Domain ………………………….………………
1.6.1.2 Role of Amino-Terminal Domain …………………...
1.6.1.3 LRR Domain …………………….……………………
1.6.2 Extracellular LRR Proteins …………………………………..…
1.6.2.1 eLRR Domain ……………………...…………………
1.6.2.2 LRR Receptor-Like Kinases …………………….….
1.6.2.3 Receptor-Like Cytoplasmic Kinases ……………….
1.6.2.4 Receptor-Like Proteins ……………………………...
1.6.2.5 Polygalacturonase Inhibiting Proteins ……………..
1.7 R Gene Specificity Evolution ….……………………………………………
1.8 Disease Resistance Research Genomic Resources…………………….
1.8.1 Common Bean Genomics ………………………………………
1.8.2 OAC Rex Genomic Resources ………………………………...
1.8.3 Other Plant Genomic Resources ………………………………
1.9 Hypothesis and Objectives …………………………………………………
19
20
21
22
23
24
24
25
26
26
27
27
28
28
29
29
30
30
31
31
32
33
34
34
35
36
36
vi
2.0 Identification and Characterization of Candidate Common Bacterial
Blight Resistance Genes …………………………………………………………
2.1 Abstract ……………………………………………………………………….
2.2 Introduction …………………………………………………………………..
2.2.1 CBB in Common Bean …………………………………………..
2.2.2 OAC Rex Genomic Library ……………………………………..
2.2.3 R Gene Classifications ………………………………………….
2.2.4 R Gene Identification in OAC Rex ……………………………..
2.3 Materials and Methods ……………………………………………………...
2.3.1 R Gene Homology Identification in OAC Rex Library Clones
2.3.2 Confirmation of Contig Sequences …………………………….
2.3.3 Gene Identification and Characterization ……………………..
2.3.4 CG and Surrounding Sequence Genome Location ………….
2.3.4.1 OAC Rex Genome Assembly Location ……………
2.3.4.2 G19833 Genome Assembly Location ……………..
2.3.4.2.1 Repetitive DNA Analysis ……………………
2.3.5 Characterization of Predicted Proteins ………………………..
2.3.5.1 Domain and Secondary Structure Analysis ……….
2.3.5.2 CG-Specific Analysis ………………………………..
2.3.6 Isolation of CGs ...……………….……………………………….
2.3.6.1 Amplification of CGs …………………..…………….
2.3.6.2 Cloning of CGs ..……………………………………..
2.4 Results ……………………………………………………………………….
2.4.1 Gene Identification in Selected OAC Rex Contig Sequences
2.4.1.1 R Gene Homology Identification ……………………
2.4.1.2 Contig Sequence Assembly Confirmation ………...
2.4.1.2.1 Contig1701 Assembly Confirmation ……….
2.4.1.2.2 Contig1455 Assembly Confirmation ……….
2.4.1.3 Contig1701 Gene Annotation ………………………
2.4.1.3.1 Contig1701 CGs ………………..………..…..
2.4.1.4 Contig1455 Gene Annotation ………………………
37
37
38
38
39
39
41
44
44
44
46
46
46
47
47
48
48
49
49
49
50
52
52
52
52
52
54
54
56
56
vii
2.4.2 OAC Rex Gene Location in OAC Rex Genome Assembly ….
2.4.2.1 G19833 Location for Contig1701 Identified Genes
2.4.2.2 G19833 Location for Contig1455 Identified Genes
2.4.3 Contig1701 Gene and Protein Characterization ……………...
2.4.3.1 Characterization of CGs .……………………………
2.4.3.1.1 CG Similarities …………………..…………...
2.4.3.1.2 CG Domain Analysis ………………………...
2.4.3.1.3 Contig Sequence Retrotransposon Analysis
2.4.3.1.4 CG Secondary Structure Prediction ……….
2.4.3.2 Characterization of Genes with Putative Functions
2.4.3.2.1 Ascorbate Oxidase Gene Homologs ………
2.4.3.2.2 β-Glucan Synthase-Like Homologs ………..
2.4.3.2.3 Hypothetical Gene Annotations …………….
2.4.4 Isolation and Amplification of CGs …………..…………………
2.5 Discussion …………………………………….……………………………..
2.5.1 CG Characteristics ………………………………………………
2.5.1.1 R Gene Characteristics of CGs …………………….
2.5.1.2 Unique/Unusual Characteristics of CGs …………..
2.5.1.3 Retrotransposon Characteristics of CGs ………….
2.5.2 Additional CGs on Contig1701 …………………………………
2.5.2.1 Ascorbate Oxidases and Disease Resistance ……
2.5.3 CG Location in the Bean Genome ……………………………..
2.5.3.1 CBB Resistance Markers and CG G19833
Genome Location ……………………………………
2.6 Conclusion ……………………………………………………………………
59
59
62
67
67
67
67
68
78
78
78
80
90
91
94
94
94
96
97
99
99
100
103
105
3.0 Detached Leaf Xanthomonas axonopodis pv. phaseoli Susceptibility
Assay in Arabidopsis thaliana …………………………………………………..
3.1 Abstract ……………………………………………………………………….
3.2 Introduction …………………………………………………………………..
3.2.1 Common Bean Improvement …………………………………..
3.2.2 CBB in A. thaliana ……………………………………………….
106
106
107
107
107
viii
3.3 Materials and Methods ……………………………………………………..
3.3.1 Bacterial and Plant Growth …………..…………………………
3.3.2 Plant Wounding and Inoculation ……………………………….
3.3.3 Assessment of Disease Symptoms ……………………………
3.3.3.1 Image Collection and Analysis ……………………..
3.3.3.2 CFU Analysis …………………………………………
3.3.4 Statistical Analyses ………………………………………………
3.4 Results ………………………………………………………………………..
3.4.1 Analysis of Variance ……………………………………………..
3.4.2 Visual Observations and IA ……………………………………..
3.4.2.1 Common Bean Visible Leaf Symptoms ……………
3.4.2.2 Arabidopsis Visible Leaf Symptoms ……………….
3.4.3 Leaf Sample CFUs ………………………………………………
3.4.3.1 Common Bean CFUs …………..……………………
3.4.3.2 Arabidopsis CFUs ……………………………………
3.5 Discussion ……………………………………………………………………
3.5.1 Symptom Development …………………………………………
3.5.1.1 Common Bean Symptom Evaluation by IA ............
3.5.1.2 Arabidopsis Symptom Evaluation by IA …………...
3.5.1.3 Symptom Evaluation by CFUs ..……………………
3.5.2 Suitability of Detached Arabidopsis Leaf CBB Assay ………..
3.5.2.1 Variability in CFU Observations ……………………
3.5.2.2 Detached Leaf vs. Attached Leaf Symptom
Progression …………………………………………..
3.6 Conclusion ……………………………………………………………………
109
109
109
111
111
111
112
113
113
113
113
115
118
118
120
127
127
127
129
130
131
131
133
135
4.0 Candidate Common Bacterial Blight Resistance Gene Expression in a
Resistant (OAC Rex) and Susceptible (Seaforth) Variety of Phaseolus
vulgaris ………………………………………………………………………………
4.1 Abstract ……………………………………………………………………….
4.2 Introduction …………………………………………………………………..
4.2.1 Significance of Common Bean …………………………………
136
136
137
137
ix
4.2.2 CBB in Common Bean …………………………………………..
4.2.3 CG Testing in Common Bean …………………………………..
4.3 Materials and Methods ……………………………………………………..
4.3.1 Plant and Inoculum Preparation ……………………………….
4.3.1.1 Plant Growth ………………………………………….
4.3.1.2 Inoculum Preparation ………………………………..
4.3.1.3 Plant Inoculation ……………………………………..
4.3.2 Sample Collection and Analysis ………………………………..
4.3.2.1 Sample Collection and Preparation ………………..
4.3.2.2 RNA Isolation …………………………………………
4.3.2.3 cDNA Transcription ………………………………….
4.3.2.4 Primer Design and PCR Amplification …………….
4.4 Results ………………………………………………………………………..
4.4.1 CG Expression …………………………………………………..
4.4.1.1 CBB Susceptible Genotype (Seaforth) …………….
4.4.1.2 CBB Resistant Genotype (OAC Rex) ……………...
4.5 Discussion ……………………………………………………………………
4.5.1 Observed CG Expression ………………………….……………
4.5.2 Expected CG Expression Patterns …………………………….
4.6 Conclusion ……………………………………………………………………
137
138
139
139
139
139
139
140
140
140
142
142
146
146
146
150
153
153
154
156
5.0 Future Directions and Recommendations ..…………………………………..
5.1 OAC Rex Genome Sequence Assembly …………………………………
5.2 Candidate CBB R Gene Analysis ……………………………………..…..
5.2.1 Identification and Characterization of New CGs ……………...
5.2.2 CG Expression Analysis ……………………………….……….
5.3 Model Plant CBB Inoculation Procedure ………………………………….
157
157
157
157
159
159
6.0 Summary ……………………………………………………………………………. 161
7.0 References .…………………………………………………………………………. 164
8.0 Appendices ...………………………………………………………………………. 193
x
LIST OF TABLES
Table 2.1 DNA sequences and annealing temperatures for primers used to
identify of OAC Rex genomic library clones associated with the PV-ctt001 QTL region of Pv04 ………………………………….…………...
40
Table 2.2 PV-ctt001 associated OAC Rex genomic library clones ……………..
40
Table 2.3 NCBI accession numbers for the NBS-LRR genes used to search for candidate common bacterial blight resistance genes …………….
45
Table 2.4 Locations within the contig1701 sequence assembly and genetic features of contig1701 gene annotations .…………………………......
58
Table 2.5 Locations within the contig1455 sequence assembly and genetic features of contig 1455 gene annotations .………………………….....
60
Table 2.6 Summary of candidate common bacterial blight resistance gene characteristics .………………………………………………………..…..
61
Table 2.7 Predicted locations in G19833 and expression of annotated genes in OAC Rex contig1701 .…………………………………………….…..
64
Table 2.8 Predicted gene locations on OAC Rex contig 1455 in bp with associated G19833 chromosome number, location (in bp), gene or element and possible function ..…………………………………….…..
66
Table 2.9 Similarity between candidate common bacterial blight resistance genes ....……………………………………………………………….…..
69
Table 2.10 Phyre2 secondary structure modelling for candidate gene proteins CBB1, CBB2, CBB3 and CBB4 ……..….………………………….…..
77
Table 2.11 Similarity between contig1701 genes of interest and identified homologues ……………………………………..……….…………..…...
79
Table 2.12 Phyre2 secondary structure modelling for gene 5, Phvul.006G011700, Glyma.20G051900 and 1ASP_A .……………...
87
Table 2.13 Phyre2 secondary structure modelling for gene 7, G2, and Glyma.08G361500 .………………………………………………………
89
xi
Table 2.14 Primers used to amplify candidate genes CBB2 and CBB3 from
OAC Rex DNA ..………………………………………………………….
93
Table 3.1 LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 144 hours post inoculation (HPI).
117
Table 3.2 LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 192 hours post inoculation (HPI).
117
Table 3.3 LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 48 hours post inoculation (HPI) .……………………
122
Table 3.4 LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 96 hours post inoculation (HPI) .……………………
122
Table 3.5 LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 144 hours post inoculation (HPI) ..………………….
123
Table 3.6 LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 192 hours post inoculation (HPI) ..………………….
123
Table 3.7 Inoculated A. thaliana leaf symptom progression .……………………
124
Table 3.8 Inoculated common bacterial blight susceptible P. vulgaris variety leaf symptom progression .………………………………………………
125
Table 3.9 Inoculated common bacterial blight resistant P. vulgaris variety leaf symptom progression .…………………………………………………...
126
Table 4.1 Candidate common bacterial blight resistance gene primer sequences for real time quantitative RT-PCR .………………………..
145
xii
LIST OF FIGURES
Figure 2.1 Alignment of selected OAC Rex genomic library clones around CBB resistance marker PV-ctt001 …………………………………..
43
Figure 2.2 OAC Rex contig1701 sequence confirmation, with alignments between OAC Rex sequence elements and the contig1701 and contig1455 sequence assemblies …………………………………..
55
Figure 2.3 Locations, coding sequences and potential functions of predicted genes on contig1701 ………………………………………………….
57
Figure 2.4 Location, coding sequence and potential function of predicted genes on contig1455 ………………………………………………….
60
Figure 2.5 Candidate common bacterial blight (CBB) resistance genes …….
61
Figure 2.6 Sequence comparisons between OAC Rex contig1701 and syntenic regions in G19833 …………………………………………..
63
Figure 2.7 Alignments of contig1455 and associated match locations within G19833 …………………………………………………………………
65
Figure 2.8 Alignment of candidate common bacterial blight resistance gene coding sequences ……………………………………………………..
72
Figure 2.9 Alignment of candidate gene protein sequences …………………..
73
Figure 2.10 LRR sequence of candidate genes .………………………………....
74
Figure 2.11 Secondary structure models of predicted protein for candidate CBB resistance genes ………………………………………………....
76
Figure 2.12 Alignment and annotation of ascorbate oxidase coding sequence .
83
Figure 2.13 Alignment and annotation of L-ascorbate oxidase amino acid sequences ……………………………………………………………...
85
Figure 2.14 Secondary structure model of OAC Rex and G19833 L-ascorbate oxidase protreins ………………………………………………………
86
xiii
Figure 2.15 Secondary structure model for predicted β glucan synthase-like genes …………………………………………………………………...
89
Figure 2.16 Candidate gene PCR amplification from OAC Rex genomic DNA and BiBAC2 library DNA sources ……………………………………
93
Figure 2.17 Common bacterial blight resistance candidate gene clones ……..
94
Figure 2.18 Location of clone sequence match within contig1455 …………….
94
Figure 3.1 Symptom progression in inoculated P. vulgaris leaves …………...
114
Figure 3.2 Symptom progression in inoculated A. thaliana rosette leaves …..
116
Figure 3.3 Pathogen growth in inoculated P. vulgaris leaf samples ………….
119
Figure 3.4 Pathogen growth in inoculated A. thaliana leaf samples ………….
121
Figure 4.1 Locations of RNA expression primers within candidate genes …..
144
Figure 4.2 Initial candidate gene expression in inoculated Phaseolus vulgaris leaves …………………………………………………………………..
147
Figure 4.3 Subsequent candidate gene expression in second experiment replication of Phaseolus vulgaris leaf inoculation ………………….
148
xiv
LIST OF ABBREVIATIONS
AA – Ascorbic Acid
AO – Ascorbate Oxidase
Avr – Avirulence
BAC – Bacterial Artificial Chromosome
BiBAC – Binary Bacterial Artificial Chromosome
BLAST – Basic Local Alignment Search Tool
CBB – Common Bacterial Blight
CBB1-4 – Common Bacterial Blight Resistance Candidate Genes 1-4
CC – Coiled Coil
CFU – Colony Forming Unit
CG – Candidate Gene
CGM – Candidate Gene Markers
DIRS – Dictyostelium Intermediate Repeat Sequence
EST – Expressed Sequence Transcript
ETI – Effector Triggered Immunity
eLRR – Extracellular Leucine Rich Repeat
HPI – Hours Post Innoculation
HR – Hypersensitive Response
hrp – Hypersensitive Response and Pathogenicity
IA – Image Analysis
Line – Long Interspersed Nuclear Element
LRR – Leucine-Rich Repeat
LTR – Long Terminal Repeat
MAMP – Moleular Associated Molecular Pattern
MAPK – Mitogen-Activated Protein Kinase
MAS – Marker Assisted Selection
NBS – Nucleotide Binding Site
PAMP – Pathogen Associated Molecular Pattern
PCD – Programmed Cell Death
PCR – Polymerase Chain Reaction
PG – Polygalacturonase
PGIP – Polygalacturonase Inhibiting Protein
PLE – Penelope-Like Element
PRR – Pattern Recognition Receptor
PTI – Pathogen Associated Molecular Pattern Triggered Immunity
QTL – Quantitative Trait Locus
xv
R – Resistance
RAPD – Random Amplified Polymorphic DNA
RLCK – Receptor-Like Cytoplasmic Kinase
RLK – Receptor-Like Kinase
RLP – Receptor-Like Protein
ROS – Reactive Oxygen Species
RT – Reverse Transcriptase
SCAR – Sequence Characterized Amplified Region
SINE – Short Interspersed Nuclear Element
SNP – Single Nucleotide Polymorphism
SSR – Simple Sequence Repeat
T3SS –Type Three Secretion System
TIR – Toll-Interleukin Receptor
1
Chapter 1: Literature Review
1.1 Common Bean
Common bean (Phaseolus vulgaris L.) is a member of the Fabacaea family, and
is an important grain legume (pulse) crop species, grown in Canada and globally. It is a
highly produced food legume crop in the world, with the majority of production occurring
in developing countries (Gepts et al. 2008). There are many coloured and white
varieties of edible dry bean in a range of different seed sizes. The most important bean
market classes grown in Canada are navy, black, pinto, dark- and light-red kidney, great
northern and cranberry beans (Bewley et al. 2006; Pulse Canada 2007). Dry beans
produced in Canada are mainly exported to the US and Europe (Agriculture and Agri-
Food Canada 2011), accounting for four times the amount consumed domestically
(Goodwin 2005). The main production areas in Canada are Manitoba, Ontario and
Alberta (Goodwin 2005; Pulse Canada 2015).
1.1.1 Nutritional Importance of Dry Bean
Pulses are recommended as a meat alternative in the human diet by Health
Canada (Health Canada, 2014) . Dry beans contain high levels of high-quality proteins
(Yañez et al. 1995), no cholesterol, and are an excellent source of complex
carbohydrates, such as dietary fibre, starch and oligosaccharides, as well as important
vitamins and minerals such as folate (Tosh and Yada, 2010). A large portion of the
protein component of common bean is made up of the phaseolin protein (Ma and Bliss,
1978), which has been extensively studied (Bollini and Chrispeels, 1978; Bollini et al.
2
1982; Lawrence et al. 1990; Lawrence et al. 1994) and has been shown to be rich in
lysine but poor in methionine (Bressani, 1983; Gepts and Bliss, 1984).
Despite the many beneficial nutritional aspects of incorporating dry beans into
the human diet, there are several factors that contribute to reduced consumption in
developed countries. The first is the presence of anti-nutritional factors such as
protease and amylase inhibitors, lectins, polyphenols and oligosaccharides, whose
effects may be decreased by different cooking methods, but still contribute to low
digestibility (Gupta, 1987). The second is the time required to cook beans, especially
when packaged dry. The long preparation time is a reason they are passed over for
faster prepared foods in developed countries. However, beans are still a major protein
source in some developing countries, especially in South America, and provide up to
40% of the daily protein intake in less developed nations in Africa (Gepts et al. 2008).
1.1.2 Centres of Origin
Common bean originates from Middle- and South-America, with wild common
bean growing from the north of Mexico to the north of Argentina (Gepts and Debouck,
1991). Two major gene pools exist, termed Middle American and Andean, with an
intermediate gene pool from the region between Peru and Ecuador, (Gepts and Bliss,
1986; Gepts, 1988; Debouck et al. 1993). Variation in the sequences of five genes from
Middle American, Andean and Peru-Ecuador wild common bean accessions indicated
that the centre of origin is Mexico, and that subsequent spread and domestication
established the Andean and Peru-Ecuador gene pools (Bitocchi et al. 2012). This was
further supported by Schmutz et al. (2014), using pooled resequencing of 30 individuals
from Middle American and Andean wild genepools, using ~663,000 polymorphic sites at
3
least 5 kb away from genes and not in repeat sequences. This analysis, which was
facilitated by the genome sequence for common bean variety G19833 (reported in the
same paper), confirmed that the wild Andean gene pool originated from the wild Middle
American population, indicating that it was the centre of origin for common bean. Due
to further domestication and geographic separation, the two groups are distinguished
not only by the location, from which they originate, but also by their agronomic and
molecular traits, which are used to sub-classify them (Singh et al. 1991).
1.1.2.1 Middle American Landraces
Within the Middle American group, which is found in wild populations located
from Mexico to Venezuela, there are three races; Mesoamerica, Durango and Jalisco as
was described by Singh et al. (1991). The race Mesoamerica is from the lowlands and
encompasses the black, navy and small red market classes. Varieties of this race grow
either type II (indeterminate growth with continued vegetative growth after flowering,
vegetative terminal buds and strong upright architecture) or type III (indeterminate
growth with weak branches and twining and pods located primarily at the base of the
plant) growth habits (Singh, 1982). Each pod produces 6 to 8 small, cylindrical, kidney
or oval shaped seeds (<25g/100 seed), which can be all possible seed colours in pods
that are slender and 8-15 cm long. The leaves and internode length can be small,
intermediate or large, with cordate, hastate or ovate terminal leaf shape. Flowers are
striped with broad cordate or lanceolate bracteoles, petals can be white, white with pink
stripes or purple, and inflorescences are multi-noded. The Durango race is from the
semi-arid highlands of Mexico and encompasses pinto, great northern, medium red and
pink market classes. These varieties predominantly have indeterminate, prostrate, type
4
III growth habits. They have small to medium ovate or cordate leaflets and thin stems
and branches with short internodes. Fruiting mainly occurs from the basal nodes, and
the flowers produce 5 to 8 cm long flattened pods containing 4 to 5 medium sized seeds
(25-40g/100seeds). Seed colour ranges from tan to yellow, cream, gray, black, white,
red or pink and may have stripes or spots. Finally, the Jalisco race is located in the
southern part of the Durango range and encompasses black, small red and yellow
market classes. These varieties have indeterminate type IV growth habit and can reach
total plant height of over 3 m in native environments. The leaves are hastate, ovate or
rhombohedric, stems and branches are weak, and internodes are medium to long.
Fruiting occurs along the entire length of the plant, but is concentrated in the upper part.
The flowers produce 5-8 small to medium sized round or oval seeds in pods that are 8-
15 cm long.
1.1.2.2 Andean Cultivated Landraces
Singh et al. (1991) also described three races that fall within the Andean centre
of origin, and which are found in Peru, Chile, Bolivia and Argentina; these are called
Nueva Granada, Chile and Peru. The Nueva Granada race, which encompasses the
majority of large seeded and horticultural snap bean market classes, is found in a
variety of altitudes and climates as well as continents. These varieties have type I
(determinate growth with reproductive terminal buds and limited or no continued
vegetative growth after flowering) (Singh, 1982), II and III growth habits, with medium to
long internodes and large hastate, ovate or rhombohedric leaves with dense hairs. The
flowers have small to medium bracteoles that are ovate, lanceolate or triangular, and
produce large pods (10-20 cm) with 4-6 seeds. The seeds are medium (25-40g/100
5
seeds) to large (>40g/100 seeds) and come in a variety of seed colours. Varieties within
the Chile race are found in the southern Andes and have indeterminate type III growth
habits, with small or medium sized hastate, rhombohedric or ovate leaves and small
stem internodes. The flowers are light pink or white with small to medium sized
triangular, spatulate or ovate bracteoles, and produce medium sized pods (5-8 cm) with
3-5 round-to-oval shaped seeds, which are predominantly harvested as green,
immature seeds. The final Andean race, Peru, is grown in the Andean highlands, and
encompasses varieties which have either indeterminate or determinate type IV climbing
growth habits (Debouck et al. 1988). These varieties have large hastate or lanceolate
leaves, and long, weak internodes, which corresponds with the fact that they are
generally grown in association with maize and other crops in their natural habitat (Singh
et al. 1991). Fruiting occurs along the length of the plant or concentrated at the top, and
produces pods that are 10-20 cm long, with large round or oval seeds.
1.1.2.3 Common Bean Diversity and Domestication
As can be seen in the summary above of the more detailed observations
presented by Singh et al. (1991), P. vulgaris is a very diverse species, both between
and within centres of origin and races. This is not only reserved to phenotype, but also
extends to nutritional contents within the seeds and pods (Singh et al. 1991). Much of
the diversity of observed traits can be attributed to the domestication process which
occurred between ~8500-~8200 years ago for the Mesoamerica genepool and ~7000-
~6300 years ago for the Andean genepool (Mamidi et al. 2011). Domestication genes
that have been identified previously are involved with plant inflorescence structure, seed
colour number and size, and harvestability (reviewed by Glémin and Bataillon, 2009).
6
Genome sequence analysis by Schmutz et al. (2014) identified 1,835 Mesoamerican
and 748 Andean candidate domestication genes, with the number and type being
variable across the subpopulation groups discussed above. Examples of the types of
candidate genes identified include flowering, vernalization, photoperiod regulation,
increased plant size, nitrogen metabolism and increased seed size and weight.
1.1.3 Common Bean Genetics
Common bean is a diploid species with 2n = 2x = 22 chromosomes. The genome is
estimated to be 600 Mb (Gepts et al.2008). P. vulgaris is closely related to Glycine max
(soybean), and both are Phaseoleae legumes. There is evidence that the soybean
genome is the product of a duplication event and further fractionation and reassembly of
the common ancestor for it and dry bean (McClean et al. 2010; Schmutz et al. 2014).
This relationship makes the soybean genome an excellent resource for genetic
comparisons and gene discovery. Even though comparisons between the two genomes
have shown that common bean has evolved more rapidly than G. max (Schmutz et al.
2014), it can still be used as a reference for gene number, function and organization,
and has proven to be useful for ongoing P. vulgaris sequencing efforts as described
below.
1.2 Common Bacterial Blight of P. vulgaris
Common bacterial blight (CBB) is a significant seed borne disease of common
bean, caused by the Gram-negative bacterial pathogen Xanthomonas axonopodis pv.
phaseoli (Xap) and its fuscans variant Xanthomonas fuscans subsp. fuscans (Xff)
(Gabriel et al. 1989; Vauterin et al. 1995; Schaad et al. 2006). Common bean is the
primary host of CBB, although alternative hosts can be found among other members of
7
the Fabacaea family (Hayward, 1993), and Arabidopsis ecotype Columbia has been
shown to be susceptible to manual inoculation (Perry, 2010). The disease is seen
wherever beans are produced, and can reduce yield from 10-45%, depending on the
environmental conditions and genotype (Saettler 1989; Gillard et al. 2009). The effect of
the disease is most severe on non-resistant varieties grown in warm, humid growing
conditions.
1.2.1 Pathogen Spread, Infection and Symptoms in P. vulgaris
The primary source of Xap inoculum is infected seeds, but the pathogen may
also be introduced into established fields by infected crop debris or secondary hosts
growing alongside fields (Vidaver 1993). Infection by Xap occurs through wounds,
stomata, or from infected cotyledons (Zaumeyer and Thomas, 1957). The initial
bacterial introduction is followed by cell proliferation and accumulation of extracellular
polysaccharide in the intercellular spaces (Rudolph, 1993). Leaf symptoms begin as
water-soaked areas appearing anywhere on the leaf between 4 to10 days after
inoculation, corresponding to the regions of bacterial cell proliferation. The bacteria will
also enter degrading plant cells adjacent to colonies and begin to multiply, resulting in
the expansion of water-soaked lesions on the leaves (Rudolph, 1993). As the spots
grow, they may merge, becoming necrotic and sometimes developing a surrounding
chlorotic zone (Vidaver, 1993).
With the progression of the disease, bacterial cells may enter the vascular tissue
and spread throughout the plant (Rudolph, 1993). Although stem symptoms are less
frequently seen, they have a similar look and progression to leaf symptoms (Vidaver,
1993). Pod symptoms develop differently however, beginning as water-soaked lesions
8
and becoming slightly sunken and brown or red-brown over time. Seed symptoms are
only visible on light coloured seed coats, and appear as yellow to brown irregular spots.
Seeds may also rot or shrivel, which greatly decreases the economic value of diseased
yield (Vidaver, 1993).
1.2.2 CBB Mode of Pathogenicity
The ability of bacteria to infect a given plant, pathogenicity, involves large
numbers of genes. An excellent example of this are the hypersensitive response and
pathogenicity (hrp) genes, which are a conserved group of bacterial genes involved in
the interaction between gram negative bacteria, such as Xanthomonas, and their hosts
(Kamoun and Kado 1990; Bonas et al. 1990). These genes tend to be associated with
the Type III secretion system (T3SS) in the bacterial cell wall (Van Gijsefem et al. 1995).
However, they have also been implicated in the regulation of expression and secretion
of proteins involved in pathogenicity directly from the bacterial cell to the plant host cell,
as well as bacterial cell motility (Van Gijsefem et al. 1995; Agrios, 2005).
These secreted proteins, called effectors, have a variety of functions related to
pathogenicity. Examples include the formation of motility structures such as the flagella
in Pseudomonas solanacearum (Van Gijsefem et al. 1995); proteases such as prt1 and
prt2, and pectin degrading polygalacturonases (PGs) which are involved in
Xanthomonas campestris pv. campestris (Xcc) infection of crucifers, causing black rot
(Dow et al. 1990; Wang et al. 2008a). The complement of proteins that are employed in
pathogenicity are specific to the bacteria injecting them. In certain cases, host species
have evolved mechanisms to recognize these effectors and use their presence to
initiate resistance reactions (Agrios, 2005), as will be discussed below.
9
1.2.3 Disease Prevention
One of the most common practises for prevention of Xap infection in affected
areas is the use of disease free seed. This seed is produced in arid areas where a low
frequency of disease is found and where preventative management to limit introduction
of the pathogen is performed. However, in a study performed by Darrasse et al. (2007),
it was found that inoculated common bean plants grown in environments that were
suboptimal for Xap proliferation were still colonized by the bacteria, although symptoms
were not observed. This is a major concern to bean growers, since the use of disease
free seed is so important for disease prevention in a production setting. Given that the
presence of common bacterial blight in a common bean crop can reduce yield
significantly (Saettler, 1989; Tar’an et al. 2001; Gillard et al. 2009), and that chemical
application control measures provide no significant reduction in infection severity and
effect (Weller and Saettler, 1976), the development and use of CBB resistant varieties
of common bean has become a more practical and attractive alternative in the efforts to
reduce yield loss to the disease.
1.3 CBB Resistance in P. vulgaris
P. vulgaris has little natural resistance to CBB, however, there are currently a few
registered varieties of common bean that are resistant to infection by Xap. Resistance
has been introduced to common bean via inter-specific crosses to close relatives of P.
vulgaris such as tepary bean (Phaseolus acutifolius) (Parker, 1985) and scarlet runner
bean (Phaseolus coccineus) (Miklas et al. 1994). P. accutifolius shows differential
levels of resistance to different Xap isolates, which Opio et al. (1996) suggested
indicates a gene-for-gene interaction between host and pathogen, with 5 gene pair
10
interactions providing the simplest explanation. However, inoculation of the progeny of
four resistant by susceptible crosses with a single isolate (484a) indicated that
resistance was controlled by one or two dominant genes for three resistant parents, and
quantitative resistance for the fourth resistant parent (Urrea et al. 1999).
This wide range in the resistance responses depending on the Xap isolate used
has also been observed in different resistant common bean genotypes (Opio et al.
1996; Mutlu et al. 2008), and multiple genomic regions have been shown to control the
reaction (Shi et al. 2011). Resistance to CBB in common bean is characterized by a
high to moderate slowing of disease symptom progression, and a lack of internal seed
infection (Aggour et al. 1989). This partial resistance suggests that not all of the
multiple CBB resistance-related genes were transferred to P. vulgaris through the
interspecific crosses, or that the transferred genes don’t function at full capacity in the
common bean background.
Current advances in developing CBB resistant common bean varieties include
combining multiple sources of resistance (pyramiding). This approach may lead to
higher levels of resistance and may reduce the chances that the resistance may be
overcome by the pathogen. This may ultimately result in the production of varieties
containing a resistance system which is more robust and would reduce the potential for
development of resistance in the pathogen to plant defences.
1.3.1 CBB Resistance Quantitative Trait Loci
Resistance to common bacterial blight in P. vulgaris is a quantitative trait,
meaning it segregates in a non-Mendelian fashion and involves multiple genes (St.
Clair, 2010). Genes involved in the trait are affected by other genes as well as the
11
environment. Quantitative trait loci (QTLs) are regions in the genome containing
gene(s) for the trait of interest. To map QTLs, individuals in a population are analyzed
for genetic markers to determine the relationship to a particular phenotype, for example,
resistance to a disease. The phenotypic and genotypic data obtained from the
population as a whole is then used to determine the location of the QTL (St Clair, 2010),
and markers shown to be associated with particular QTL are then used to determine its
presence or absence in a plant for the purpose of trait selection.
Since the introduction of CBB resistance through interspecific crosses with P.
acutifolius, many linkage maps have been cdeveloped to determine the locations of
QTLs for CBB resistance (i.e. Miklas et al. 2000; Tar’an et al. 2001; Blair et al. 2003;
Cordoba et al. 2010; Shi et al. 2011), which identified 22 minor and major effect CBB
resistance QTLs across the 11 linkage groups. Although these maps do not identify
specific genes associated with resistance to CBB, markers linked to QTL can be used
for selection, as they identify the regions in the genome which likely contain genes for
resistance to the disease. Markers also provide the opportunity to identify genes that
may be related to a particular QTL when the linkage map is compared to a physical map
(i.e. Perry et al. 2013). Thus, QTL, linkage maps and markers can, and have been
excellent tools, not only for the selection of traits related to CBB resistance in common
bean, but to study the genetic mechanisms of resistance.
1.3.1.1 Frequently Used CBB Resistance QTL Markers
Markers which have been frequently used for CBB resistance selection, and
account for the most variability in resistance phenotypes across multiple genetic
backgrounds are SU91 and BC420 (Pedraza et al. 1997; Yu et al. 2000b). The
12
resistance associated with both sequence characterized amplified region (SCAR)
markers originated from the dry bean line XAN159, which resulted from an interspecific
cross with P. acutifolius accession PI31944.
Marker SU91 has been reported to be on Pv08 (Miklas et al. 2006; Shi et al
2011; Perry et al. 2013) and BC420 has been reported to be on Pv06 (Yu et al. 2000b;
Shi et al. 2011). In the study by Vandemark et al. (2008), it was shown that both of
these dominant markers are part of a recessive epistatic interaction. In this interaction,
the recessive su91//su91genotype supresses the expression of heterozygous or
dominant homozygous BC420. The most resistant phenotypes were seen when at least
one dominant allele was present for both BC420 and SU91. However, since both
markers are dominant, it is difficult to determine when a given genotype is homozygous
for the dominant allele of either or both markers. This makes selection for genotypes
that are homozygous dominant for both BC420 and SU91 difficult.
BC420 and SU91 are the most often used markers for determining the presence
of resistance QTL in common bean accounting for 64% and 17% of phenotypic variation
respectively (Miklas et al. 2006). BC420 is estimated to be 7.1 cM away from the
associated resistance QTL (Yu et al. 2004), and the distance between SU91 and its
associated resistance gene is estimated to be 1-2 cM (Xie et al., personal
communication). These two markers are not perfect indicators of resistance, and may
result in the identification of false positives or negatives, but they are still useful tools
when breeding for CBB resistance.
To improve prediction capabilities for the QTL which SU91and BC420 are
associated with, Shi et al. (2012) developed new markers through the use of a genomic
13
library available for resistant common bean variety HR45 (Liu et al. 2010). Candidate
gene markers (CGMs) were developed for genes present in bacterial artificial
chromosome (BAC) library clones associated with both SU91 and BC420 (Shi et al.
2012).
Although common bean is recalcitrant to transformation, Shi et al. (2012) were
able to determine that several of the CGMs accounted for more of the variability in
resistance phenotypes than the original markers did. This was shown by testing for the
presence of the CGM expression in resistant (Heterozygous dominant BC420 and
SU91) and susceptible (heterozygous recessive BC420 and SU91) near isogenic lines
(NILs) under disease pressure. Since the CGMs were developed by identifying genes
shown to be involved in disease resistance within the SU91 and BC420 QTL regions, it
was expected that they would provide a more specific method of selection for the trait
during breeding. This assumption was validated for SU91 in a recombinant inbred line
(Shi et al. 2012), which showed that CGMs accounted for greater phenotypic variation
both in the growth room (R2 value up to 0.36) and in the field (R2 value up to 0.42). One
of the CGMs was also found to be co-dominant, making identification of the
homozygous or heterozygous states easier.
1.3.1.2 Other Significant CBB Resistance Markers
Two other significant markers used for identification of CBB resistance QTL
include simple sequence repeat (SSR) marker PV-ctt001 and SCAR marker SAP6. The
PV-ctt001 marker was identified in the resistant common bean variety OAC Rex,
accounts for 42.2% of variation (Tar’an et al. 2001), and is located at the end of the
Pv04 (Yu et al. 2000a; Perry, 2010). However, subsequent studies using OAC Rex as a
14
resistant parent have not shown this marker to be involved in CBB resistance (Larsen,
2005; Durham et al. 2013). This suggests that PV-ctt001 may have been a false positive
detection in the original study, and that other abiotic (ie temperature and humidity) and
biotic (ie. common bean disease Colletitrichum lindemuthianum) factors may have been
responsible for the increased variability accounted for by PV-ctt001 (personal
communication; Alireza Navabi). The effect of the common bean disease anthracnose
(C. lindemuthianum) is a likely possibility, since the same region of the Pv04 has been
the focus of studies on a cluster of multiple resistance (R) genes and major effect QTLs
for resistance to anthracnose (Geffroy et al 1999; Geffroy et al 2000; Ferrier-Cana et al.
2003; Campa et al. 2011). However, multiple resistance type genes are predicted to be
present in a large cluster in the same region of Pv04 (Schmutz et al. 2014), suggesting
other potential resistance interactions
SAP6 is a dominant marker for CBB resistance that was identified in great
northern cultivar Montana No. 5 on Pv10 (Miklas et al. 2000) and accounts for 35% of
resistance variation in an F2 population (Miklas et al. 2003). Although this marker was
shown to be associated with a major effect QTL for CBB resistance, when Vandemark
et al. (2009) attempted to combine SAP6 and SU91 in a single population, it was found
that of the two, SU91 was primarily responsible for resistance. They discussed the
possibility that the linkage between SAP6 and its associated QTL might not be strong,
and that recombination was the cause of the lack of resistance conferred by the
presence of the marker, as was evidenced by the presence of the marker in susceptible
bean cultivar Matterhorn (Miklas et al. 2003). Although markers provide a good
indication of the desired trait, the SAP6 marker highlights the need for identifying the
15
gene(s) that are responsible for CBB resistance. With gene-based markers there is an
improved ability to select for the desired phenotype.
1.4 OAC Rex
OAC Rex was the first CBB-resistant variety of common bean registered in
Canada, and is the result of a cross between the HR20-728 and MBE 7 bean lines
(Michaels et al. 2006). Resistance to CBB originated from an inter-specific cross with
naturally resistant tepary bean (P1440795) (Parker, 1985). OAC Rex produces white
navy bean seeds and displays resistance to CBB in leaves and pods (Michaels et al.
2006). Although resistance to infection by Xap in P. acutifolius is characterized as a
hypersensitive response (HR), and likely involves gene-for-gene resistance (Opio et al.
1996), OAC Rex lacks HR when infected. Instead, a decrease in disease symptom
severity is observed, allowing for increased yield in resistant varieties under disease
pressure when compared to non-resistant varieties under the same conditions (Tar’an
et al. 2001; Gillard et al. 2009).
1.4.1 Genetics of CBB Resistance in OAC Rex
In the case of OAC-Rex and other varieties that are resistant to Xap but do not
exhibit HR in the presence of the pathogen, it is likely that some, but not all of the genes
for resistance were transferred from the resistant donor. Assuming this is the case, key
signalling or recognition genes may be missing, which slows the resistance reaction.
This is supported by the observation that disease progression and symptom
development is often delayed and less severe in these resistant varieties as opposed to
the small contained necrotic region associated with HR. Although complete resistance
isn’t present, the slowed disease progression is sufficient to protect yield compared to
16
susceptible varieties under disease pressure (Tar’an et al. 2001, Gillard et al. 2009). It
must also be noted that a strategy to use multiple partial resistance genes may be a
more robust system of resistance, since it may be more difficult for the pathogen to
overcome that kind of resistance.
1.4.2 Major CBB Resistance QTL in OAC Rex
QTL analysis of CBB resistance in OAC Rex performed by Tar’an et al. (2001)
indicated the involvement of at least one major R gene and two minor QTLs. The major
R gene, associated with the PV-ctt001 marker, was originally placed on the Pv05
linkage group (Tar’an et al. 2001) but the original SSR mapping study by Yu et al.
(2000a) had reported the position of Pvctt001 on Pv04. Also, subsequent studies
localized the marker on Pv04 (Perry, 2010; Perry et al. 2013). The location of this
marker at the end of the linkage group in both cases is most likely the reason for
differing reports. Since the most recent report (Perry, 2010) suggested the marker was
present on the Pv04 linkage group, the region associated with the PV-ctt001 marker on
this linkage group has been used for a preliminary candidate gene search as described
below.
Another disease resistance marker, SU91, was not initially identified in OAC Rex
as being associated with a resistance QTL (Tar’an et al. 2001). However, the SU91
sequence is present in the OAC Rex genome as confirmed by Perry et al. (2013), and
further testing has shown the marker to be associated with a major effect QTL in
progeny of OAC Rex (Durham et al. 2013). Association mapping performed by Shi et
al. (2011), which used 469 bean cultivars and breeding lines and 132 bean single
nucleotide polymorphisms (SNPs) has indicated marker SU91 is located on the Pv08
17
linkage group, and comparisons between the genome sequence of Andean common
bean line G19833 and OAC Rex by Perry et al. (2013) provide support for this location
in OAC Rex.
1.5 Plant-Pathogen Interactions
The majority of microbes are non-pathogenic towards most plant species, but in
some cases, a parasitic, or disease interaction may evolve. Due to their stationary
nature and lack of a circulatory immune system such as those found in mammals,
plants have developed complex systems for pathogen recognition and signalling
defense responses. This involves a diverse complement of genes related to pathogen
resistance, which encode proteins specific to the role they are needed for. These genes
may be major effect resistance genes, which have a high level of specificity and efficacy
on their own, or they may be minor effect resistance genes, which act in conjunction
with other minor and major effect genes to provide resistance to a particular disease,
race or strain. In either case, the expression of these genes can be induced in
response to an invading pathogen or constitutively expressed in the plant as a whole, or
in specific locations.
1.5.1 Mechanisms of Plant Pathogen Resistance
One of the most important steps in resisting a pathogen for any organism is the
recognition that there is an attacking entity present. The absence or retardation of
pathogen recognition can mean the difference between disease resistance and
susceptibility, as it can mean responses may not be started or may be too slow to be
effective. Plants are no exception, and just as there are a variety of pathogen types
with diverse strategies for plant infection, there are a variety of mechanisms for
18
recognizing them. These mechanisms fall into two broad categories called pathogen
associated molecular pattern (PAMP) or microbe associated molecular pattern (MAMP)
triggered immunity (PTI), or effector triggered immunity (ETI), and which may overlap,
or complement each other (reviewed by Jones and Dangl 2006; Block et al. 2008;
Padmanabhan et al. 2009; Rafiqi et al. 2009).
1.5.1.1 Pathogen Associated Molecular Pattern Triggered Immunity
The initial, more general form of recognition and defense is called PTI (Jones
and Dangl 2006). This line of defense involves the recognition of molecules which are
conserved among many classes of microbes (PAMPs/MAMPs), but are not necessarily
involved in pathogenicity. Examples of PAMPs/MAMPs include the flagellin in bacterial
flagella, or chitin which is a cell wall component specific to fungal cells (Zipfel and Felix,
2005). These molecules are recognized via pattern recognition receptors (PRRs),
which are generally membrane bound proteins with recognition domains that are
located extra-cellularly, and which may have an intracellular kinase domain for further
signalling (Zipfel, 2008). Their role is to monitor for the presence of microbes, by
recognizing the conserved PAMPs/MAMPs, whether or not it is generally pathogenic
toward that species.
Once a pathogen is recognized, different intracellular responses ensue, such as
signalling via MAP kinase phosphorylation cascades (Asai et al. 2002). Ultimately, a
defense response occurs via the activation of defense genes. The effect of PTI on the
plant may range from increased cell wall thickness, closing of stomata to prevent
bacterial access, increases in hormone levels, production of reactive oxygen species
production and defense gene expression (Taguchi et al. 2003; Desaki et al. 2006;
19
Melotto et al. 2006). PTI is an effective defense strategy for the majority of microbes
that plants come into contact with, on a daily basis. However, the initial recognition of a
microbe can be overcome by a virulent species through mutation of the conserved
molecule, which allows it to avoid PTI and become pathogenic (Zipfel, 2008).
Resistance is then dependent on the recognition of other molecules produced by the
pathogen, whether it is another PAMP or a protein directly involved in pathogenicity, as
will be discussed below.
1.5.1.1.1 Recognition of Flagellin: An Example of PTI
A well-studied example of PTI is the recognition and response to flagellin. This
molecule is the building block molecule of the bacterial flagella, the membrane
protrusion responsible for cellular motility, and is an important factor for many bacteria,
whether plant pathogenic or otherwise. Although the internal parts of flagellin can be
very different between bacterial species, there are well conserved regions at the ends
(Murthy et al. 2003), which are the targets of recognition of PRRs (Gómez-Gómez et al.
1999; Asai et al. 2002). The N-terminal domain is the most highly conserved part of
flagellin, and a synthesized peptide (flg22) from this region has been shown to induce
typical defense responses, such as increased ethylene and reactive oxygen species
production and induction of defence related genes (Felix et al. 1999; Gómez-Gómez et
al. 1999; Asai et al. 2002).
Recognition of the flagellin molecule occurs via the PRR flagellin sensing 2
(FLS2), which is a LRR-receptor like kinase (LRR-RLK) that is expressed in flowers,
stems, leaves and roots, even in the absence of flg22 (Gómez-Gómez and Boller,
2000). The FLS2 protein has an LRR domain for PAMP/MAMP recognition, a
20
membrane spanning domain, and a serine/threonine protein kinase domain (Gómez-
Gómez and Boller, 2002). It acts in the presence of flg22 with another LRR-RLK called
BRI1-associated receptor kinase 1 (BAK1) due to its association with the
brassinosteroid receptor BRI1 (Li et al. 2002; Chinchilla et al. 2007). Defense
responses are induced by the FLS2-BRI1 association by initiating signalling cascades
via mitogen-activated protein kinases (MAPKs), resulting in the activation of defense-
related genes via WRKY transcription factors (Asai et al. 2002). In Arabidopsis,
downstream responses such as oxidative burst, callose deposition, ethylene production
and the expression of defense-related genes FRK1, GST1, PR1 and PR5 were
observed at different time points post-treatment (Asai et al. 2002)
1.5.1.2 Effector Triggered Immunity
Although PTI may be effective in responding to the presence of PAMPs/MAMPs,
it can also be overcome by a successful pathogen, by either altering the conserved
molecule, or by producing molecules that restrict host resistance responses such as
kinase signalling and protein transport (Reviewed by Jones and Dangl, 2006; Block et
al. 2008; Padmanabhan et al. 2009). These proteins that are involved with initiating and
maintaining pathogenesis are called effectors. They are secreted by the pathogen into
the host cell or surrounding extracellular region, and may trigger the form of resistance
called ETI. Recognition of effectors generally occurs within the cell via the protein
products of R genes. R genes are generally major effect genes, and are most
commonly of the NBS-LRR class. ETI can involve direct or indirect recognition of the
molecule. Direct recognition of the pathogen involves the interaction of the LRR domain
of the R protein with the pathogen effector. Indirect recognition, which is the more
21
common form of pathogen recognition, is mediated by NBS-LRR proteins, and involves
monitoring a host molecule for changes made by a pathogen effector protein (Jones
and Dangl, 2006; Padmanabhan et al. 2009).
As with PTI, recognition of effectors leads to a series of responses resulting in
ETI. This includes an oxidative burst, changes in hormone ratios, and signalling
cascades via kinase activation and transcription factors, and eventually leads to a
resistant response (Ryals et al. 1996; Dorey et al. 1997; Torres et al. 2005).
Alternatively to PTI, ETI may lead to the more severe hypersensitive response (HR), in
which infected and surrounding cells undergo apoptosis to restrict expansion of the
pathogen. This method of resistance is only effective on obligate biotrophs, such as
bacteria, because they require a living host cell to obtain nutrients and survive. By
sacrificing the infected cell, the plant stops the progression of the infection into the
surrounding healthy tissue. Conversely, if the pathogen were necrotrophic, killing cells
to obtain nutrients from them, the HR would not decrease pathogen expansion since it
would still be able to obtain nutrients from the dead cells (reviewed by Glazebrook,
2005).
1.5.1.2.1 Downy Mildew Resistance in Arabidopsis: An Example of ETI
An example of ETI are the Recognition of Peronospora parasitica genes (RPP),
which confer resistance to downy mildew (Hyaloperonospora arabidopsidis) (Hpa) in
Arabidopsis (Parker et al. 1997; Botella et al. 1998; van der Biezen et al. 2002). The
RPP genes are present in two clusters, the RPP5 and RPP1 clusters, which are located
on chromosomes 4 and 3 respectively (Parker et al. 1997; Botella et al. 1998; Noël et al.
1999). The functional members of these large gene clusters encode Toll interleukin
22
receptor (TIR) nucleotide binding site NBS-LRR class of resistance proteins (discussed
below), and recognize the presence of the Hpa effector proteins Arabidopsis Thaliana
Recognized (ATR) (Parker et al. 1997; Botella et al. 1998; van der Biezen et al. 2002;
Gunn et al. 2002; Krasileva et al. 2011; Goritschnig et al. 2012). There is variability
seen in the LRR domain sequence, however, the NBS region for RPP gene family
members are highly conserved (Noël et al. 1999). The variability which is seen in the
different RPP gene family members corresponds to the range in specificities required to
recognize the different Hpa effectors in a gene-for-gene fashion (Botella et al. 1998;
Rehmany et al. 2005; Fabro et al. 2011; Krasileva et al. 2011). In the case of RPP1,
recognition of ATR1 occurs through the association of the LRR domain of RPP1 with
the effector protein, and the TIR domain facilitates signalling and induction of defense
genes (ie PAL, PBS2/3 and SID1/2), and hormone (ie. salicylic acid) production, which
ultimately results in HR (van der Biezen et al. 2002; Krasileva et al. 2010).
1.5.2. Diversity in Plant-Pathogen Interactions
Throughout the interactions between the different plant species and the
pathogens that affect them, similarities and trends can be seen, and classifications of
the related genes and proteins can be made. However, the mechanisms for individual
plant-pathogen interactions are complex, and may also be affected by several
interchangeable factors. These factors include the genetic background of the plant
and/or the pathogen, the environment in which the interaction is occurring, and the
developmental stages of the plant and pathogen.
23
1.5.2.1 Genetic Variability and Pathogen Resistance
The genetic background of the plant is an important consideration, especially
when dealing with highly cultivated crops. Some pathogen resistance mechanisms
require the presence of multiple genes for recognition of a pathogen to produce a
complete resistance reaction. Examples include the FLS2/BAK1 complex required for
complete downstream resistance reaction to flagellin in Arabidopsis (Chinchilla et al.
2007), the complex formed between Pi5-1 and Pi5-2 that confer resistance to rice blast
(Magnaporthe oryzae) in rice (Lee et al. 2009), and the complexes formed between Prf,
Pto and Pto-homologues which confer resistance to bacterial speck disease
(Pseudomonas syringae pv. tomato) in tomato (Chang et al. 2002; Mucyn et al. 2006;
Gutierrez et al. 2010). In these cases, the absence of regulatory genes or genes that
would normally work together to form a complex translates into a reduction in, or non-
reaction to the pathogen.
There is also a complex interplay between the genetics of the plant host and the
pathogen. The interaction between resistance genes in the host plant and avirulence
(Avr) genes in the pathogen, combine to produce the resistance reaction on the host
that we see. In general terms, when the pathogen has superior Avr expression, disease
symptoms are seen, and when the plant expresses superior resistance genes, disease
symptoms are either not present, or significantly reduced. Pathogens with different
genetic backgrounds that are of the same species are called races, to make a
distinction between the differences in pathogenic abilities. This interplay between host
and pathogen genetic variability is called race-specific resistance. An excellent
example of race-specific resistance is the interaction between races of anthracnose
24
(Coletotrichum lindemuthianum) and common bean. There are multiple races of bean
anthracnose, and multiple resistance genes, called Co, have been identified, and they
provide resistance to different anthracnose races when present in different
combinations (reviewed by Kelly and Vallejo, 2004; Ferreira et al. 2013).
1.5.2.2 Transposable Elements and Pathogen Resistance
In most cases, the genetic background of a plant species refers to which genes
and alleles are present, and how their presence and combination affects the reaction to
the presence of a pathogen. However, sometimes other genetic elements, such as
transposable elements, can have an effect on gene function.
1.5.2.2.1 Classifications of Transposable Elements
Transposable elements are repetitive sequences within a genome that are able
to move within the genome. There are two classifications of transposable element,
which is based on the intermediate used for their movement (transposition) within the
genome: Type I retrotransposons and Type II DNA transposons, which use RNA and
DNA as their transposition intermediate, respectively (Finnegan, 1989). These
classifications have been further divided into orders and super-families, to reflect the
differences in insertion mechanisms and enzyme characteristics (Wicker et al. 2007).
Type I retrotransposons are divided into the orders long terminal repeat (LTR),
Dictyostelium intermediate repeat sequence (DIRS), Penelope-like elements (PLE),
long interspersed nuclear element (LINE) and short interspersed nuclear element
(SINE), which are found in plants, mammals, fungi and other eukaryotes. Despite
differences in their size, organization, and the number and type of encoded proteins, the
main distinguishing features of retrotransposons are the presence of a reverse
25
transcriptase, and the production of a new copy with each replication cycle (for
complete review see Wicker et al. 2007).
Type II DNA transposons are classified into two subclasses based on the number
of DNA strands cut during transposition: subclass I encompasses orders TIR and
crypton, which mainly use transposase to “cut and paste” from and into double stranded
sites; subclass II is comprised of the helitron and maverick orders, which use a range of
proteins to “copy and paste” from and into single stranded sites. Unlike the Type I
retrotransposons, the main unifying feature of Type II DNA transposon subclasses are
the use of the DNA intermediate for transposition (for complete review of mechanisms
and proteins see Wicker et al. 2007).
1.5.2.2.2 Retrotransposons and R Gene Function
In addition to their role as a major source of highly repetitive regions,
retrotransposons also have been shown to affect the function of disease resistance
genes in plants. In many species, retrotransposons are found in areas where gene
clusters are rapidly evolving, such as disease resistance related genes in rice (Miyao et
al. 2003), lettuce (Meyers et al. 1998), barley (Marcel et al. 2007), common bean
(Vallejos et al. 2006; David et al. 2009), poplar (Lescot et al.2004), sugar beet
(Kuykendall et al. 2009) and Arabidopsis (Yi and Richards, 2007). Retrotransposons
have also been shown to cause transcription of neighboring disease resistance genes
(Hernández-Pinzón et al. 2009), cause chimeric proteins with resistance genes
(Kashkush et al. 2003; Wang and Warren, 2010), and re-functionalize inactive
resistance genes (Hayashi and Yoshida, 2009).
26
1.5.2.3 Genetic by Environmental Interaction and Pathogen Resistance
In addition, the genetic background is affected by the environment, which can
make the evaluation of resistance gene effectiveness difficult. This genetic (G) by
environmental (E) interaction (G x E) is not unique to pathogen resistance, but the effect
is two-fold in that the conditions present during plant growth and development affect
host plant physiology and host gene expression as well as the ability of the pathogen to
infect the host. Plant resistance genes have been shown to be affected by temperature
(Fu et al. 2009; Jorgensen, 2012), soil nutrient composition (Jorgensen, 2012) humidity
(Xiao et al. 2003; Zhou et al. 2004a) and light levels (Xiao et al. 2003), and may be
affected at either high or low extremes. The typical response measured in these
experiments is the lack of HR, which indicates that resistance genes with high resource
and energy requirement are the primary target to conserve energy in increased abiotic
stress. However, there are likely other less visibly affected resistance genes that have
yet to be studied.
1.5.2.4 R Gene Expression at Different Developmental Stages
Some resistance genes are differentially expressed depending on the
developmental state of the plant (Reviewed by Develey-Rivière and Galiana, 2007).
Resistance has been shown to be affected by transitions between developmental
stages such as Zea mays resistance to Puccinia sorghi which is dependent on the
expression of adult characteristics (Abedon and Tracy, 1996). It may also be affected
by the maturity of tissues or organs, such as the increased resistance to Venturia
inaequalis with increased leaf maturity in apple (Li and Xu, 2002), or tissue rank, such
as the increased resistance in rice from juvenile leaf ranks to adult ones (Koch and
27
Mew, 1991). Resistance has also been shown to increase over several stages once it
begins to have an effect, such as resistance to Xanthomonas oryzae pv. oryzae in rice,
which starts at the transition from the juvenile to adult stage, and increases to maximize
at the full adult state (Mazzola et al. 1994; Century et al. 1999).
1.6 R Gene Classes
Just as resistance genes have been shown to be involved in a variety of
pathogen recognition roles, there are several different classes of proteins which these
genes encode. This includes the nucleotide binding site – leucine-rich repeat (NBS-
LRR), extracellular leucine rich repeat (eLRR) containing proteins such as LRR-receptor
like kinases (RLKs), receptor like proteins (RLPs), polygalacturonase inhibiting proteins
(PGIPs), and receptor like cytoplasmic kinases (RLCKs). Many genes are also involved
in peripheral roles, such as downstream signalling (i.e. MAPKs) or physical prevention
of pathogenesis (i.e. callose production). Although there are multiple classes of genes
and resultant proteins involved in pathogen resistance pathways in plants, the most
commonly found, and most well studied group of resistance genes encode NBS-LRR
proteins (Mindrinos et al. 1994; Ori et al.1997; Wang et al. 1999; Meyers et al. 2003).
1.6.1 Nucleotide Binding Site-Leucine Rich Repeat Proteins
The basic NBS-LRR protein contains two main domains: the nucleotide binding
site domain, and the leucine rich repeat domain. These domains have different motifs,
and play different roles in the recognition and defense pathway. The NBS domain of R
proteins is involved in binding nucleotides for induction of downstream resistance
processes (McHale et al. 2006). The LRR region is involved in recognition of a
pathogen via protein-protein interaction (Jones and Jones, 1997).
28
1.6.1.1 NBS Domain
The NBS region of R proteins is made up of several conserved motifs, including
the P-loop, kinase-2, resistance nucleotide binding site (RNBS)-B, Gly-Leu-Pro-Leu
(GLPL) and MHDV subdomains (Meyers et al. 2002; Liu et al. 2007). These motifs are
important for anchoring and hydrolyzing ADP molecules, which is the beginning of the
signal transduction cascade for the resistance response (Tameling et al. 2002; McHale
et al. 2006; Mestre and Baulcombe, 2006). The NBS site is kept inactive by other
domains of the protein, or with host proteins, and is activated by the presence of a
specific pathogen effector molecule either by direct interaction or by conformational
changes in the host protein it is monitoring (Reviewed by Muthamilarasan and Prasad,
2013).
1.6.1.2 Role of Amino-Terminal Domain
In addition to the nucleotide binding region, an NBS-LRR protein may have other
domains on the N terminal end. These extra domains are either the coiled coil (CC) or
toll-interleukin receptor (TIR) motifs, and are the basis for two subfamilies of NBS-LRR
proteins having different sequences and downstream pathways they affect. Both the
CC and TIR domains are comprised of ~ 200 amino acids (Meyers et al. 2003; Bernoux
et al. 2011). Crystallography has shown the CC domain structure to be a rod-shaped
dimer of α-helices (Maekawa et al. 2011), and the TIR structure is comprised of a β-
sheet connected by α-helices (Chan et al. 2010; Bernoux et al. 2011). It has been
shown for both N terminal domains that self-association occurs, and is an important
component for initiation of downstream signalling and ultimately the induction of HR
(Moffett et al. 2002; Rairdan et al. 2008; Bernoux et al. 2011; Maekawa et al. 2011).
29
Bernoux et al. (2011) hypothesized that dimerization of the TIR region after effector
binding, might provide a target for binding proteins that would cause downstream
signalling, however, it is unclear whether this is a unique or more common action .
1.6.1.3 LRR Domain
The LRR region is involved in protein-protein interactions (Kobe and Kajava,
2001). The amino acid sequence is hyper-variable, yet maintains a basic consensus
sequence of LxxLxxLxLxxc/nxx, where L represents the location of leucine or other
allopathic amino acids, and x represents the location of any amino acid (Kobe and
Kajava, 2001; Kajava and Kobe, 2002; McHale et al. 2006). The leucine rich consensus
sequence forms a β-strand followed by a β-turn structure, and makes up the backbone
of the LRR domain (Kobe and Deisenhofer, 1993; Kobe and Kajava, 2001). The other
variable amino acids comprise the exposed region, and changes in these amino acids
may alter the specificity of the protein (Parniske et al. 1997; Botella et al. 1998; Hwang
et al. 2000; Krasileva et al. 2010) as well as the structure (for review see Kobe and
Kajava, 2001).
1.6.2 Extracellular LRR Proteins
Another class of genes that have been shown to be involved in pathogen
resistance is the extracellular leucine rich repeat protein encoding genes. There are
several classifications of these proteins based on their domains, whether they are
membrane spanning, and if they contain a cytoplasmic domain. Their unifying feature is
mainly the presence of an eLRR, as well as their localization to the cell membrane.
30
1.6.2.1 eLRR Domain
The extracellular leucine rich repeat domain is comprised of 20-29 repeats of the
leucine rich repeat motif found in cytoplasmic genes with a variation in the leucine rich
repeat motif consensus sequence (Zhang et al. 2013). The eLRR consensus sequence
is xxLxxLxxLxxLxLxxNxLt/sGxIP where x may be any amino acid and L represents
either leucine or other allopathic residues (Kobe and Kajava, 2001; Zhang et al. 2013).
Like the LRR motif of cytoplasmic proteins, the eLRR has been shown to be involved in
pathogen ligand binding, such as recognition of flg22 by the eLRR domain of the
receptor like kinase FLS2 (Chinchilla et al. 2006).
1.6.2.2 LRR Receptor-Like Kinases
RLKs are comprised of an extracellular leucine-rich repeat domain, a membrane
spanning domain, an intracellular serine/threonine kinase domain and a signal peptide
(Sun et al. 2004; Zipfel et al. 2006). Two variations of RLK domain content have also
been identified in various plants. The variants RLCK and RLP have also been shown to
be involved in disease resistance reactions (discussed below). While the eLRR domain
of RLKs have been shown to bind pathogen ligands as was discussed above, the
kinase domain is involved in the direct and indirect initiation of signalling for downstream
resistance responses by phosphorylation (Ellis et al. 2000; Lu et al. 2010; Zhang et al.
2013).
RLKs have been shown to be involved in resistance to fungal and bacterial
pathogens both by positive and negative regulation (Reviewed by Yang et al. 2012).
Some examples of isolated and characterized RLK pathogen resistance genes are
31
Xa26 and OsBISERK1 in rice (Sun et al. 2004; Song et al. 2008), EFR, FLS2 and BAK1
in Arabidopsis (Zipfel et al. 2006; Yang et al. 2012).
1.6.2.3 Receptor-Like Cytoplasmic Kinases
Receptor-like cytoplasmic kinases have similar domain content to RLKs, but are
lacking the eLRR domain. Although there is no LRR ligand-binding domain, RLCKs
have been implicated in signalling roles in disease resistance. For example, resistance
to bacterial pathogens was demonstrated by the BIK1 gene which encodes an RLCK
that mediates signalling post-recognition of flagellin by FLS2/BAK1 complex in
Arabidopsis (Lu et al. 2010). Interestingly, the BIK1 protein was first reported to be
involved in Arabidopsis resistance to fungal pathogens Botrytis cinerea and Alternaria
brassicicola, and decrease resistance to the bacterial pathogen Pseudomonas syringae
pv. tomato (Veronese et al. 2006). This indicates the existence of more diverse roles
for proteins involved in disease resistance signalling than those involved in pathogen
recognition.
1.6.2.4 Receptor-Like Proteins
RLPs have a similar structure to RLKs as they contain an eLRR and
transmembrane domain and lack only the cytoplasmic kinase domain (Wang et al.
2008b). Within these two major domains exist several smaller conserved domains
including a putative signal peptide, a cysteine-rich domain, the eLRR domain which
consists of two LRR sequences interrupted by a non-LRR region, a spacer, an acidic
domain, a single transmembrane domain and a short cytoplasmic region (Reviewed by
Kruijt et al. 2005). RLPs have been implicated in resistance to fungal pathogens such
as the tomato Cf-9 gene that confers resistance to Cladosporum fulvum (Jones et al.
32
1994) and LepR3 gene involved in resistance to Leptosphaeria maculans in Brassica
napus (Larkan et al. 2013), as well as bacterial pathogens such as AtRLP30, which has
been shown to be involved in non-host resistance in Arabidopsis to Pseudomonas
syringae pv. phaseolicola (Ellendorff et al. 2008; Wang et al. 2008b).
1.6.2.5 Polygalacturonase Inhibiting Proteins
Polygalacturonase inhibiting proteins (PGIPs) are extracellular proteins that are
involved in both the general PTI and specific ETI forms of pathogen resistance in a plant
(reviewed by Dangl and Jones, 2001; Nüremberger et al. 2004; Federici et al. 2006).
These proteins have been well studied for their role in inhibiting fungal pathogen
infection in many dicot and monocot plants (reviewed by De Lorenzo et al. 2001; Ferrari
et al. 2002; Federici et al. 2006), but have also been reported to be involved in
resistance to bacterial pathogens (Huang and Allen, 2000; Hwang et al. 2010). PGIPs
are also implicated in stress-induced and developmental roles, due to their inhibition of
the pectinase polygalacturonase (PG) (for review see Protsenko et al. 2008).
Pectinases are used by pathogenic microbes in the initial stages of infection to
degrade the cell wall either for nutrients, or to gain access to the cytoplasm (Collmer
and Keen, 1986; Alghisi and Favaron, 1995). PG in particular has been shown to be
the first protein secreted by pathogenic microorganisms during the initial stages of
penetration (Jones et al. 1972). PGIPs inhibit PG activity in two ways. The first method
of inhibition is by physically occupying the PG cleavage site on the homogalacturonan
molecules (Protsenko et al. 2008). The second method is by binding the PG enzyme
and regulating its action (Leckie et al. 1999; Manfredini et al. 2005). This leads to the
release of degraded plant cell wall oligogalacturide fragments in the apoplast (Cook et
33
al. 1999), which elicit further resistance reactions in surrounding unaffected cells (De
Lorenzo and Ferrari, 2002).
There are multiple plants from which PGIPs have been isolated, such as
common bean, soybean, Arabidopsis, tomato and pear (reviewed by De Lorenzo et al.
2001). These proteins have different triggers that induce their expression as well as
different specificities for both the pathogen and the range of PGs they employ
(Desiderio et al. 1997). For example, in P. vulgaris, four PGIPs have been identified:
PvPGIP1-4. PvPGIP1 is involved with resistance to Fusarium moniliforme via binding of
its PG, whereasPvPGIP2 is able to inhibit the of PGs secreted by both F. moniliforme
and Aspergillus niger, but has also been shown to inhibit Botrytis cinerea PG1 (Sicilia et
al. 2005).
1.7 R Gene Specificity Evolution
Resistance gene specificity for a particular pathogen is an important component
for the resistance reaction since loss of specificity in a given gene may cause a resistant
plant to become susceptible to the associated disease. New specificities may be
achieved through different means which have been observed in multiple plants for both
NBS-LRR and kinase genes (Meyers et al. 1998; Meyers et al. 2003; Kim et al. 2009;
Schmutz et al. 2010; Huard-Chauveau et al. 2013). Events that lead to new specificities
include inter-allelic recombination, unequal pairing and mispairing, gene duplication of
small and large DNA fragments and single genes or gene clusters, diversifying
selection, intergenic sequence diversion and rearrangements due to transposable
element activity (reviewed by Michelmore and Meyers, 1998; Meyers et al. 2005; Liu et
al. 2007; Joshi and Nayak, 2013).
34
These events cause shuffling and duplication of large and small chunks of DNA,
which cause changes in amino acid sequences of the resistance proteins, which are
seen primarily as high sequence variability and changes in the specificity area of the
LRR region (Michelmore and Meyers, 1998). This not only promotes the development
of increased, or new pathogen specificities, but also the occurrence of clusters of R
genes and pseudogenes. The genes in these clusters are typically related, but have
highly divergent sequences indicating duplication events and followed by divergence
caused by chromosomal rearrangements (Hulbert et al. 2001; David et al. 2009).
Selection of these changes can occur either through positive or balancing selection,
depending on the plant and the genes observed (Bakker et al. 2006; Chen et al. 2010;
Gos et al. 2012).
1.8 Disease Resistance Research Genomic Resources
1.8.1 Common Bean Genomics
Recently, the genomic sequence of an Andean line G18933, primarily used as a
parent of the principal CIAT (Centro Internacional de Agricultura Tropical, Cali
Columbia) mapping population was released by a group in the US (available at
www.phytozome.net, Schmutz et al. 2014). The sequencing of the G19833 BAC genetic
library was performed using the Roche 454 platform with additional information from
BAC and fosmid end sequences. Assembly was performed using the Arachne2 system
(Jaffe et al. 2003) in combination with genetic markers and the G. max genomic
sequence (Schmutz et al. 2010) as a reference. The released assembly is
approximately 521.1 Mb, with 27,197 genes which encode 31,638 transcripts, and
35
transposons accounting for 41% of the genome (www.phytozome.net, Schmutz et al.
2014).
Although the sequencing was performed on an Andean variety of common bean
and some rearrangements can be expected between it and Mesoamerican varieties, it
is still an excellent tool for characterization and comparison of gene organization,
structure and function between the gene pools. It also serves as a useful reference for
other P. vulgaris sequencing efforts. Current projects include the South American-
Spanish “PhaseIbeAm” consortium focused on sequencing the Mesoamerican variety
BAT93, as well as the Canadian “Applied Bean Genomics & Bioproducts” effort,
focused on sequencing CBB resistant varieties HR67 and OAC Rex, which will be
discussed below.
1.8.2 OAC Rex Genomic Resources
A binary bacterial artificial chromosome 2 (BiBAC2) genomic library has been
created for the OAC-Rex genome (Perry, 2010), providing a resource for genetic
analysis of CBB resistance in OAC-Rex. With the use of this library, the OAC Rex has
been sequenced using several sequencing methods. Initial sequencing was performed
on 16 BiBAC2 clones selected by markers surrounding the PV-ctt001 CBB disease
resistance marker using Roche 454 sequencing. The obtained sequence was then
assembled into 1,309 contigs based on homology to the G. max chromosome 19.
Further sequencing of the entire OAC Rex genome was performed using the Ilumina
(Illumina Inc, California) and PacBio (Pacific Biosciences Inc., California) platforms,
which provided a more complete assembly based on homology to the P. vulgaris variety
G19833 genome (Schmutz et al. 2014).
36
1.8.3 Other Plant Genomic Resources
Multiple other plant genomes have been sequenced, including A. thaliana, G.
max, Oryza sativa, and annotations of genes involved in plant-pathogen interactions are
available through the National Centre for Biotechnology Information (NCBI -
www.http://www.ncbi.nlm.nih.gov). These available gene sequences provide an
excellent resource for homologue comparison to locate genes of interest within the OAC
Rex genome. The collection of gene and protein sequences in the NCBI database, as
well as their related studies, also make it possible to determine putative gene function,
characteristics and protein structure, which can be further tested in the plant.
1.9 Hypothesis and Objectives
It was hypothesized that candidate CBB resistance genes could be identified in
the genomic sequence of OAC Rex genomic library clones selected from the PV-ctt001
region of Pv04 using homology to previously identified disease resistance genes with an
LRR domain. The first of four objectives relating to the exploration of this hypothesis
was to identify and characterize candidate common bacterial blight resistance genes
associated with disease resistance marker Pv-ctt001 on Pv04. The second objective
was to isolate the predicted candidate genes for future disease resistance testing in the
model plant Arabidopsis. The third objective was to develop a detached Arabidopsis leaf
tissue culture assay to be used in the testing of candidate genes in the model plant.
The last objective was to measure candidate gene expression in susceptible and
resistant varieties of common bean, to observe differences in gene expression.
37
Chapter 2: Identification and Characterization of Candidate Common Bacterial
Blight Resistance Genes
2.1 Abstract
Common bacterial blight (Xanthomonas axonopodis pv. phaseoli) is a serious
bacterial disease of common bean (Phaseolus vulgaris L.) which causes lesions on the
leaves, stems, pods and seeds of the plant. Since the disease reduces the quantity and
quality of seed and fresh pod harvests, efforts to breed for resistance have been
ongoing for several decades. To improve the understanding of the genetic mechanisms
underlying CBB resistant variety OAC Rex, resistance gene homologs were identified
within selected BiBAC2 clones from the OAC Rex genomic library. Characterization of
the gene homologs identified four candidate genes, as well as six genes in the
surrounding sequence that have properties associated with genes involved in disease
resistance. Identified genomic features include retrotransposons, a predicted ascorbate
oxidase, a callose/glucan synthase and a hypothetical gene. Genetic and protein
analyses of these genes are described.
38
2.2 Introduction
2.2.1 CBB in Common Bean
CBB is a major disease of common bean, caused by the bacterial pathogen Xap
and its fuscans variant Xff. Symptoms produced by the disease include the
development of lesions on the leaves, stems, pods and seeds of the plant (Vidaver
1993). The disease affects seed quality and can reduce yield by up to 45% (Saettler
1989; Gillard et al. 2009). There is little natural resistance found in wild or domesticated
common bean varieties. However, sources of resistance within the same genus have
been used to introduce improved CBB resistance into breeding populations; including
Phaseolus acutifolius (tepary bean) (Parker 1985) and Phaseolus coccineus (scarlet
runner bean) (Miklas et al. 1994).
The first CBB resistant variety of common bean, OAC Rex, was registered in
Canada in 2002. It was the result of a cross between HR20-728 and MBE7 (Michaels
et al. 2006), and resistance originated from an inter-specific cross with P. acutifolius
accession P1440795 (Parker 1985). Two major resistance QTLs were found in OAC
Rex, associated with PV-ctt001 and SU91, as well as two minor affect QTL, associated
with BNG71DraI and BNG21EcoRV (Tar’an et al. 2001; Perry et al. 2013). PV-ctt001 was
first reported in OAC Rex on linkage group Pv05 by Tar’an et al. (2001) and was
mapped 21.6 cM away from a major CBB gene locus, and accounted for 42.2% of the
phenotypic variation. Subsequently, a physical location for PV-ctt001 was identified on
chromosome 4 , through the creation of a genomic library for OAC Rex (Perry 2010;
Perry et al. 2013), which is in agreement with a previous study performed by Yu et al.
(2000a) in a different mapping population. The difference in the location of the marker
39
between reports was attributed to the location of the marker at the end of the linkage
group, which is difficult to map accurately in the absence of a physical map (Tar’an et al.
2001; Perry 2010).
2.2.2 OAC Rex Genomic Library
Resistance to CBB in P. vulgaris has been a main focus of bean improvement for
decades. However, the genes involved have yet to be discovered. To assist in CBB R
gene identification, the OAC Rex genomic library created by Perry (2010) was used to
select clones associated with the PV-ctt001 region of Pv04. Selection was performed
by Southern hybridization of library membranes, using primers for PV-ctt001, as well as
P. vulgaris variety G19833 library clone end sequences PV_GBa00015K06 5’,
PV_GBa000015K06 3’ and PV_GBa00100K10 3’ (Schuleter et al. 2008) as probes
(Table 2.1). Sixteen positive clones were confirmed to have either 1 or 2 of the probe
sequences by PCR (Table 2.2), and the locations of the probes, as well as clone end
sequences that were used to orient the sequences into three contigs (Figure 2.1).
These 16 clones were sequenced using 454 sequencing, yielding 433,233 reads which
were pooled and assembled into 1,550 contigs. The current work was designed to
identify candidate CBB resistance genes associated with the PV-ctt001 marker in the
contig sequences.
2.2.3 R Gene Classifications
One of the main classifications of pathogen R genes are the NBS-LRR protein
encoding genes (Jones and Dangl 2006; Padmanabhan et al. 2009). Two basic
components of NBS-LRR proteins are NBS domains, which bind and hydrolyze ADP for
downstream signalling (Tameling et al. 2002), and LRR domains, which are involved in
40
Table 2.2 PV-ctt001 associated OAC Rex genomic library clones. Presence (+) or absence (-) of markers is indicated for each Binary Bacterial Artificial Chromosome 2 (BiBAC2) library clone. (Adapted from Perry 2010)
Clone Marker
PV_GBa00015K06 5’ PV_GBa000015K06 PV_GBa00100K10 3’ PV-ctt001
Rex001A06 + + - +
Rex012B03 - + + -
Rex020F10 - + + +
Rex021F10 + - - +
Rex028A07 - - - +
Rex045C01 - - - +
Rex056D11 - + - -
Rex057D11 - + - +
Rex063G02 - + + -
Rex075F07 - + + -
Rex076C04 - - + -
Rex090F06 - + + -
Rex091D05 - + + -
Rex092G02 + - - -
Rex213E05 + - - +
Rex281F03 + - - -
Table 2.1. DNA sequences and annealing temperatures for primers used to identify of OAC Rex genomic library clones associated with the PV-ctt001 QTL region of Pv04 (Adapted from Perry 2010)
Primer Sequence (5’-3’) Annealing Temperature
PV-ctt001 Forward GAGGGTGTTTCACTATTGTCACTGC 48oC
PV-ctt001 Reverse TTCATGGATGGTGGAGGAACAG 48oC
PV_GBa00015K06 5’ Forward CACCTAGTACTTCTGCATATAAAG 50oC
PV_GBa00015K06 5’ Reverse TCTTGGTAATTGCCTATTTAGG 50oC
PV_GBa00015K06 3’ Forward GGATATGACCCTAATTGCC 50oC
PV_GBa00015K06 3’ Reverse TCCCTTCCCTTCTCTCAG 50oC
PV_GBa00100K10 3’ Forward GCCGGAGTATAATTCAACCAGC 48oC
PV_GBa00100K10 3’ Reverse ATTCAGACTTTCATGATGTGTG 48oC
41
protein-protein interactions and pathogen specificity (Jones and Jones 1997; Ellis et al.
1999; Dodds et al. 2001). Additional small motifs may also be present at the amino
terminal ends, including the CC or TIR motifs, which help mediate signalling and the
induction of HR (Meyers et al. 2002; Moffett et al. 2002; Rairdan et al. 2008; Bernoux et
al. 2011; Maekawa et al. 2011).
Another type of gene involved in plant pathogen resistance are the eLRR genes.
This includes RLKs, which contain an eLRR domain, a transmembrane domain and a
kinase domain (Sun et al. 2004; Zipfel et al. 2006), RLPs which contain an eLRR
domain, transmembrane domain and small cytoplasmic tail (Wang et al. 2008b), and
PGIP which is located in the apoplast and contains only an eLRR (Di Matteo et al. 2003;
Sakamoto et al. 2003). The secondary structure has been resolved by X-ray
crystallography for PGIP2, which was isolated in P. vulgaris (Di Matteo et al. 2003), and
may be used as a reference to model the structure of LRR domain containing proteins.
RLCKs are similar to RLKs, but do not contain an eLRR and are anchored to the cell
membrane and have a kinase domain (Veronese et al. 2006; Lu et al. 2010).
2.2.4 R Gene Identification in OAC Rex
Both NBS-LRR and the eLRR genes have been studied in many different
pathogen systems. However, they have yet to be linked to resistance to CBB in the
common bean. The aim of this research was to identify and characterize CGs in the
region of the Pv04 linkage group associated with the PV-ctt001 marker in the OAC Rex
genome. It was hypothesized that the gene associated with this CBB resistance QTL
encoded an LRR protein, since it is the most commonly reported pathogen R gene
domain. It was further hypothesized that the conserved sequence of LRR genes could
42
be used to identify candidate CBB R genes in OAC Rex that could be tested for their
ability to reduce the disease.
43
Figure 2.1 Alignment of selected OAC Rex genomic library clones around CBB resistance marker PV-ctt001. The ~75 kb region of BiBAC2 library clone 21 (Rex021F10; ~150 kb) that represents the likely location for contig1701 is highlighted in blue to indicate the region of focus for this chapter. (Adapted from Perry 2010; Perry et al. 2013).
44
2.3 Materials and Methods
2.3.1 R Gene Homology Identification in OAC Rex Library Clones
Contigs assembled from the sequence raw reads obtained from clones 1, 12, 20,
21, 28, 45, 56, 57, 63, 75, 76, 90, 91, 92, 213 and 281 (Figure 2.1) were analyzed for
homologous regions to known LRR genes (Table 2.3) in other plants using BLAST. The
query was run through the CLC Genomics Workbench, and comparisons were based
on a collection of plant LRR genes available at the National Centre for Biotechnology
Information (NCBI) website (www.ncbi.nlm.nih.gov). The collection included sequences
from A. thaliana, G. max, O. sativa, Populus trichocarpa and Z. mays, which were
deposited in the CLC Genomics Workbench for BLAST against the selected BiBAC
clone contig sequences (Table 2.3). When selecting which regions of LRR to explore
further, the size of contig and the size and number of homologous regions were taken
into account. Preference was given to large contigs containing multiple predicted gene
regions with E values (probability of obtaining the hit by chance) less than 1E-20.
2.3.2 Confirmation of Contig Sequences
Two contigs, contig1455 and contig1701, were analyzed for sequence continuity.
Raw reads from PacBio (Pacific Biosciences, CA) and Illumina sequencing systems
were assembled into a consensus sequence using each contig as a reference to
produce a consensus sequence. The consensus sequences were aligned to their
respective contig sequence (from Roche 454 sequencing). Scaffolds, contigs and raw
sequencing reads were also used to confirm the sequence assembly and associated
gene annotations of contig1701. The sequence for contig1701 from 35,528 – 53,077 bp
was determined to be an assembly error (results presented in section 2.4.1.2), and
45
Table 2.3 NCBI accession numbers for the NBS-LRR genes used to search for candidate common bacterial blight resistance genes.
Species of Origin NCBI Accession Number
Arabidopsis Thaliana NM_001123924.1
NM_001125847.1
NM_001161067.1
NM_102893.2
NM_112307.2
NM_114955.4
NM_118071.5
NM_123196.1
NM_124542.2
NM_128428.4
NM_180323.3
NM_180841.2
Glycine Max EU839671.1
EU888329.1
EU888330.1
EU888332.1
FJ014886.1
Oryza Sativa NM_001055547.2
NM_197391.1
Populus Trichocarpa XM_002301537.1
Zea Mays NM_001112339.1
46
analyses performed on the 1-35,527 bp section, only, are reported below. However, the
final consensus sequence was produced after the majority of analyses were performed
on the entire contig1701 sequence (1-53,077 bp). This includes the CG CBB3, which
was identified and characterized using the same procedures as the other CGs, and is
included in the results reported below. The sequence for contig1455 was aligned to the
~7 kb sequence surrounding CBB2 (25,469-32,210 bp) to determine the similarity of the
two sequences.
2.3.3 Gene Identification and Characterization
Genes were identified in contig1701 and contig1455 using Fgenesh
(www.softberry.com) to identify transcription start points, exons and poly A tails. The
coding sequences and the corresponding proteins were predicted for each identified
gene by Fgenesh. Confirmation of gene predictions were performed by identifying the
presence of promoter elements (TAT box or CAAT core) in the putative promoter
region, expected intron start (GT) and stop (AG) (Luehrsen et al. 1994), internal content
of plant introns (Lorković et al. 2000), and poly A tail sequences. Confirmed genes
which also had a corresponding resistance gene homology match hit were designated
CGs.
2.3.4 CG and Surrounding Sequence Genome Location
2.3.4.1 OAC Rex Genome Assembly Location
Sequences of the contigs as well as the individual genes were BLASTed against
the most current assembly and raw sequencing data from the OAC Rex genome. The
most current OAC Rex assembly was comprised of 11 pseudochromosomes, 8,532
scaffolds and 30,023 contigs using Illumina, and 1,550 contigs using Roche 454
47
sequencing data (Perry 2010). The most current raw sequencing data (March 2015)
was produced using the PacBio (Pacific Biosciences, CA) sequencing system, and
consisted of 992,295 total raw reads.
2.3.4.2 G19833 Genome Assembly Location
The coding sequences and full sequences for genes identified in contig1455 and
contig1701, as well as the contig sequences were BLASTed against the sequence
assembly reported by Schmutz et al. (2014) for P. vulgaris variety G19833, to determine
their locations within the common bean genome
(http://phytozome.jgi.doe.gov/pz/portal.html). An initial indication of putative gene type
and function was obtained when a OAC Rex gene matched to a previous gene
annotation or other features (i.e. EST, transcript, protein match, RNA expression). In
the case where multiple good (>E63) matches within the G19833 sequence assembly
were found, the first match, with the highest E-value, was used for further comparisons
and analyses.
2.3.4.2.1 Repetitive DNA Analysis
The presence of repetitive DNA elements (i.e. transposable elements) was
identified within the regions of the G19833 genome that matched to genes in selected
contigs using the Phytozome RepeatMasker feature. The OAC Rex contigs were
analyzed using LTR_Finder (Xu and Wang 2007) and LTRphyler
(http://tools.bat.infspire.org/ltrphyler/) to identify the presence of long terminal repeats
(LTRs) and LTR retrotransposon domains.
48
2.3.5 Characterization of Predicted Proteins
The protein sequences were predicted for genes which were associated with
annotations of the G19833 sequence assembly. The annotation types which were used
to select OAC Rex genes for further analysis included previously identified genes
(including hypothetical genes/proteins), locations where ESTs or transcripts matched to,
or where RNASeq data indicated expression was occurring. OAC Rex genes that
matched to locations which contained transposable elements were the only annotations
that were not included, except for CGs.
2.3.5.1 Domain and Secondary Structure Analysis
The protein sequences were analyzed for the presence of signal peptide using
SignalP 4.1 (Petersen et al. 2011), and transmembrane domain prediction using
TMHMM Server v. 2.0 (www.cbs.dtu.dk/services/TMHMM). To identify functional
domains, the protein sequences were analyzed using InterPro
(http://www.ebi.ac.uk/interpro/; Mitchell et al. 2014). The secondary structures for the
peptide sequences were modelled using Phyre2 (Kelley and Sternberg 2009). BLAST
searches at UniProt (www.uniprot.org), NCBI (http://blast.ncbi.nlm.nih.gov/Blast.cgi),
InterPro (http://www.ebi.ac.uk/interpro/; Mitchell et al. 2014) and PvGEA
(http://plantgrn.noble.org/PvGEA/blasttranscript.jsp; O’Rourke et al. 2014) were
performed for each of the proteins to confirm potential functions. Alignments of the
coding and peptide sequences for the genes with putative functions with a previously
predicted gene of the same type from G19833 or other species were performed to
identify whether key features were conserved.
49
2.3.5.2 CG-Specific Analysis
CG protein sequences were manually screened for leucines and other allopathic
amino acids to determine the locations of leucine rich repeat motifs. Leucine rich
repeats were identified using the consensus LRR motif LxxxLxLxLxxL. This motif was
designed based on the general consensus motif reported in literature (Tornero et al.
1996; Kajava and Kobe 2002; Di Matteo et al. 2003), but modified to fit the recurring
consensus in the predicted proteins encoded by the CGs. Manual analysis of the CG
protein sequences was also performed to identify NBS, CC and TIR motifs within the
sequence, using the motifs described by Meyers et al. (2003) for Arabidopsis TIR- and
CC- NBS-LRR genes. Alignment of CG protein sequences was performed using
ClustalW (http://www.genome.jp/tools-bin/clustalw), and the locations of LRR motifs
were indicated to show protein homology as well as the percent similarity between the
CG proteins. CG protein sequences were also aligned to PvPGIP-2 and Swiss-Model
(Arnold et al. 2006) was used to provide an additional secondary structure prediction for
CGs using PvPGIP-2 as a reference template.
2.3.6 Isolation of CGs
2.3.6.1 Amplification of CGs
Primers were designed for the identified CG regions from contig1701 (Table 2.3)
using CLC Genomics. Polymerase Chain Reaction (PCR) was performed using the
OAC Rex BiBAC library clone 21 DNA as the template with the following conditions.
Each PCR reaction consisted of 2.5 µl of 10x PCR buffer, 2.5 µl of 15 mM MgCl2, 1 µl of
10 mM dNTP mix, 1 µl of reverse primer, 1 µl of forward primer, 0.5 µl of JumpStart Taq
DNA Polymerase (Sigma-Alderich, St. Louis, MO, USA), 1 µl of DNA template and 14.5
50
µl of sterile distilled water for a total of 25 µl. The PCR parameters included an initial
denaturation cycle at 94oC for 1 minute, followed by 30 cycles of denaturation (94oC for
30 seconds), annealing (30 seconds at the temperature specific to the primers – see
Table 2.3), and extension (72oC for 3 minutes), this step was followed by 10 minutes of
final extension at 72oC, and held at 4oC. The PCR products were separated by
electrophoresis through a 1% agarose gel in 1x TBE buffer (108 g Tris, 55 g Boric Acid,
40 mL EDTA in 10 L of distilled water) stained with 2.5% ethidium bromide, and
visualized by exposure to UV light. To isolate DNA fragments of interest from the
agarose gel the region containing the band of interest was cut from the gel and
extracted using PureLink Quick Gel Extraction Kit (Invitrogen, CA).
2.3.6.2 Cloning of CGs
Isolated fragments were inserted into TOPO cloning vectors using a TOPO TA™
Cloning Kit (Invitrogen), and the ligations were then transformed into TOPO E. coli cells
using heat shock, according to manufacturer instructions. After overnight culture at
37oC on solid LB selective medium (1 µl ampicillin/mL LB), white colonies were selected
and cultured in liquid ampicillin selective medium (1µLampicillin/mL LB). PCR was
performed for cultures that grew in the selective liquid media to determine the size of
the ligated fragment, with the following conditions. Each PCR reaction consisted of 2.5
µl of 10x PCR buffer, 2.5 µl of 15 mM MgCl2, 1 µl of 10 mM dNTP mix, 1 µl of reverse
primer, 1 µl of forward primer, 0.5 µl of JumpStart Taq DNA Polymerase (Sigma-
Alderich, St. Louis, MO, USA), 1 µl of each positive culture as the DNA template and
14.5 µl of sterile distilled water for a total of 25 µl. The PCR parameters included an
initial denaturation cycle at 94oC for 1 minute, followed by 30 cycles of denaturation
51
(94oC for 30 seconds), annealing (30 seconds at the temperature specific to the primers
– see Table 2.3), and extension (72oC for 3 minutes), this step was followed by 10
minutes of final extension at 72oC, and held at 4oC. The PCR products were separated
by electrophoresis through a 1% agarose gel in 1x TBE buffer (108 g Tris, 55 g Boric
Acid, 40 mL EDTA in 10 L of distilled water) stained with 2.5% ethidium bromide, and
visualized by exposure to UV light.
For cultures containing an insert of the appropriate size, the plasmid was isolated
using PureLink Quick Plasmid Mini Prep kit (Invitrogen). For each isolated plasmid, 1
kb of the 5’ and 3’ ends of the ligated fragment was sequenced at the University of
Guelph Advanced Analysis Centre Genomics Facility (Guelph, ON, CA). The 1 kb
fragments were sequenced using M13 forward and reverse primers which correspond to
locations on the 5’ and 3’ ends of the cloning site, to confirm the correct sequence was
cloned. The end sequences were then compared to CG and contig sequences to
determine the locations the fragments that were isolated.
52
2.4 Results
2.4.1 Gene Identification in Select OAC Rex Contig Sequences
2.4.1.1 R Gene Homology Identification
Several contigs from OAC Rex BiBAC2 library clone 21 were identified as having
significant homology to previously reported NBS-LRRs (Figure 2.1). Contigs1701 and
1455 were selected for analysis. Contig1701 was selected for further analysis because
of its large size (~50 kb) and the presence of 3 NBS-LRR homologous regions in its
sequence. Contig1455 was added after the initial BLAST and selection of CGs,
although it was not originally analyzed. Interest in this contig arose from cloning and
sequencing work in later experiments (described below).
2.4.1.2 Contig Sequence Assembly Confirmation
2.4.1.2.1 Contig1701 Assembly Confirmation
When the contig1701 sequence was BLASTed against the current OAC Rex
assembly and raw sequence data, 2 scaffolds (scaffold1045 and scaffold296), 4 contigs
(contig9955, contig9956, contig4106 and contig 4107) and 3 PacBio raw reads (PBR2,
PBR4 and PBR11) matched the best (between 87-99% similarity) to 1-35,527 bp, with
some overlapping sequence (Figure 2.2). When the contig1701 sequence was
BLASTed to the OAC Rex pseudochromosomes there were no locations with high
similarity observed. Within the contig1701 sequence, the1-19,586bp section was 98%
similar to scaffold1045, and the 19,668-35,527 bp section was 97% similar to
scaffold296 (Figure 2.2). Contigs and raw reads matched within these two sections, but
not between, and therefore did not support the assembly of a continuous sequence for
contig1701 as illustrated in Figure 2.2. A section of scaffold1045 (5,968-26,642 bp)
53
matched to contig1701 at 1-19,626 bp, and corresponded with contig9955, contig9956,
and pbr2. The 1-5,967bp overhang region of scaffold1045 which was missing on the
contig1701 sequence corresponded to the same overhang region of contig9955. The
section of scaffold296 (113,508-130,206 bp) that matched to contig1701 at 20,885-
35,527 bp, corresponded with contig4107, contig4106, pbr4 and pbr11. The same
region of scaffold296 (113,508-130,206 bp) also had high similarity to the region
between 35,647-49,671 bp in the reverse compliment direction compared to the 20,885-
35,527 bp region. Alignment of the two regions (19,668-35,527 bp and 35,647-49,671
bp) within contig1701, which corresponded to scaffold296 (113,508-130,206 bp),
showed them to be 87% similar, with large stretches of identical sequence (>1kb)
interrupted by smaller stretches of no, or low similarity (<200 bp).
Since a single location could not be identified for the entirety of the contig1701
sequence within the OAC Rex sequence assembly, it was divided into four sections
based on homology to OAC Rex contig and scaffold matches (Figure 2.2). The first
section extended from 1-19.586 bp (contig1701-1), the second from 19,668-35,527 bp
(contig1701-2), the third from 35,647-49,671 bp (contig1701-3) and the fourth and final
section from 50,608-53,077 bp (contig1701-4).
The junctions between sections contig1701-1 and contig1701-2, and contig1701-
3 and contig1701-4 were confirmed on the basis of the similarity between the
contig1701 sequence and the consensus sequence produced when PacBio raw reads
were assembled using the contig1701 sequence as a reference. The contig1701
sequence and the assembly consensus sequence were 93% similar for the junction
between contig1701-1 and contig1701-2 sections, and were 97% similar for the junction
54
between contig1701-3 and contig1701-4 sections. No consensus assembly was
obtained for the junction between contig1701-2 and contig1701-3 sections. Therefore,
because the sequence from 35,527-53,077 bp was highly similar to the sequence from
1-35,527 bp, and the number of PacBio raw reads that matched the 35,527-53,077 bp
sequence was significantly lower (Figure 2.2), further analyses were performed only on
the genes predicted in the 1-35,527 bp sequence. However, characterization of CBB3
from the discarded region (39,732-42,310 bp), is reported below, and in Chapter 4,
since these analyses were performed on this gene previous to the confirmation of the
continuity of the contig1701 sequence assembly.
2.4.1.2.2 Contig1455 Assembly Confirmation
Comparison of contig1455 to the most recent assembly of the OAC Rex genome
identified high similarities to one scaffold, one contig and one raw sequence read (Table
2.7). The 1-6,365 bp region of contig1455 matched to scaffold296 (117,948-124,325)
which also corresponded to contig4106, and the 47-7,720 bp region matched to pbr11.
Alignment of contig1455 to the section within contig1701 (25,469-32,210 bp), which also
matched to contig4106 and pbr11, indicated 92% similarity, and the predicted genes
were present in similar arrangements in all three locations (Figure 2.2). This confirmed
the continuity of the contig1455 sequence assembly.
2.4.1.3 Contig1701 Gene Annotation
When FGeneSH was used to identify genes on contig1701, 16 genes were
identified within the whole sequence (1-53,077 bp) (Figure 2.2). Within the confirmed
sequence (1-35,527 bp), 10 genes were identified (Figure 2.2-2.3: Table 2.4). Promoter
elements were identified for all ten genes, but poly A tails could only be identified for
55
Figure 2.2 OAC Rex contig1701 sequence confirmation, with alignments between OAC Rex sequence elements and the contig1701 and contig1455 sequence assemblies. A) Frequency of OAC Rex PacBio raw read match locations within contig1701 when it was used as the reference for a sequence assembly. The number of reads mapping to the reference is indicated by the lefthand scale.B) Alignments between contig1701 and PacBio raw reads, Illumina sequencing assembled contigs and scaffolds, and contig1455. Contig1701 and contig 1455 are highlighted in blue. Sections within contig1701 where sequence integrity was in question are highlighted in green. Sequences with high homology to contig1701 (>85%) are indicated by solid lines. Sequences with low homology to contig1701 (<85%) are indicated by dashed lines. Arrows indicate genes with high homology between sequences. C) Summary of OAC Rex genome assembly elements, their percent similarity and location of similarity to contig1701 and contig1455.
C OAC Rex Sequence Element
Homologous Genes
Contig1701 Match Location
Similarity to Contig1701
Similarity to Contig1455
Contig9955 1(CBB1), 2, 3 1 – 9,980 98% - PBR2 3, 4, 5 7,300 – 16,189 87% - Contig9956 4, 5 9,756 – 19,586 98% - PBR4 6, 7 19,668 – 24,932 91% - Contig4107 7 23,030 – 25,424 99% - PBR11 7, 8(CBB2), 9, 10 24,947 – 34,161 88% 88% Contig4106 7,8(CBB2) 26,697 – 35,131 98% 98% Scaffold1045 1, 2, 3, 4, 5 1 – 19,626 98% - Scaffold296 6, 7, 8(CBB2), 9, 10 20,885 – 35,527 97% 98% Contig1455 8(CBB2), 9 25,469 – 32,210 92% -
A
B
2,100
0
1,000
56
genes 4-10 (Table 2.4). The predicted exon/intron splice points were confirmed for each
of the ten genes.
2.4.1.3.1 Contig1701 CGs
Three resistance gene homologous regions were identified on contig1701,
based on similarity to a reported resistance gene from O. sativa (NM_197391.1; Table
2.3). The first homologous region was 662 bp long, 57% similar to the matching contig
sequence (2E-20), and extended from the promoter region to the second coding region
of a predicted gene, which was designated candidate CBB resistance gene CBB1 (123-
2,274 bp) (Figure 2.5A; Table 2.4). CBB1 was 2,249 bp in size, with 3 exons consisting
of 804 bp of coding sequence (Figure 2.3; Table 2.4 and 6). The second homologous
region was 266 bp long, 65% similar to the matching contig sequence (3E-23), and
located between the first and second coding regions of a predicted gene, designated
CG CBB2 (27,481-31,229 bp) (Figure 2.5B; Table 2.4). CBB2 was 3,922 bp in size, with
4 exons comprising 1,452 bp of coding sequence (Figure 2.3; Table 2.4 and 6). The
third significant resistance gene homologous region was 488 bp long, 59% similar (2E-
24), and extended from the first coding region into the second coding region of a
predicted gene, designated candidate CBB resistance gene CBB3 (39,732-42,310 bp)
(Figure 2.5C; Table 2.4 and 2.6). CBB3 is 2,806 bp in size with 3 exons comprising
1,020 bp of coding sequence (Figure 2.3; Table 2.5).
2.4.1.4 Contig1455 Gene Annotation
FGeneSH identified three genes on contig1455 (Figure 2.4; Table 2.5).
Promoter elements were identified for all three genes, but poly A tails could only be
identified for genes 1-2, indicating they were likely not whole genes (Table 2.5).
57
Figure 2.3 Locations, coding sequences and potential functions of predicted genes on contig1701. Candidate genes CBB1, CBB2 and CBB3 are indicated in blue, yellow and red respectively. Genes with solid fills have promoter and poly A elements, and outlined genes are missing both the promoter elements and a poly A. A BLAST analysis against the G19833 genome sequence associated predicted genes with retroelement (red and candidate genes), L-ascorbate oxidase/multi-copper oxidase (pale green), and glucan-like synthase/callose synthase annotations.
58
Table 2.4 Locations within the contig1701 sequence assembly and genetic features of contig1701 gene annotations Gene Contig1701 Location TATA Box CAAT Core Coding Sequence Poly A
Gene 1 (CBB1) 123 – 2,274 2,294-2,299 2,367-2,371 CDS1 – 2,119-2,158 CDS2 – 1,578-1,888 CDS3 – 924-1,376
-
Gene 2 2,426 – 5,867 5,891-5,898 6,193-6,197 CDS1 – 3,965-4,145 CDS2 – 2,753-3,267
-
Gene 3 8,273 – 9,780 - - CDS1 – 9,633-9,731 CDS2 – 9,058-9,328 CDS3 – 8,700-8,871 CDS4 – 8,293-8,389
-
Gene 4 10,965 – 13,458 10,927-10,933 10,885-10,889 CDS1 – 11,550-11,601 CDS2 – 11,893-12,259 CDS3 – 13,062-13,290
13,459-13,503
Gene 5 14,960 – 20,200 20,228-20,234 - CDS1 – 18,739-18,990 CDS2 – 17,572-17,766 CDS3 – 16,676-16,780 CDS4 – 15,980-16,125 CDS5 – 15,500-15,705 CDS6 – 15,166-15,437
14,972-14,946
Gene 6 20,838 – 21,767 21,797-21,801 22,224-22,228 CDS1 – 21,334-21,504 20,839- 20817 Gene 7 22,461 – 25,632 25,458-25,465 - CDS1 – 25,013-25,027
CDS2 – 24,506-24,645 CDS3 – 23,626-23,712 CDS4 – 23,190-23,237 CDS5 – 22,617-22,833
22,524- 22,402
Gene 8 (CBB2) 27,481 – 31,229 27,447-27,452 27,308-27,312 CDS1 – 28,082-28,303 CDS2 – 28,426-28,945 CDS3 – 29,562-30,058 CDS4 – 30,891-31,103
31,164-31,196
Gene 9 31,668 – 32,062 32,090-32,095 - CDS1 – 31,679-31,966 31,668-31,678 Gene 10 32,417 – 34,101 34,128- 34,133 - CDS1 – 33,738-33,855
CDS2 – 32,506-32,741 32,413- 32,422
59
The predicted exon/intron splice points were confirmed for each of the three predicted
genes. CBB4 is 4,049 bp in size and includes 6 exons comprising a 1,428 bp coding
sequence (Figure 2.4-2.5D; Table 2.5-2.6).
2.4.2 OAC Rex Gene Locations within OAC Rex Genome Assembly
In attempting to confirm the sequence continuity of the contig1701 and
contig1455 (see section 2.4.1.2) sequences, no location within the most recent OAC
Rex pseudochromosomes could be found. Therefore, no conclusions about the
chromosome locations within OAC Rex could be made.
2.4.2.1 G19833 Location for Contig1701 Identified Genes
When the sequences of the ten genes identified in contig1701 were BLASTed to
the G19833 genome sequence, the genes matched to multiple locations (>100) within
and between chromosomes, with varying similarities and confidence values. The best
result for each CG resulted in genes 1-5 matched to chromosome 6 and genes 6-10
matching to chromosome 8 (Figure 2.5; Table 2.5). However, when BLAST was
performed using the entire contig1701 sequence a location within the G19833 sequence
assembly was not identified (data not shown).
Putative functions for the genes on contig1701 were assigned according to the
annotations present for the G19833 genes they were matched to. Gene 5 matched to
the same location within chromosome 6 as an annotation for a multi-copper oxidase/L-
ascorbate oxidase gene and for which expression was observed in multiple tissue
sources (Figure 2.3 and 2.6; Table 2.7). Gene 6 matched to the same location within
chromosome 8 as a hypothetical protein, for which expression was observed in the
nodules and roots (Figure 2.3 and 6; Table 2.7). Gene 7 matched to the same location
60
Figure 2.4 Location, coding sequence and potential function of predicted genes on contig1455 showing candidate gene CBB4 (bright green). Genes with solid fill have promoter and poly A elements, and outlined genes are missing both the promoter and poly A. A BLAST analysis against the G19833 genome sequence associated predicted genes with retroelement (red and candidate genes).
Table 2.5 Locations within the contig1455 sequence assembly and genetic features of contig 1455 gene annotations
Gene Contig 1455 Location TATA Box CAAT Core Coding Sequence Poly A Gene 1 282-706 283-290 - CDS1 – 412-549 688-706
Gene 2 (CBB4) 1,604-6,056 6,002-6,008 - CDS1 – 5,064-5402 CDS2 – 4,544-4,759 CDS3 – 4,135-4347 CDS4 – 3,908-4033 CDS5 – 2,997-3110 CDS6 – 2,491-2916
1,604-1,736
Gene 3 6,695-8,815 - 8051-8054 CDS1 – 7,619-7969 -
61
Figure 2.5 Candidate common bacterial blight (CBB) resistance genes. Gene organization for candidate genes CBB1 (A), CBB2 (B), CBB3 (C) and CBB4 (D). Promoters are indicated with black arrow boxes, coding regions are indicated by colored boxes, pathogen resistance gene homologies are indicated by the outline of a rectangle and the poly A tails are indicated with four black lines. The positions (bp) within contig1701 for CBB1, CBB2, and CBB3 and contig1455 for CBB4 are indicated.
Table 2.6 Summary of candidate common bacterial blight resistance gene characteristics. The sizes of the candidate genes, predicted coding sequences, protein sizes and the number of leucine rich repeats for each of the candidate genes CBB1, CBB2, CBB3 and CBB4 are indicated.
Candidate Gene
Total Gene Size (Base Pairs)
Coding Sequence Size (Base Pairs)
Protein Size (Amino Acids)
Number of LRRs
CBB1 2,249 804 267 8
CBB2 3,922 1,452 483 11
CBB3 2,806 1,020 339 10
CBB4 4,453 1,428 476 11
62
within chromosome 8 as an annotation for a β-glucan-like synthase/callose synthase for
which expression was not observed in the source tissues used in the RNA-seq study
performed by Schmutz et al. (2014) and reported in Phytozome (Figure 2.3 and 6; Table
2.7). The remaining genes, including CBB1-3, matched to regions within chromosomes
6 and 8 which were annotated as retrotransposons (Table 2.7). Some of the
retrotransposons had associated RNAseq data indicating expression, but no source
tissue locations were given (Table 2.7).
2.4.2.2 G19833 Location for Contig1455 Identified Genes
When the genes identified in contig1455 were BLASTed against the G19833 sequence,
they matched to multiple different locations within and between chromosomes. The
best results matched genes 1 and 2 on chromosome 8 and gene 3 on chromosome 6
(Figure 2.7; Table 2.8). Each of the three predicted genes matched to locations where
retrotransposons had been identified, but no other gene annotations were present.
Contig1455 predicted genes 2 and 3 were associated with locations where RNA seq
data indicated gene expression to be present. Two of the three predicted genes were
located in the same region as contig1701 predicted genes. CBB4 matched to the same
location as CBB2 and CBB3. Contig1455 gene 1 was matched to the same location as
contig1701 gene 10.
63
Figure 2.6 Sequence comparisons between OAC Rex contig1701 and syntenic regions in G19833. Contig1701 sections coloured by blue and purple blocks correspond to chromosome 6 (5.817-5.839 Mbp) and green and yellow coloured regions corresponded to chromosome 8 (49.680-49.698 Mbp) when compared (with BLAST) to the G19833 sequence on Phytozome. Predicted genes for G19833 sequences are indicated by grey arrows for genes matching to contig1701 genes and arrow outline for genes not matching contig1701 genes. Gene match locations are indicated with lines and white boxes.
64
Table 2.7 Predicted locations in G19833 and expression of annotated genes in OAC Rex contig1701. The positions in the G19833 assembly (Phytozome; Schmutz et al 2014) are indicated by chromosome number and location (bp) of contig1701 gene synteny, and associated gene(s) or element(s), which indicate a possible function.
Gene Number
G19833 Chromosome Location (bp) Similarity to G19833
Associated Genetic Feature G19833 Expression Details
Chromosome 6 Chromosome 8 Gene 1 (CBB1) 5,817,952 – 5,820,113 98% pvRetroSF205-2, pvRetroSF112-2,
pvRetroSF100-1
No expression
Gene 2 5,820,266 – 5,823,700 98% pvRetroSF100-1, pvRetroSF172-1 No expression
Gene 3 5,826,105 – 5,832,901 98% pvRetroSF318-1 No expression
Gene 4 5,825,866 – 5,833,506 97% pvRetroSF318-1 No expression
Gene 5 5,835,002 – 5,839,661 98% Multi-copper oxidase Expression in flowers, pods, leaves,
stem, nodules, roots
Gene 6 49,682,264 – 49,683,238 97% Unknown protein transcript Expression in nodules, roots
Gene 7 49,683,929 – 49,687,869 92% Glucan synthase No expression
Gene 8 (CBB2) 49,682,319 – 49,693,055 75% pvRetro12, pvRetroSF188-3 Expression
Gene 9 49,693,473 – 49,693,864 88% pvRetroSF188-3 Expression
Gene 10 49,694,477 – 49,699,799 69% pvRetro19 No expression
Gene 13 (CBB3) 49,688,390 – 49,692,057 95% pvRetro12, pvRetroSF188-3 Expression
65
Figure 2.7 Alignments of contig1455 and associated match locations within G19833. The locations where contig1455
gene annotations match within the G19833 assembly chromosomes are indicated with lines. Candidate gene CBB4 is
indicated by a green arrow, and other gene predictions within contig1455 are indicated with red arrows. The red coloured
block indicates similarity to chromosome 6 and the orange coloured block indicates similarity to chromosome 8 within the
G19833 assembly.
66
Table 2.8 Predicted gene locations on OAC Rex contig 1455 in bp with associated G19833 chromosome number, location (in bp), gene or element and possible function.
Gene Number
G19833 Chromosome Location
Similarity to G19833
Associated Genetic Feature
G19833 Expression
Details Chromosome 6 Chromosome 8 Gene 1 49,693,478 –
49,693,898
99% pvRetro19 No Expression
Gene 2
(CBB4)
49,688,126 –
49,691,770
98% pvRetroSF188-3
pvRetro12
Expression
Gene 3 2,980,777 –
2,981,831
95% pvRetro3 Expression
67
2.4.3 Contig1701 Gene and Protein Characterization
2.4.3.1 Characterization of CGs
2.4.3.1.1 CG Similarities
Alignments of the CG sequences showed that CBB3 had the highest similarity to
CBB2 and CBB4 (>90%), CBB2 was less similar to CBB4 (72%), and as a group CBB2,
CBB3, CBB4 (CBB2-4) had low similarity with CBB1 (<15%) (Table 2.9). When the
predicted coding sequences were aligned for CBB1-4 (Figure 2.8), the sequences were
less similar than the full gene sequences (Table 2.9). CBB1 was the least similar to
CBB2-4 (<11%), CBB3 had the highest similarity to CBB2 and CBB4 (>89%), and CBB2
was less similar to CBB4 (65%) (Figure 2.8; Table 2.9). The predicted protein
sequences for the CGs were 267, 483, 339 and 476 amino acids long for CBB1, CBB2,
CBB3 and CBB4, respectively (Table 2.6). Alignments between amino acid sequences
showed there to be low similarity between CBB1 and CBB2-4 (<17%), the highest
similarity was seen between CBB3 and CBB4 (84%) (Figure 2.9;Table 2.9). Large
stretches of conserved sequence could be seen in all three comparisons between
CBB2-CBB4, especially in the carboxyl end, with stretches of non-conserved, variable
amino acids at the amino-terminal end as well as roughly in the middle of the protein
sequence (Figure 2.8-9).
2.4.3.1.2 CG Domain Analysis
Domain analysis of CBB1-4 determined that there were no NBS or related motifs
present in any of the CG predicted proteins. In addition, no TIR or CC motifs could be
identified in their N terminal ends. Further analysis of the N terminal ends indicated that
no signal peptides for extracellular transport exist in the putative proteins, indicating a
68
low likelihood that the proteins function outside the cell. Also, no transmembrane
domains were present in the putative protein sequences. These results indicate that the
CG proteins likely function within the cell.
Although NBS motifs were absent in all four putative CG proteins, they all
contained high numbers of leucine and other allopathic amino acids, as well as an LDL
motif, with a consensus sequence of LDLLLD. The predicted amino acid sequences
contained 8, 11, 10, and 11 LRRs for CBB1 CBB2, CBB3 and CBB4, respectively
(Figure 2.9-10; Table6). These LRRs conformed to the consensus motif sequence
consisting of LxxxLxLxLxxL, (Figure 2.9) where L represents a leucine or allopathic
amino acid and x represents any amino acid. Some variability in the lengths of LRRs
and the spacings between Ls was observed.
2.4.3.1.3 Contig Sequence Retrotransposon Analysis
Different analyses for gene and protein features provided low confidence
evidence that CGs were retrotransposons. BLAST searches using contig1701 and
contig1455 predicted gene sequences against the G19833 genome sequence indicated
that many of the predicted genes on contig 1701 and all contig1455 genes were
retrotransposons (Figure 2.3-4; Table 2.4-5). However, when CGs were BLASTed
against the NCBI database, only the sequence for CBB1 (gene 1) matched to a
retrotransposon (NCBI accession FJ402925.1). NCBI BLAST performed using CG
protein sequences resulted in multiple matches to unknown/hypothetical proteins.
BLAST searches against the UniPro database indicated that all four CGs had low (30-
47%) similarity to retrotransposon proteins including Gag-pol poly protein, POL3-like
69
Table 2.9 Similarity between candidate common bacterial blight resistance genes. Percent similarity between candidate resistance genes was determined by aligning full gene sequences, coding sequences and protein sequences in ClustalW
Genes Compared Compared Gene Similarity
Full Gene Coding Sequence Protein Sequence CBB1 CBB2 14% 11% 17%
CBB3 15% 9% 11%
CBB4 14% 11% 13%
CBB2 CBB3 90% 89% 72%
CBB4 72% 65% 52%
CBB3 CBB4 93% 91% 84%
70
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 ATGGTAGGCAATGGTGCCTTCATACAATGCCAAGGCATATGTCCCTTGGTGGACATTTCT
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 CTTCAAACTTCTACATTCACCATTTCTTTTTACCTATTACCTATTGAAGGAGCAAATGTA
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 GTTTTGGGCATTGAATGTTTGCGCACTCTTGGGCCTACTCAGGCATATTTCTCTATACCT
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 AGCATTGCTTTCACCCACCAGAACCAACAAATCACCCTACAAGCTGCCTTTCCATCTACC
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 GCAACTTCAACCACCTACCACCAATTATGTCAATACCTATCCACCAATTCCATTGCATCC
CBB1 ------------------------------------------------------------
CBB2 -------------------------------------ATGGTAGTTGGCGCTTTTTGTGT
CBB3 -------------------------------------ATGGTACTTGGCACTTTTTGTGT
CBB4 ATTCACCTGCTTTCAATTGACAATAACCCTATTCCACCAGGTACTTGGCACTTTT-GTGT
CBB1 ------------------------------------------------------------
CBB2 TGACTACAGAGCCTTAAATGCAGCCACCATCCGTGATCGCTTCCCCATCCCTACCATCGA
CBB3 TGATTACAGAGCATTAAATGCAGCCACCATTCGTGATCACTTCCCCATTCCTACCATCGA
CBB4 TGATTACAGAGCATTAAATGCAGCCACCATTCGTGATCACTTCCCCATTCCTACCATCGA
CBB1 ------------------------------------------------------------
CBB2 TGAATTGCTCGATGAACTAGGCTCAACTACAGTTTTCACTAAGATTGATTTATACTCAGG
CBB3 TGAATTGCTCGATGAACTAGGCTCAACTACAATTTTCACTAAGATAGATTTACACTCAGG
CBB4 TGAATTGCTCGATGAACTAGGCTCAACTACAATTTTCACTAAGATAGATTTACACTCAGG
CBB1 ------------------------------------------------------------
CBB2 GTATCATCAAATTCGACTTATCCCTCAAGACACTCACAAATCAGCTTTTAGAACCATTGA
CBB3 TCCCAATTTGAAGGAACATATTGTGCACTTACAGATTATCTTAGAAGTTTTACACACTAA
CBB4 GTATGATTATATTCGACTCATCCCTCAGGAAACTCACAAATCAGCATTTAGAC-CATTGA
CBB1 ------------------------------------------------------------
CBB2 TGGACATTACGAATTTTTAGAACATATTGTGCACTTAAAGATTATCTTAGAAGTTTTACA
CBB3 AAAACATTTTGC-TAAGT------------------------------------------
CBB4 TGGACATTATGAATTTTT------------------------------------------
CBB1 -------------ATGGAAACCGCTTTTAAGACCAAATTTG--GTTATATGAGTGACTTC
CBB2 CACTAAAAAATTTTTTGCTAAGTTATCTAAGTGCAGTTTTGCCACTTCTCAAGTAAATTA
CBB3 -----------------------TATCTAAGTGCAGTTTTGCCACTTCTCAAGTTAGTTA
CBB4 -----------------------TATCTAAGTGCAGTTTTGCCACTTCTCAAGTTAGTTA
* **** ** **** * *** * **
71
CBB1 GTAGGGTT-TGTGGTATGTTCTAAAGGGGTGCATGTAGACAAAGAAAAGGTTGTAACAAT
CBB2 TTTGGGCCATATCATTTCGGCTAAAGGAGTAGCCCCTGATCCAGAAAAAGTTATTGCCAT
CBB3 TTTGGGTAATATCATTTTGGCTAAAGTAGTAGTCCTTGATCCAAAAAAAGTTATTGCCAT
CBB4 TTTGGGTAATATCATTTTGGCTAAAGTAGTAGTCCTTGATCCAAAAAAAGTTATTGCCAT
* *** * * * * ****** ** ** * **** *** * * **
CBB1 TCAACATTGGCCAACACCCACCAATGTTAATGAGGT-ACGAAGTTTTCATGGCCTTGCTA
CBB2 ACACAATTGGCCG-CAGCCACGTTCACTCACGGAATTACGTGGTTTTCTCAGCCTCACAG
CBB3 ACACAATTGGCCA-CATCCACGTTCACTCACGAAATTGCGTGGTTTCCTCAACCTCACAG
CBB4 ACACAATTGGCCA-CATCCACGTTCACTCACGAAATTGCGTGGTTTCCTCAACCTCACAG
** ******* ** **** * * * * ** **** * *** *
CBB1 GT--TTTTATAGGAGGTTTGTGCAAAACTTTAGTACTATTG-------------------
CBB2 GA--TTTTATAGAAAGTTTTTTTATCACTACGCCACTCTCGCCGCTCCTCTCACCGATTT
CBB3 GGATTTTTATAGAAAGTTTGTTTATCACTACACCACTCAAAA------------------
CBB4 GA--TTTTATAGAAAGTTTGTTTATCACTACACCACTCTCG-------------------
* ******** * **** * * *** ***
CBB1 ------------------------------------------------------------
CBB2 GTTGCATAATCAAAAATTTACATGGAGTGTCTCGACTCAGGAGGCCTTTACAGAATTAAA
CBB3 ----------------TTTACATGGAGTGTCTC---------------------------
CBB4 -------------------------------TC---------------------------
CBB1 -------------------------CCACACCTATAAA----------------TGCTAT
CBB2 ATTACAAATATCTCAAGTTCCTACACTACACCTACAGAATTTCTCCTTGCCTTTTGTTGT
CBB3 ------------------------GCTACACCTACAGAATTTCTCCCTACCATTTGTCGT
CBB4 ------------------------ACTCCTCTCACTGATTTTCTCCCTACCATTTGTCGT
* * * * * ** *
CBB1 AGTAA-AGAAGGATGTGGTATTCAAGTGGGGACAAGACCAAATTAAAG------CTTTTG
CBB2 GGAAACAGACGCGTCTGCAGTAGTCGTGGGGTCGTGCTCAGCCAAAAGGGGCACCCGCTA
CBB3 GGAGA-AGACGCATCTGCAGTAGCCGTGGGGTCGTGCTCAGCTAAAAGGGGCACCCGCTA
CBB4 GGAGA-AGACGCATCTGCAGTAGCCGTGGGGTCGTGCTCAGCTAAAAGGGGCACCCGCTA
* * *** * * ** * ****** * * ** **** * *
CBB1 AAACTTTAAAGGAAAAATTCCCATTTTTAGCTCTTCCTAACTTTAAAACATTTG------
CBB2 TCCTTCTTCAACAAGAAAATGTGTCCAAGGCTCCAAGCTTCATCAGTGTATGTCCGAGAG
CBB3 TCCTTCTTCAATAAGAAGATGTGTCCAAGGCTCCAAGCATCATCATT-------------
CBB4 TCCTTCTTCAATAAGAAGATGTGTCCAAGGCTCCAAGCATCATCATTCGAGATCCCCCAT
* * * ** ** * **** * * *
CBB1 --------AAATAGAATGTGATGCTTCCAACCCAAAGCACACAAAGGAACTTTATAATGA
CBB2 ATACGGACAAACAGAAGTCCTTAATCGAAGTTTGGAAGCCTACCTACAATGCTTTGTTGG
CBB3 ------------------------------------------------------------
CBB4 TTGTCAGTACATTCTGGA----AACACCTATTCAAGGCACAAGGCACAACACTAAAATTC
CBB1 TGACCTTGATTTTTCTC-------------TTATCTATCAAGAGTTTTCCAAAGGAGCAC
CBB2 TGATCACCCTCACACTTGGTTCCAATATCTCCATCTAGCGGAACTTTGGCACAATACGAC
CBB3 -------------------------------------GTATAACTTTGGCACAATACGAC
CBB4 ATTTCCACTTTACCATCTACAACAGA----CGGACAAACATAACTTTGGCACAATACGAC
* *** ** * * **
CBB1 A---CAAAGAATTTTTCATACATAATGGTTTTCT-TTTCAAAGGAAAAAGACTTTGTGTT
CBB2 ATATCATTCCGCCATTGGCACCTCACCGTTCCATGCTCTGTACGGAAGACAACCTCCAAC
CBB3 ATATCATTCTGCCATTGGCACC-CACCGTTCCATGCTCTGTACGGAAGACAACCTCCAAC
CBB4 ATATCATTCTGCCATTGGCACC-CACCGTTCCATGCTCTGTACGGAAGACAACCTCCAAC
* ** ** ** * *** * * * * ** * * *
72
CBB1 CCCCAAGGATCTTTAAGACAATCTCTTGTTAGGGAAGCACATGAGAGTCGGCTCGTGGGT
CBB2 CACCTTAGATCTGTTACACAGTCCACACTCAAGCACCACCATTGCAGAT--TTGTTGCAC
CBB3 CACCTTAGATTTGTTAGACAATCCACACTCAAGCACCACCATTGCAGAT--TTGTTGCAC
CBB4 CACCTTAGATTTGTTAGACAATCCACACTCAAGCACCACCATTGCAGAT--TTGTTGCAC
* ** *** * * * *** ** * * * * *** ** * **
CBB1 CACTTTAGGATAGCTAAAACTTTAGATACATTGCATGAGTATTTCTTTTGGCCACACATG
CBB2 CAACACACGCTGGTTCTCCACGCCCTCAAACAAACCCTTCGCCGAACACGTCAACGAATG
CBB3 CAACACACGCTGGTTCTCCACGCCCTTAAACTAAGCCTTCACCGGACACGTCAACGAATG
CBB4 CAACACACGCTGGTTCTCCACGCCCTTAAACTAAGCCTTCACCGGACACGTCAACGAATG
** * * * * * * * * * ** ***
CBB1 CGCAAATCTGTACATAGCTTCCGTGATAAATG-TATAGCATGTAGGAAGGCTAAATCTAA
CBB2 TGCGACCAGGCCAACCGCCACCGATCCGAACGCTCTTTTAACCCGGATGATTGGGTATGG
CBB3 TGCGACCAGGCCAATCGCCACCAATCCGAACGCTCTTTTAACTCGGATGATTGGGTGTGG
CBB4 TGCGACCAGGCCAATCGCCACCAATCCGAACGCTCTTTTAACTCGGATGATTGGGTGTGG
** * * * ** ** ** * * * * *** * * * *
CBB1 AGTACAACCCCATGGTTTTATATACCCTTCTTCCTATTCCAACAATGC-----ATTGGGT
CBB2 GTACGTCTTCAACCTTACCGCCAACAGTTGGTGGAACGTCGTCCATGTTCGAAGCTCGAC
CBB3 GGACGTCTTCAATCTTACTACCGACAGTTGATGGAGCGTCGTTTATGTTCGAAGCTCGAC
CBB4 GGACGTCTTCAATCTTACTACCGACAGTTGATGGAGCGTCGTTTATGTTCGAAGCTCGAC
* * * ** ** * * *** * *
CBB1 CGATATTTCTATGGATTTTATCTTAGGTCTTCCCA---AGACATCGAAGGGTGTGGATTC
CBB2 CCTCGTTACTCGGGTCCTTACCAAGTGCTCCGCCGCATCGGCGTTGTGGCCTACAAACTC
CBB3 CCTTGTTACTCGGGTCCTTACCAAGTGCTCCGCCGCATCGACGTTGTAGCCTACAAACTT
CBB4 CCTTGTTACTCGGGTCCTTACCAAGTGCTCCGCCGCATCGACGTTGTAGCCTACAAACTT
* ** ** ** *** * * ** * * * * * * * *
CBB1 TATATTTGTTGTAGTGGACCGATTTTCTAA------------------------------
CBB2 CGTTTACCAAGCACCTCACAAGTTCTCATGGCCTCTAGTGTGCGGTGCTTCGATGTTCTT
CBB3 CGTTTATCAAGCACCTCACAAATACACCCAGTATTCCATGTATCCCTCCTTCGTGCTTAC
CBB4 CGTTTATCAAGCACCTCACAAATACACCCAGTATTCCATGTATCCCTCCTT---------
* * * * ** * *
CBB1 ------------------------------------------------------------
CBB2 TCCCCTATTAGTCGAATGAGTGGCGGGCCACCAGGGGTGACGTGCAAAGTCACATCTGAC
CBB3 TAA---------------------------------------------------------
CBB4 ------------------------------------------------------------
CBB1 ------------------------------------------------------------
CBB2 GATTTCAAGTTAGCTTTTAAGTACAAGTTGCAGGAGTCGAGCCAGAGAAAAATTACCTAT
CBB3 ------------------------------------------------------------
CBB4 ------------------------------------------------------------
CBB1 ------------------------------------------------------
CBB2 CTGTACGCTGCGATGCCTGGTCTCAGCTATCATGGACATGCTCGTGCGGTCTAA
CBB3 ------------------------------------------------------
CBB4 ------------------------------------------------------
Figure 2.8 Alignment of candidate common bacterial blight resistance gene coding sequences. Candidate genes CBB1 (blue), CBB2 (yellow), CBB3 (red) and CBB4 (green) were aligned in ClustalW. Coding sequences are indicated with alternating coloured rectangles.
73
CBB1 ------------------------------------------------------------
CBB2 ------------------------------------------------------------
CBB3 ------------------------------------------------------------
CBB4 MVGNGAFIQCQGICPLVDISLQTSTFTISFYLLPIEGANVVLGIECLRTLGPTQAYFSIP
CBB1 ------------------------------------------------------------
CBB2 ----------------------------------------------------MVVGAFCV
CBB3 ----------------------------------------------------MVLGTFCV
CBB4 SIAFTHQNQQITLQAAFPSTATSTTYHQLCQYLSTNSIASIHLLSIDNNPIPPGTWHFCV
CBB1 --------------------------METAFKTKFGYMS---------------------
CBB2 DYRALNAATIRDRFPIPTIDELLDELGSTTVFTKIDLYSGYHQIRLIPQDTHKSAFRTID
CBB3 DYRALNAATIRDHFPIPTIDELLDELGSTTIFTKIDLHSGPNLKEHIVHLQIILEVL---
CBB4 DYRALNAATIRDHFPIPTIDELLDELGSTTIFTKIDLHSGYDYIRLIPQETHKSAFR---
.*:. **:. *
CBB1 --------------------------------------DFVGFVVCSKGVHVDKEKVVTI
CBB2 GHYEFLEHIVHLKIILEVLHTKKFFAKLSKCSFATSQVNYLGHIISAKGVAPDPEKVIAI
CBB3 -------------------HTKKHFAKLSKCSFATSQVSYLGNIILAKVVVLDPKKVIAI
CBB4 -------------------PLMDIMNFLSKCSFATSQVSYLGNIILAKVVVLDPKKVIAI
.::* :: :* * * :**::*
CBB1 QHWPTPTNVNEVRSFHGLASFYRRFVQNFSTIATPINAIVK-------------------
CBB2 HNWPQPRSLTELRGFLSLTGFYRKFFYHYATLAAPLTDLLHNQKFTWSVSTQEAFTELKL
CBB3 HNWPHPRSLTKLRGFLNLTGIFIESLFITTPLKIYMECLAT-------------------
CBB4 HNWPHPRSLTKLRGFLNLTGFYRKFVYHYT------TLVTP-------------------
::** * .:.::*.* .*:.:: . . : :
CBB1 ------------KDVVFKWGQDQIKAFETLKEKFPFLALPNFKTFEIECDASNP------
CBB2 QISQVPTLHLQNFSLPFVVETDASAVVVGSCSAKRGTRYPSSTRKCVQGSKLHQCMSERY
CBB3 ---------PTEFLPTICRGEDASAVAVGSCSAKRGTRYPSSIRRCVQGSKHHH------
CBB4 ---------LTDFLPTICRGEDASAVAVGSCSAKRGTRYPSSIRRCVQGSKHHHSRSPIC
: * . . *. :: . :
CBB1 ---------------------KHTKELYNDDLDFSLIYQEFSKGAHKEFFIHNGFLFKGK
CBB2 GQTEVLNRSLEAYLQCFVGDHPHTWFQYLHLAELWHNTTYHSAIGTSPFHALYGRQPPTT
CBB3 -------------------------------CITLAQYDISFCHWHPPFHALYGRQPPTT
CBB4 ---QYILETPIQGTRHNTKIHFHFTIYNRRTNITLAQYDISFCHWHPPFHALYGRQPPTT
*. * .
CBB1 RLCVPQGSLRQSLVREAHESRLVGHFRIAKTLDTLHEYFFWPHMRKSVHSFRDKCIACRK
CBB2 LDLLHSPHSSTTIADLLHQHTLVLHALKQTLRRTRQRMCDQANRHRSERSFNPDDWVWVR
CBB3 LDLLDNPHSSTTIADLLHQHTLVLHALKLSLHRTRQRMCDQANRHQSERSFNSDDWVWGR
CBB4 LDLLDNPHSSTTIADLLHQHTLVLHALKLSLHRTRQRMCDQANRHQSERSFNSDDWVWGR
: . ::. *: ** * . * :. .: ::* :**. . . :
CBB1 AKSKVQPHGFIYPSSYSN----------NALGRYFYGFYLRSSQDIEGCGFYICCSGPIF
CBB2 LQPYRQQLVERRPCSKLDPRYSGPYQVLRRIGVVAYKLRLPSTSQVLMASSVRCFDVLSP
CBB3 LQSYYRQLMERRLCSKLDPCYSGPYQVLRRIDVVAYKLRLSSTSQIHPVFHVSLLRAY--
CBB4 LQSYYRQLMERRLCSKLDPCYSGPYQVLRRIDVVAYKLRLSSTSQIHPVFHVSLL-----
:. : .* : . :. * : * *:.::
CBB1 -------------------------------------------------------
CBB2 ISRMSGGPPGVTCKVTSDDFKLAFKYKLQESSQRKITYLYAAMPGLSYHGHARAV
CBB3 -------------------------------------------------------
CBB4 -------------------------------------------------------
Figure 2.9 Alignment of candidate gene protein sequences. LRR regions highlighted for candidate genes CBB1 (blue) CBB2 (yellow), CBB3 (red) and CBB4 (green), LDL motif is indicated by a box.
74
A) CBB1
B) CBB2
C) CBB3
D) CBB4
[4]…
FK T K F G YM- SDF …[11]
VD K E - K V -V T -I …[8]
VN E - V R - SFHGL …[13]
I A T P I N - A IVK - …[17]
LK E KF P F - LA - L …[21]
YN DDL D FS L I - Y …[43] LV G HF R I A - KTL …[48]
LG R - Y F Y G FY- L …[20]
[15]…
I R D R F P I P TIDEL …[14]
LY S GY H - Q I R LI …[25]
ID G H Y E F - LEHI …[17]
FA T S - Q VNYLGHI …[38]
LR G - F - L S LTGF …[32]
F T E - L K L Q ISQV …[29]
LN R S LEAY - LQCF …[12]
LHQHTL - V - LHAL …[14]
YS G PY Q V - LR RI …[23]
VR C - F D V - LS PI …[28]
VTSDDF K L A F K-Y …[10]
[17]…
I R D H F P IP TI D E L …[20]
L K E H I - V HL - Q I …[10]
FATS QV S Y - L G N I …[27]
LR G F L N LTGI F - I …[4]
I T T P L K I - YMECL …[50]
L A Q - Y D I S F C H - …[32]
L H Q H- T LV L H A L …[29]
VW GRLQSY - Y R Q L
…[12]
YS G P Y Q V - L R R I …[14]
I H P - V - F HV S LL …[3]
[20]…
LQTSTF T I S F YL L …[59] LSTNS IAS IHL LS - I …[23] I RD H F P IPT IDE L …[14] LH S GY D Y - I R- L …[24] FATSQV S Y - L GNI …[27] LR G F L N LTGF - -Y …[9] LV T P L TDF - L P T I …[74] L A Q- Y D I S FCH - …[32] LHQHTL V LHAL K- L …[29] VWGR LQ SY - YRQL …[12] YS G P YQ V - LR R I …[24]
LxxxLxLxLxxL
Figure 2.10 LRR sequences of candidate genes A) CBB1, B) CBB2, C) CBB3 and D) CBB4 with LRR consensus motif indicated
75
reverse transcriptase, Gypsy/Ty-3 retro-element polyprotein, as well as many
uncharacterized proteins.
Domain analysis with InterPro was unable to identify protein domains within any
of the CG protein sequences. However, the program indicated the presence of protein
signatures for all four CGs other than CBB2, providing a suggested protein
type/function. For CBB1, reverse transcriptase, GAG/POL/ENV polyprotein and
DNA/RNA polymerase signatures were found. For CBB2, no protein signatures were
found. For CBB3, reverse transcriptase and DNA/RNA polymerase signatures were
found. Finally, for CBB4, reverse transcriptase and DNA/polymerase signatures were
identified.
LTR_finder was unable to identify long terminal repeats within either of the contig
sequences. However, LTRphyler identified multiple retrotransposon poly protein
domains associated with CGs. Within CBB1, both an integrase core domain (660-1028
bp) and a Gypsy reverse transcriptase domain (1,908-2,374 bp) were identified which
corresponded to the same region as CDS1 and CDS3, although they also associated
with intron sequence. Gypsy reverse transcriptase domains were identified in CBB2,
CBB3, and CBB4. For CBB2, the reverse transcriptase domain was located between
CDS1 and CDS2 (28,086-28,295 bp). For CBB3, the reverse transcriptase domain was
associated with the location of CDS2 and the adjacent intron (41,622-41,831 bp). For
CBB4, the reverse transcriptase domain corresponded to the location of CDS2 (4,572-
4,814).
76
Figure 2.11 Secondary structure models of predicted proteins for candidate CBB
resistance genes CBB1 (A), CBB2 (B), CBB3 (C) and CBB4 (D), using Phyre2 software
(Kelley and Sternberg 2009)
77
Table 2.10 Phyre2 secondary structure modelling (Kelley and Sternberg 2009) for candidate gene proteins CBB1, CBB2, CBB3 and CBB4
Candidate
Gene
Amino Acids
Modelled
Template Template Characteristic Similarity to
Template
Confidence
CBB1 14-127 D1mu2a2 Reverse transcriptase
DNA/RNA polymerase
12% 99.9%
146-262 C3I2uA_ Prototype foamy virus (pfv)2
integrase
22% 99.7%
CBB2 5-271 D1mu2a2 Reverse transcriptase
DNA/RNA polymerase
14% 100%
213-430 C3I2uA_ Prototype foamy virus (pfv)2
integrase
19% 99.9%
CBB3 5-173 D1mu2a2 Reverse transcriptase DNA/RNA
polymerase
18% 100%
193-338 C312uA_ Prototype foamy virus (pfv)2
integrase
15% 99.7%
CBB4 9-68 C3nr6A_ xenotropic murine leukemia virus-
related virus2 (xmrv) protease
21% 97.9%
75-279 D1mu2a2 Reverse transcriptase DNA/RNA
polymerase
15% 100%
218-476 C3I2uA_ Prototype foamy virus (pfv)2
integrase
12% 99.7%
78
2.4.3.1.4 CG Secondary Structure Prediction
Modeling of protein secondary structure using Phyre2 (Kelley and Sternberg
2009) resulted in models for each of the CG proteins (Figure 2.11). CGs CBB1-4 were
modelled with the same reverse transcriptase (D1mu2a2) and integrase (C312uA_)
proteins, and CBB4 had an additional section modelled with a protease protein
(C3nr6A_) (Table 2.11). The model for CBB2 was produced using two viral integrase
proteins (Table 2.11). The presence of the manually modelled LRR motifs were
unconfirmed by the secondary structure models produced for the CGs, except for the
small section of β-sheet structure in CBB4 (Figure 2.11).
2.4.3.2 Characterization of Genes with Putative Functions
2.4.3.2.1 Ascorbate Oxidase Gene Homologs
Gene 5 matched to a Multicopper oxidase/L-ascorbate oxidase gene at
5,835,002 – 5,839,661 bp on chromosome 6 (Figure 2.6; Table 2.7). When the full
gene sequence for gene 5 was BLASTed at NCBI, putative conserved Cupredoxin
superfamily domains, and L-ascorbate oxidase and multicopper oxidase multi-domains
were predicted (data not shown). When the amino acid sequence was BLASTed against
the PvGEA Atlas (O’Rourke et al. 2014), matches were identified in several
chromosomes to several L-ascorbate oxidase annotations, including the L-ascorbate
oxidase annotation gene 5 matched to within G19833 chromosome 6
(Phvul.006G011700). When the sequence was BLASTed to the G. max genome
(Schmutz et al. 2010) in Phytozome it identified homology to an ascorbate oxidase
annotation at 11,769,051 – 11,776,969 bp on chromosome 20 (Glyma.20G051900).
79
Table 2.11 Similarity between contig1701 genes of interest and identified homologues. Percent similarity between genes identified in P. vulgaris varieties OAC Rex contig1701 (gene 5), G19833 annotation Phvul.006G011700, G. max annotation Glyma.20G051900 was determined by aligning full gene sequences, coding sequences and protein sequences in ClustalW. Zucchini ascorbate oxidase protein sequence (1ASP_A; Messerschmidt et al. 1993) was also aligned to the protein sequences to indicate conservation of protein domains.
Genes Compared Similarity (%)
Full Gene Coding Sequence Protein Sequence
Gene 5 Phvul.006G011700 91 87 82
Glyma.20G051900 19 80 75
1ASP_A - - 58
Phvul.006G011700 Glyma.20G051900 17 89 90
1ASP_A - - 68
Glyma.20G051900 1ASP_A - - 69
Gene 7 G2 100 52 81
Glyma.08G361500 2 14 23
G2 Glyma.08G361500 2 41 46
Gene 6 Phvul.008G191100 97 8 5
80
Alignment of the three gene sequences (gene 5, Phvul.006G011700 and
Glyma.20G051900) showed high similarity between gene 5 and Phvul.006G011700
(91%), but the similarity was low between Glyma.20G051900 and the other two genes
(Table 2.11). When the coding sequences for the three genes were aligned, higher
similarities were observed, with similarity between the coding sequences >80% (Figure
2.12; Table 2.11). Alignments of the protein sequences for gene5, Phvul.006G011700,
Glyma.20G051900, and X-ray modelled Zucchini ascorbate oxidase (IASP_A), obtained
from NCBI indicated a number of regions with high similarities (Figure 2.13; Table 2.11).
When InterPro was used to identify domains within gene 5, Phvul.006G011700,
Glyma.20G051900 and 1ASP_A, multicopper oxidase type 1, 2 and 3 domains were
identified (Figure 2.13). The amino acid sequences of these domains were highly
conserved between the aligned genes. However, the domains indicated by InterPro in
gene 5 were less conserved (Figure 2.13). Phyre2 secondary structure modelling of
gene 5, Phvul.006G011700 and Glyma.20G051900 used the X-ray structure of the
Zucchini ascorbate osxidase 1ASP_A (Messerschmidt et al.1993) (Figure 2.14).
Secondary structure modelling of the putative ascorbate oxidase proteins resulted in
structures that consisted of three similar motifs (Figure 2.14).
2.4.3.2.2 β-Glucan Synthase-Like Homologs
Gene 7 matched to 49,683,929 – 49,687,869 bp in chromosome 8 of G19833,
which is associated with an EST, and multiple annotations for similarity to β-glucan
synthase-like or callose synthase genes from various other species. When the gene 7
sequence was BLASTed against NCBI, multiple matches to P. vulgaris hypothetical
proteins were
81
Gene 5 ------------------------------------------------------------
Phvul.006G011700 ATGGGGTTGAAAGCAGTTTTGGTTTGGTGC---ATATGGTTGGGGCTGATACAATATTCA
Glyma.20G051900 ATGGGTTTGAAAGCACTTTTTGTTTGGTGCATTATATGGTTAGGTTTAGCACATTTGTCC
Gene 5 ------------------------------------------------------------
Phvul.006G011700 GTTGGAGGAAGGGTGAGGCACTACAGGTTTGATGTGGAGTACATGATGAGAAAGCCAGAT
Glyma.20G051900 CTTGGAGGAAGAGTGAGGCACTACAAGTTTGATGTGGAGTACATGATCAGAAAGCCAGAT
Gene 5 ------------------------------------------------------------
Phvul.006G011700 TGTTTGGAACACGTTGTGATGGGAATCAATGGGCAGTTTCCAGGGCCAACTATTAGGGCT
Glyma.20G051900 TGCTTGGAACACGTTGTGATGGGAATCAACGGCCAGTTTCCAGGCCCAACTATTAGGGCT
Gene 5 ------------------------------------------------------------
Phvul.006G011700 GAAGTTGGTGACACTCTTCACATTGCTCTCACCAACAAGCTTTTCACTGAGGGAACTGTT
Glyma.20G051900 GAAGTTGGTGACATTCTTGACATTGCTCTCACCAACAAGCTTTTCACTGAGGGAACTGTT
Gene 5 ------------------------------------------------------------
Phvul.006G011700 ATTCACTGGCATGGAATCAGACAGGTTGGAACTCCTTGGGCAGATGGAACTGCTGCTATC
Glyma.20G051900 ATTCACTGGCATGGAATCAGACAGGTTGGAACTCCTTGGGCTGATGGAACTGCTGCCATC
Gene 5 ------------ATGTGTGTTGTAATGA---TTAATTGTAATTATATGGTGCA---GCCT
Phvul.006G011700 TCACAGTGTGCTATAAATCCAGGAGAAACTTTTCACTACAGGTTTATAGTTGACAGGCCT
Glyma.20G051900 TCACAGTGTGCTATAAACCCAGGAGAGGCTTTTCATTACAGGTTTACAGTTGACAGGCCT
** * * ** * * * * ** ** * ****
Gene 5 GGAACGTATTTCTACCATGGACACTATGGTATGCAAAGATCAGCAGGGTTGTATGGTTCA
Phvul.006G011700 GGAACATATTTCTACCATGGACACTATGGTATGCAAAGATCAGCAGGGTTGTATGGTTCA
Glyma.20G051900 GGTACATATTTCTATCATGGACACCATGGTATGCAAAGATCAGCTGGGTTGTATGGTTCA
** ** ******** ********* ******************* ***************
Gene 5 CTGATAGTAGATTTGCCAAAGGGACAAAACGAACCGTTTCACTATGATGATGAGTTCAAC
Phvul.006G011700 CTGATAGTAGATTTGCCAAAGGGACAAAACGAACCGTTTCACTATGATGATGAGTTCAAC
Glyma.20G051900 TTGATAGTAGATTTGCCAAAGGGACAAAACGAACCGTTTCATTACGATGGTGAATTCAAC
**************************************** ** **** *** ******
Gene 5 CTTCTTCTAAGTGATTTGTGGCACACCAGCTCACATGAACAAGAAGTTGGTCTCTCTTCC
Phvul.006G011700 CTTCTTCTAAGTGATTTGTGGCACACCAGCTCACATGAACAAGAAGTTGGTCTCTCTTCC
Glyma.20G051900 CTTCTTCTTAGTGATTTGTGGCACACCAGTTCACATGAACAGGAAGTTGGCCTCTCTTCC
******** ******************** *********** ******** *********
Gene 5 CTACCATTCAAATGGATTGGTGAACCTCAGAGTCTGTTGATCAATGGAAGGGGACAATTC
Phvul.006G011700 CTACCATTCAAATGGATTGGTGAACCTCAGAGTCTTTTGATCAATGGAAGGGGACAATTC
Glyma.20G051900 AAACCATTCAAATGGATTGGTGAACCTCAGACTCTACTCATCAATGGAAAAGGACAATTC
***************************** *** * ******* ** *********
Gene 5 AATTGTTCTCTGGCAGCTAAATTCATTAACACCACTTTACCCGAGTGCCAATTCAGAGGT
Phvul.006G011700 AATTGTTCTCTGGCAGCTAAATTCATTAACACCACTTTACCCGAGTGCCAATTCAGAGGT
Glyma.20G051900 AATTGTTCCCTTGCATCTAAATTCATCAACACAACCCTACCCCAATGCCAACTTAAAGGT
******** ** *** ********** ***** ** ***** * ****** * * ****
Gene 5 GGTGAAGAATGTGCACCTCAAATTCTTCATGTAGAGCCAAACAAGACCTACAGGATCAGA
Phvul.006G011700 GGTGAAGAATGTGCACCTCAAATTCTTCATGTAGAGCCAAACAAGACCTACAGGATCAGA
Glyma.20G051900 GGTGAAGAATGTGCCCCTCAGATTCTTCATGTGGAGCCAAACAAGACCTATAGAATCAGG
************** ***** *********** ***************** ** *****
82
Gene 5 ATTTCCAGCACCACTTCCTTGGCTTCACTCAACTTAGCCATTTCG---CTGAGATCTACC
Phvul.006G011700 ATTTCCAGCACCACTTCCTTGGCTTCACTCAACTTAGCCATTTCGAATCACAAACTTATT
Glyma.20G051900 ATTGCCAGCACCACTGCCCTAGCTTCACTCAACTTAGCCATTTCGAATCACAAACTTGTA
*** *********** ** * ************************ * * * *
Gene 5 TCTGT---AATTAATGGAGTTCA-ATACAATCTTTCTTTCTT-----------CTTCTTC
Phvul.006G011700 GTGGTGGAAGCTGATGGAAACTACGTTACACCATTTGTGGTTGATGATATGGATATTTAT
Glyma.20G051900 GTGGTGGAAGCTGATGGAAATTACGTTTCACCTTTTGCGGTTGATGATATTGACATCTAT
** * * ***** * * * * ** ** * *
Gene 5 TCTG---AATGTTACACAGT----------AGAGGC---------------AATTATTTG
Phvul.006G011700 TCTGGTGAAAGCTACTCAGTTCTCCTTCGCACAGATCAAGATCCAAAGAAAAACTATTGG
Glyma.20G051900 TCTGGGGAAAGTTATTCAGTGCTCCTTCGCACAGACCAAGATCCAAACAAAAATTATTGG
**** ** * ** **** * ** ** **** *
Gene 5 TTCTT--------------------------------------------CAAATAATGGA
Phvul.006G011700 CTTTCAATTGGAGTTAGAGGAAGAAA---ACCTAACACACCACAAGGTCTAACCATTCTA
Glyma.20G051900 CTATCAATCGGGGTGAGAGGAAGAAGGGCACCCAACACCCCACAAGGCCTAACCATTCTA
* * ** * * *
Gene 5 AATCACAAACTTATTGTGGTGGAAGCTGATGGAA-------ACTACGTTACAC---CATT
Phvul.006G011700 AACTACAAGACAATTTCTGCCTCAGTTTTTCCAACTTCTCCACCACCCCTCACACCCCTT
Glyma.20G051900 AACTATAAGCCCATTTCTGCCTCAATTTTCCCAATTTCTCCACCACCCATCACTCCCATT
** * ** *** * * * ** ** ** *** * **
Gene 5 TG---TGGTT----------------GATGATATGGATATTTATTCTGGTGAAAGCTACT
Phvul.006G011700 TGGAATGATTTTGAACGTAGCAAAGCATTCACCAAGAAAATCATTGCCAAGATGGGAACC
Glyma.20G051900 TGGAATGATTTTGAGCGCAGCAAAGCGTTCACCAAGAAAATCATTGCGAAAATGGGGACC
** ** ** * * ** * * *** * * **
Gene 5 C----------------------------AGTTCTCCTTCGCACAGATCAAGATC-----
Phvul.006G011700 CCACAACCTCCAAAACGTTCTGATCGTACAATTTTTCTCCTCAACACCCAAAACCGTGTT
Glyma.20G051900 CCACAACCTCCAAAACGCTCTGATCGTACAATTTTCCTCCTCAACACCCAAAATTTGCTT
* * ** * ** * ** *** *
Gene 5 ----------CAAAGAAAACTATTGGC---------TTTCAATTG--GACAACCCCTTAC
Phvul.006G011700 GCTGGATTCACAAAATGGGCTATTAACAATGTGTCCCTAACATTGCCAGCAACCCCTTAC
Glyma.20G051900 GATGGATTCACCAAATGGGCCATTAACAATGTGTCCCTAACATTGCCGCCAACCCCTTAC
* ** * *** * * **** ***********
Gene 5 TTGGGCTCCATCAAGTTCAAACTAA-CAATGCTTTTGATCAAACACCTCCACCTGTTACC
Phvul.006G011700 TTGGGCTCCATCAAGTTCAAACTAAACAATGCTTTTGATCAAACACCTCCACCTGTTACC
Glyma.20G051900 TTGGGTTCCATCAAATTCAAAATAAATAATGCCTTTGACAAAACTCCCCCACCAGTTACC
***** ******** ****** *** ***** ***** **** ** ***** ******
Gene 5 TTCCCTCAAGACTATGACATTTTCAACCCTCCTGTGAACCCTAATTCAACCATTGGCAAT
Phvul.006G011700 TTCCCTCAAGACTATGACATTTTCAACCCTCCTGTGAACCCTAATTCAACCATTGGCAAT
Glyma.20G051900 TTCCCACAAGATTATGACATCTTCAACCCTCCTGTGAACCCTAATGCATCTATTGGCAAT
***** ***** ******** ************************ ** * *********
Gene 5 GGGGTGTACAAGTTCAACCTTAACGAGGTTGTTGATGTGATATTGCAAAATGCAAATCAA
Phvul.006G011700 GGGGTGTACAAGTTCAACCTTAACGAGGTTGTTGATGTGATATTGCAAAATGCAAATCAA
Glyma.20G051900 GGGGTGTACATGTTCAACCTTAATGAAGTTGTTGATGTGATCTTGCAAAATGCAAACCAA
********** ************ ** ************** ************** ***
83
Gene 5 TTGAGTGGAAATGGTAGTGAGATTCACCCTTGGCACTTGCATGGACATGACTTTTGGGTT
Phvul.006G011700 TTGAGTGGAAATGGTAGTGAGATTCACCCTTGGCACTTGCATGGACATGACTTTTGGGTT
Glyma.20G051900 TTATCTGGGAGTGGTAGTGAGATTCACCCTTGGCACTTGCATGGACATGACTTTTGGGTT
** *** * *************************************************
Gene 5 TTGGGGTATGGAGAAGGCAAATTCAAACAAGGTGATGAGAAGAAATTCAACTTGACACAT
Phvul.006G011700 TTGGGGTATGGAGAAGGCAAATTCAAACAAGGTGATGAGAAGAAATTCAACTTGACACAT
Glyma.20G051900 TTGGGGTATGGAGAAGGGAAATTCAAACCAAGTGATGAGAAGAAATTCAATTTGACACAT
***************** ********** * ******************* *********
Gene 5 GCACCATTGAGGAACACAGCAGTGATATTTCCATATGGTTGGACTGCATTAAGGTTTAAG
Phvul.006G011700 GCACCATTGAGGAACACAGCAGTGATATTTCCATATGGTTGGACTGCATTAAGGTTTAAG
Glyma.20G051900 GCACCGTTGAGGAACACTGCTGTGATATTTCCATATGGTTGGACTGCTTTGAGGTTTAAG
***** *********** ** ************************** ** *********
Gene 5 GCAGATAATCCAGGAGTTTGGGCCTTCCATTGCCACATTGAACCACATTTGCACATGGGA
Phvul.006G011700 GCAGATAATCCAGGAGTTTGGGCCTTCCATTGCCACATTGAACCACATTTGCACATGGGA
Glyma.20G051900 GCTGATAACCCAGGAGTTTGGGCCTTCCATTGTCACATTGAACCCCATTTGCACATGGGA
** ***** *********************** *********** ***************
Gene 5 ATGGGTGTGATTTTTGCTGAGGGTGTCCACAAAGTTGGAAAAATTCCAAGGGAAGCACTA
Phvul.006G011700 ATGGGTGTGATTTTTGCTGAGGGTGTCCACAAAGTTGGAAAAATTCCAAGGGAAGCACTA
Glyma.20G051900 ATGGGTGTGATTTTTGCTGAGGGTGTTCACAAAGTTGGAAAAATCCCAAGAGATGCACTA
************************** ***************** ***** ** ******
Gene 5 AATTGTGGGCTTGTTGGGAAGAAGCTAGTAGAAAATGGACACTACTGA
Phvul.006G011700 AATTGTGGGCTTGTTGGGAAGAAACTAGTAGAAAATGGACACTACTGA
Glyma.20G051900 ACTTGTGGGCTTACTGGGAATAAGCTAGTAGGAAATAGACACTATTGA
* ********** ****** ** ******* **** ******* ***
Figure 2.12 Alignment and annotation of ascorbate oxidase coding sequences. Exons are indicated in alternating dark and light coloured boxes. Gene 5 is indicated in green, Gene 16 is indicated in purple, Phvul.006G011700 is indicated in red, and Glyma.20G051900 is indicated in blue.
84
Gene5 ------------------------------------------------------------
Phvul.006G011700 -MGLKAVLVWCIWLGLIQYSVGGRVRHYRFDVEYMMRKPDCLEHVVMGINGQFPGPTIRA
Glyma.20G051900 MGLKALFVWCIIWLGLAHLSLGGRVRHYKFDVEYMIRKPDCLEHVVMGINGQFPGPTIRA
1ASP_A ----------------------SQIRHYKWEVEYMFWAPNCNENIVMGINGQFPGPTIRA
Gene5 ----------------------------------------------MCVVMINCNYMVQP
Phvul.006G011700 EVGDTLHIALTNKLFTEGTVIHWHGIRQVGTPWADGTAAISQCAINPGETFHYRFIVDRP
Glyma.20G051900 EVGDILDIALTNKLFTEGTVIHWHGIRQVGTPWADGTAAISQCAINPGEAFHYRFTVDRP
1ASP_A NAGDSVVVELTNKLHTEGVVIHWHGILQRGTPWADGTASISQCAINPGETFFYNFTVDNP
.: : .*
Gene5 GTYFYHGHYGMQRSAGLYGSLIVDLPKGQNEPFHYDDEFNLLLSDLWHTSSHEQEVGLSS
Phvul.006G011700 GTYFYHGHYGMQRSAGLYGSLIVDLPKGQNEPFHYDDEFNLLLSDLWHTSSHEQEVGLSS
Glyma.20G051900 GTYFYHGHHGMQRSAGLYGSLIVDLPKGQNEPFHYDGEFNLLLSDLWHTSSHEQEVGLSS
1ASP_A GTFFYHGHLGMQRSAGLYGSLIVDPPQGKKEPFHYDGEINLLLSDWWHQSIHKQEVGLSS
**:***** *************** *:*::******.*:****** ** * *:*******
Gene5 LPFKWIGEPQSLLINGRGQFNCSLAAKFINTTLPECQFRGGEECAPQILHVEPNKTYRIR
Phvul.006G011700 LPFKWIGEPQSLLINGRGQFNCSLAAKFINTTLPECQFRGGEECAPQILHVEPNKTYRIR
Glyma.20G051900 KPFKWIGEPQTLLINGKGQFNCSLASKFINTTLPQCQLKGGEECAPQILHVEPNKTYRIR
1ASP_A KPIRWIGEPQTILLNGRGQFDCSIAAKYDSN-LEPCKLKGSESCAPYIFHVSPKKTYRIR
*::******::*:* .: : .. * *:::*.*.*** *:**.*:******
Gene5 ISSTTSLASLNLAISLRSTSVINGVQYNLSFFFFSECYTVEAIICSSNNGNHKLIVVEAD
Phvul.006G011700 ISSTTSLASLNLAISN-----------------------------------HKLIVVEAD
Glyma.20G051900 IASTTALASLNLAISN-----------------------------------HKLIVVEAD
1ASP_A IASTTALAALNFAIGN-----------------------------------HKLIVVEAD
*:***:**:**:**. *:*:*****
Gene5 GNYVTPFVVDDMDIYSGESYSVLLRTDQDPKKTIGFQLDN--------------------
Phvul.006G011700 GNYVTPFVVDDMDIYSGESYSVLLRTDQDPKKNYWLSIGVRGRKPN-TPQGLTILNYKTI
Glyma.20G051900 GNYVSPFAVDDIDIYSGESYSVLLRTDQDPNKNYWLSIGVRGRRAPNTPQGLTILNYKPI
1ASP_A GNYVQPFYTSDIDIYSGESYSVLITTDQNPSENYWVSVGTRARHPN-TPPGLTLLNYLPN
**** ** ..*:***********: ***:*.:. ..:.
Type III
Type I
85
Gene5 ------------------------------------------------------------
Phvul.006G011700 SASVFPTSPPPLTPLWNDFERSKAFTKKIIAKMGTPQPPKRSDRTIFLLNTQNRVAGFTK
Glyma.20G051900 SASIFPISPPPITPIWNDFERSKAFTKKIIAKMGTPQPPKRSDRTIFLLNTQNLLDGFTK
1ASP_A SVSKLPTSPPPQTPAWDDFDRSKNFTYRITAAMGSPKPPVKFNRRIFLLNTQNVINGYVK
Gene5 -------------PLLGLHQVQTNNAFDQTPPPVTFPQDYDIFNPPVNPNSTIGNGVYKF
Phvul.006G011700 WAINNVSLTLPATPYLGSIKFKLNNAFDQTPPPVTFPQDYDIFNPPVNPNSTIGNGVYKF
Glyma.20G051900 WAINNVSLTLPPTPYLGSIKFKINNAFDKTPPPVTFPQDYDIFNPPVNPNASIGNGVYMF
1ASP_A WAINDVSLALPPTPYLGAMKYNLLHAFDQNPPPEVFPEDYDIDTPPTNEKTRIGNGVYQF
* ** : : :***:.*** .**:**** .**.* :: ****** *
Gene5 NLNEVVDVILQNANQLSGNG----------------------------------------
Phvul.006G011700 NLNEVVDVILQNANQLSGNGSEIHPWHLHGHDFWVLGYGEGKFKQGDEKKFNLTHAPLRN
Glyma.20G051900 NLNEVVDVILQNANQLSGSGSEIHPWHLHGHDFWVLGYGEGKFKPSDEKKFNLTHAPLRN
1ASP_A KIGEVVDVILQNANMMKENLSETHPWHLHGHDFWVLGYGDGKFSAEEESSLNLKNPPLRN
::.*********** :. .
Gene5 -TVIFPYGWTALRFKADNPGVWAFHCHIEPHLHMGMGVIFAEGVHKVGKIPREALNCGLV
Phvul.006G011700 TAVIFPYGWTALRFKADNPGVWAFHCHIEPHLHMGMGVIFAEGVHKVGKIPREALNCGLV
Glyma.20G051900 TAVIFPYGWTALRFKADNPGVWAFHCHIEPHLHMGMGVIFAEGVHKVGKIPRDALTCGLT
1ASP_A TVVIFPYGWTAIRFVADNPGVWAFHCHIEPHLHMGMGVVFAEGVEKVGRIPTKALACGGT
.*********:** ***********************:*****.***:** .** ** .
Gene5 GKKLVENGHY-
Phvul.006G011700 GKKLVENGHY-
Glyma.20G051900 GNKLVGNRHY-
1ASP_A AKSLINNPKNP
.:.*: * :
Figure 2.13 Alignment and annotation of L-ascorbate oxidase amino acid sequences. Amino acid sequences were aligned for predicted ascobate oxidase like genes from P. vulgaris varieties OAC Rex (gene 5) and G19833 (Phvul.006G011700; Schmutz et al. 2014), a predicted G. max ascorbate oxidase gene (Glyma.20G051900; Schmutz et al. 2010) and an ascorbate oxidase protein from Cucurbita pepo var. melopepo, for which the secondary structured was resolved by X-ray (1ASP_A; Messerschmidt et al. 1992). Type 1, 2 and 3 multicopper oxidase domains are outlined and labelled. A copper binding site is highlighted in grey.
Type II
86
Figure 2.14 Secondary structure models of OAC Rex and G19833 L-ascorbate oxidase protreins. Secondary structure models for Gene 5 (A) from contig1701, G19833 gene annotation Phvul.006G011700 (B) and G. max gene annotation Glyma.20G051900 (C) were produced using Phyre2 (Kelley and Sternberg 2009). Ascorbate oxidase type I, II and III domains are indicated by circles. All models were created using the X-ray structure of a zucchini ascorbate oxidase (D) as a template (Messerschmidt et al. 1993)
87
Table 2.12 Phyre2 secondary structure modelling (Kelley and Sternberg 2009) for gene 5, Phvul.006G011700, Glyma.20G051900 and 1ASP_A
Gene Name Amino Acids
Modelled
Template Template
Characteristic
Similarity to
Template
Confidence
Gene 5 11-408 C1asqB_ Ascorbate oxidase
(Messerschmidt et al. 1993)
57% 100%
Phvul.006G011700 22-570 C1asqB_ Ascorbate oxidase
(Messerschmidt et al. 1993)
69% 100%
Glyma.20G051900 23-572 C1asqB_ Ascorbate oxidase
(Messerschmidt et al. 1993)
70% 100%
1ASP_A 1-552 C1asqB_ Ascorbate oxidase
(Messerschmidt et al. 1993)
100% 100%
88
identified, as well as to callose synthase 3-like predictions from other species, including
Medicago truncatula (data not shown). BLAST against the pvGEA EST database
identified several β-glucan synthase-like gene matches on several chromosomes,
including chromosome 8 (data not shown). However, none of these matches
corresponded to 49,683,929 – 49,687,869 bp location in chromosome 8.
Since there was no transcript or gene annotation within G19833 where gene 7
matched, a ~12 kb sequence (49,679,901 – 49,691,730 bp on chromosome 8) was
selected surrounding the match location and FGeneSH analysis identified 4 genes.
One gene (G2) corresponded to the gene 7 match location within the G19833 sequence
(49683929 – 49687948 bp; Figure 2.6). Gene 7 and G2 gene sequences were then
BLASTed against the G. max genome sequence in Phytozome (Schmutz et al. 2010),
which identified homology to gene annotation Glyma.08GG361500 on chromosome 8
(47,300,299 – 47,324,252 bp).
Alignment of gene 7, G2 and Glyma08G361500 DNA sequences showed high
similarity between gene 7 and G2, but low similarity to Glyma08G361500 (Table 2.12).
Alignment of the coding sequences indicated low similarity between all three genes
(Table 2.11). When the protein sequences were aligned, the highest similarity to
Glyma08G361500 was seen for both genes, however, they were still <50% similar
(Appendix 1; Table 2.11).
When the protein sequences were BLASTed at InterPro, callose synthase family
related signatures were identified in G2 and Glyma08G361500. G2 also contained
three transmembrane domains which corresponded to the location of similar domains in
Glyma08G361500 (Appendix 1). Glyma08G361500 was classified as a callose
89
Figure 2.15 Secondary structure model for predicted β glucan synthase-like genes. Phyre 2 (Kelley and Sernberg 2009) secondary structure models were created for P. vulgaris gene 7 (A) from OAC Rex contig1701, and G2 (B) from G19833, and G. max gene annotation Glyma.08G361500 (C).
Table 2.13 Phyre2 secondary structure modelling (Kelley and Sternberg 2009) for gene 7, G2, and Glyma.08G361500
Gene Name Amino Acids
Modelled
Template Template
Characteristic
Similarity to
Template
Confidence
Gene 7 36-98 D1h2vc3 Alpha-alpha superhelix 17% 52.3%
G2 105-225 C4gmjE_ RNA binding protein 17% 54.4%
Glyma.08G361500 66-449 C4hg6A_ Cellulose synthase
subunit a
14% 96.8%
90
synthase based on the whole peptide sequence, and as a glycosyl transferase family 48
(glucan synthase) member based on amino acids 1,059-1,815. Domains identified in
Glyma08G361500 included a vacuolar protein sorting-associated protein Vta1/callose
synthase N-terminal domain (amino acids 45-175), a 1,3-β-glucan synthase subunit
FKS1-like domain (amino acids 321-436), two large and one small cytoplasmic domains
and two transmembrane domains (Appendix 1). No family or domain signatures were
predicted for gene 7 (Appendix 1).
When Phyre2 was used to predict protein secondary structure for gene 7, G2 and
Glyma08G361500, there was very low similarity to previously resolved proteins (Figure
2.15; Table 2.13). Secondary structure modelling for gene 7 and G2 produced low
confidence (<55%) models for small sections of the protein sequences (Figure 2.15A-B;
Table 2.12). Glyma.08G361500 was modelled using a cellulose synthase subunit a,
and was a 96.8%confident model, with 14% similarity to the model template (c4hg6A_)
(Figure 2.15C; Table 2.13).
2.4.3.2.3 Hypothetical Gene Annotations
Gene 6 matched to a hypothetical protein annotation at 49,682,264 – 49,683,238 bp on
chromosome 8 (Figure 2.5-6; Table 2.6). The matched region in G19833 was
associated with RNA seq data obtained from the nodules and roots, EST and transcript
information related to the hypothetical gene annotation Phvul.008G191100.1. The
coding sequence predicted in FGeneSH for gene 6 corresponded to a region beside this
annotation, but still corresponded to low level RNA seq expression data (49,682,789 –
49,682,959 bp). Neither the coding sequence associated with Phvul.008G191100.1,
91
nor the coding sequence of gene 6 had high similarity to known protein domains when
BLASTed against the NCBI database.
When the gene 6 and Phvul.008G191100 DNA sequences were BLASTed against the
G. max sequence in Phytozome (Schmutz et al. 2010), no homologs were found.
Alignment of the DNA sequences for gene 6 and Phvul.008G191100.1 indicated that
gene 6 was 97% similar to Phvul.008G191100 (Table 2.11). However, alignment of
coding and protein sequences indicated low similarity (8% and 5% respectively)
between gene 6 and Phvul.008G191100 (Appendix 2; Table 2.11) .
Analysis with InterPro identified no protein family or domain signatures within the
protein sequences. Phyre2 modelling (Appendix 3) produced a low confidence (15.2%)
model that had low similarity (33%) to an iron regulated transcription activator (c4ImgD)
for gene 5 (Appendix 4). The model produced for Phvul.008G191100 also had low
confidence (32%) (Appendix 4).
2.4.4 Isolation and Amplification of CGs
Amplification of bands from genomic OAC Rex DNA using the designed primers
for CGs CBB2 and CBB3 (Table 2.14) produced multiple bands ranging from 850 –
5,000 bp (Figure 2.16 A-D). To reduce amplification of non-specific bands, BiBAC2
library clone 21 DNA was used as the template, which produced a single band when the
same primers were used (Figure 2.16 E-H). The PCR fragments were cloned into E. coli
(Figure 2.17) and 1 kb of the forward (5’) and reverse (3’) ends of the clones were
sequenced. BLAST of the 5’ and 3’ end sequences for all sequenced clones matched
to contig1455 at 2,236-3,401 bp and 4,526-5,566 bp respectively (Figure 2.18). When
the contig1455 sequence surrounding the 5’ and 3’ 1 kb sequences was analyzed using
92
FGeneSH and GeneMark, three genes were predicted (discussed in section 2.4.1.3.2;
Figure 2.4; Table 2.5). Additionally, when contig1455 was compared to the region
surrounding CGs CBB2 and CBB3, it was 99% similar to each region, with small (<100
bp) sequence differences, so the gene was included as a CG (CBB4).
93
Table 2.14 Primers used to amplify candidate genes CBB2 and CBB3 from OAC Rex DNA Primer Forward Sequence Reverse Sequence Band Size
(bp)
CBBS2-14 CATTTCTCACCACCTCCACCTACCC GAAAGTCTTTGAGGGTTAGGTGAGTGG 2,553
CBBS2-15 CACCTATAAATACCTAATGCCCAAACACC GTGAGTGAAGTAGTGCAGAGTTAGGTGG 2,808
CBBS3-8 CACCTATAAATACCTAATGCCCAAACACC GTTGGAGAATTGTTAGGTGTGAGGTTTTG 2,391
CBBS3-9 CACATTTCTCACCACCACCTCCACCTAC GTTTTGGGGTTGGGAATCTTTGGTG 2,204
Figure 2.16 Candidate gene PCR amplification from OAC Rex genomic DNA and BiBAC2 library DNA sources. Amplification of candidate genes from OAC Rex genomic DNA exhibited non-specific binding A) CBBS3-8, B) CBBS3-9, C) CBBS2-14, and D) CBBS2-15. Amplification of candidate genes from OAC Rex BiBAC2 library clone 021 E) CBB3-8, F) CBB3-9, G) CBB2-14, and H) CBB2-15 produced single bands. No bands were produced when water was used as a negative control (NC)
94
Figure 2.17 Common bacterial blight resistance candidate gene clones. Amplification of ~3.5 kb band using candidate gene primers for CBBS3-8 (A), CBBS3-9 (B), CBBS2-14 (C), CBBS2-15 from Escherichia coli clones. E. coli clones contained DNA amplified from OAC Rex BiBAC2 clone 021 using primers CBBS3-8 and CBBS3-9 designed for candidate gene CBB3, and CBBS2-14 and CBBS2-15 designed for candidate gene CBB2.
Figure 2.18 Location of clone sequence match within contig1455. Sequence of 1kb flanking ends of CBB candidate gene Escherichia coli clones matched to CBB4 5’ and 3’ ends when BLAST search was performed. The 1 kb sequences matched to 2,236-3,401 bp and 4,526-5,566 bp within the contig1455 sequence, and are indicated with a blue box.
95
2.5 Discussion
2.5.1 CG Characteristics
2.5.1.1 R Gene Characteristics of CGs
Several characteristics that are exhibited by CBB resistance CGs CBB1, CBB2,
CBB3 and CBB4 have previously been reported in literature. The organization of
multiple CGs and genes with potential disease resistance functions on contig1701
(Figure 2.2B and 2.3; Table 2.4, Table 2.7) are typical of resistance gene family clusters
(Michelmore and Meyers 1998; Graham et al. 2002; Meyers et al. 2003; Ameline-
Torregrosa et al. 2008). This clustering was accompanied by high similarity between
two of the CGs on contig1701 (CBB2 and CBB3) and the single CG identified on
contig1455 (CBB4) (Figure 2.2B). High similarity between resistance genes has been
frequently reported, especially in gene families where genes are present in close
proximity (Anderson et al. 1997; Meyers et al. 2003; Song et al. 2003). Both
characteristics are thought to be the result of frequent recombination events, which
result in high variability in the pathogen-interaction region (LRR) and may change
pathogen recognition capabilities (Anderson et al. 1997; Meyers et al. 1998; Song et al.
2003; Leister, 2004; Bakker et al. 2006).
Another important feature of the CGs is the presence of LRR domains, which are
found in many resistance related protein classes such as NBS-LRR, eLRR, RLKs and
RLPs (Meyers et al. 2003; Wang et. al. 2008b). Although it was not reflected in the
secondary structure model (Figure 2.11), LRR motifs were identified in the protein
sequence for each of the CG proteins (Figure 2.10). In addition, CBB2-4 contained an
96
LDL motif, but didn’t contain end motifs similar to those described for CC-NBS-LRR and
TIR-NBS-LRR proteins in Arabidopsis (Meyers et al. 2003).
Although there are similarities between the CBB2, CBB3 and CBB4 gene
sequences (Table 2.9), they were sufficiently variable to encode proteins which were
even more variable (Figure 2.9). Both the overall protein sizes and the numbers of LRR
motifs identified within the sequences varied (Figure 2.10; Table 2.6), resulting in
similarities between proteins as low as 11%, in the case of CBB1 and CBB2 (Table 2.9).
However, an overall consensus sequence (LxxxLxLxLxxL) was still identified, that was
applicable to all four predicted CG proteins (Figure 2.10). The finding that the motif is
not an exact match to LRR motifs reported previously (LxxLxLxxL), is consistent with
reports of high variability in LRR motif organization in NBS-LRR genes, within and
between species (Kajava 1998; Monosi et al. 2004; Zhou et al. 2004b)
2.5.1.2 Unique/Unusual Characteristics of CGs
Although the characteristics discussed above provide evidence to support the
hypothesis that they play a role in disease resistance, there are some differences which
indicate otherwise. When the protein sequences were analyzed both manually and via
predictive programs, NBS, CC, TIR, kinase, transmembrane and eLRR motifs were not
identified, and no signal peptide was indicated for any of the CGs. The sizes of the
loops between LRR motifs were more variable than expected when compared to the
LRR domains of NBS-LRRs and PGIPs (Di Matteo et al. 2003; Meyer et al. 2003).
Additionally, the secondary structure predicted for the CGs failed to support the manual
prediction of LRR domains (Figure 2.11). It was expected that the secondary structure
of the CGs would resemble the resolved secondary structures for eLRR protein PGIP,
97
and receptor like kinase RPK2 (Di Matteo et al. 2003; Song et al. 2014). These proteins
exhibit LRRs that align to form a stacked backbone, with the inter-LRR sequence
forming loops. Since there are few plant pathogen-resistance LRR proteins modelled, it
might be assumed that the failure to model CBB1-4 protein sequences into the
expected LRR secondary structure model is due to the lack of a good reference
structure for the proteins analysed with the modelling program. However, when a PGIP
was used as the model template, the expected secondary structure model still could not
be obtained. This evidence indicates that the CBB1-4 may not be LRR proteins, and
originate from another classification of protein.
2.5.1.3 Retrotransposon Characteristics of CGs
Retrotransposons are characterized by the ability to make copies of themselves
using RNA as the transposition medium, reverse transcribe and re-insert into the
genome (Wicker et al. 2007). BLAST search and secondary modelling of the CG
proteins identified low similarities to viral integrases, reverse transcriptase and
DNA/RNA polymerase proteins and GAG/POL/ENV polyproteins (see section 2.4.3.1.3;
Table 2.11). These are all proteins found in various types of retrotransposons, although
the similarity to the templates was low (Table 2.11), with percent similarity reaching no
higher than 22% for an 116 amino acid sequence for CBB4. This is likely to be an
indication of the lack of information about the secondary structure of plant
retrotransposon polyproteins.
When the CGs and other predicted genes from the area surrounding the CGs
were BLASTed against the G19833 sequence, many of the genes matched to areas
within the G19833 genome that were marked as retrotransposons (Figure 2.3; Table
98
2.7). In several cases, including for CBB2 and CBB3, there was also RNASeq data
associated with the retrotransposons, indicating that they were active (Table 2.7).
Retrotransposons have been shown to integrate preferentially into genic regions (Miyao
et al. 2003; Le et al. 2007). It is therefore not surprising that multiple gene predictions
associated with retrotransposons were present in a contig1701. Since the contig was
selected based on its presumed association with disease resistance marker PV-ctt001,
the presence of multiple possible resistance-related genes and retrotransposons
indicate the likelihood that part of a multigene family is represented in the sequence.
Retrotransposons have previously been shown to be involved in disease
resistance by interacting with resistance genes. When transposable elements
transpose into the location of a resistance gene, they may disrupt gene function which
might lead to reduced or abolished resistance (Song et al. 1997; Hernández-Pinzón et
al. 2009). Gene 7 may be an example of this, since it matched to the site of a putative
callose synthase gene on Chromosome 8 in the G19833 sequence assembly, but was
shown to be similar to only a portion of the large gene expressed in G. max (Figure 2.6,
2.15 and 2.16; Table 2.7 and 2.12). Studies have also shown that transposable
elements transpose in front of or between two genes and cause a chimeric protein to be
formed (Kashkush et al. 2003; Frost et al. 2004). Transposition can also change
promoter function and epigenetic controls (Hayashi et al. 2009; McDowell and Meyers
2013; Tsuchiya and Eulgem 2013). Considering that transposable elements were
reported to comprise 45% of the G19833 sequence (Schmutz et al. 2014), the likelihood
of an interaction between transposable elements and resistance genes is high, and is
an area to expand research into pathogen resistance.
99
2.5.2 Additional CGs on Contig1701
Since the predicted CGs CBB1-4 may be retrotransposons, the characterization
of three other genes within contig1701, which have potential disease resistance roles,
were explored. The genes were classified as ascorbate oxidase (gene 5), callose
synthase (gene 7) and hypothetical gene (gene 6) (see section 2.4.3.2; Appendices 1-4;
Figure 2.3 and 2.12-2.15; Table 2.7 and 2.11). Only gene 5, which matched an
ascorbate oxidase gene in G19833 chromosome 6, was likely to be a functional gene
based on the gene and protein analyses performed (see section 2.4.3.2).
The other two potential genes (callose synthase, hypothetical) either were not
very similar in sequence or secondary structure to previously identified genes of their
classification (Appendix 1-4; Figure 2.15; Table 2.11 and 2.13), or they were similar to
other uncharacterized genes and so were uninformative (Appendices 2-4). Gene 6 and
gene 7 may be fragments of genes that were produced by recombination events that
are often associated with the evolution of resistance genes (Michelmore and Meyers
1998; Meyers et al. 2005; Liu et al. 2007; Joshi and Nayak 2013). The association
between multiple predicted genes within the contig1701 with retro-element annotations
within the G19833 (Figure 2.3 and 2.5; Table 2.7) sequence suggests that transposable
element activity caused gene fragmentation in this stretch of the bean genome.
2.5.2.1 Ascorbate Oxidases and Disease Resistance
Ascorbate oxidases (AOs) are cell wall bound proteins which, are members of
the multi-copper oxidase family and are involved in binding and oxidizing ascorbic acid
(AA) in the apoplast (Messerschmidt et al. 1989). AA is involved primarily in providing
protection against reactive oxygen species (ROS) which are involved in the modulation
100
of stress (Smirnoff 2000) and defense responses (Pastori et al. 2003; Pavet et al. 2005)
have been shown to have a role in stress and pathogen resistance in various plant
species (Pavet et al. 2005; Pignocchi et al. 2006; Sanmartin et al. 2007; Fotopoulos et
al. 2008).
The presence of a predicted ascorbate oxidase gene within contig1701 is
suggestive of a potential role in resistance to CBB. The involvement of AA in protection
against ROS indicates that gene 5, as an AO, would regulate PCD associated with cell
death (Pavet et al. 2005), which is not a characteristic of the CBB resistance reaction.
However, the truncated domain predictions for gene 5 (Figure 2.13) may cause
incomplete binding and oxidation to occur, which has the potential to affect the
accumulation of ROS and the resultant hypersensitive response. Since this gene was
characterized at the bioinformatics level only, further studies would show more
definitively whether gene 5 is a functional ascorbate oxidase.
2.5.3 CG Location within Bean Genome
When the genes identified in the contig1701 sequence assembly were BLASTed
against the G19833 sequence, there were high numbers of significant matches (> e -63)
to many chromosomes for most of the predicted genes. The best matches (Figure 2.6;
Table 2.7) were to chromosomes 6 (5,817,952 – 5,839,661 bp) and 8 (49,682,264 –
49,698,171 bp). Since the contig1701 sequence was produced from BiBAC clones that
were selected based on the presence of disease resistance marker PV-ctt001, it was
expected that the contig and the genes predicted on it would match best to the area
surrounding its location (517,577-517,741 bp) on chromosome 4 (Tar’an et al. 2001;
Perry 2010; Perry et al. 2013). This is also the location of a large cluster of NBS-LRR
101
genes at the end of chromosome 4, which is associated with a variety of resistance-
related genes (Geffroy et al. 2009; Schmutz et al. 2014)
An explanation for this discrepancy is that the contig1701 sequence was
assembled using sequence data which originates from both Chromosome 6 and 8, and
assembled into one continuous sequence by human or program error. However, the
junction between the section that matched to chromosome 6 (contig1701-1) and the
section that matched to chromosome 8 (contig1701-2) was confirmed by PacBio reads.
Additionally, the creation of a new reference assembly which had read coverage of 8-
2,037 per 1 kb, indicating that it is likely that the sequence is continuous for the 1-35 kkb
length of contig1701 (see section 2.4.1.2.1; Figure 2.2A). The presence of the PV-
ctt001 marker within the BiBAC2 library clone from which CG CBB4 was isolated
(Rex021F10; Figure 2.1, 2.16 and 2.17) indicates that the contig1701 sequence is from
chromosome 4. This suggests the possibility that sequence rearrangement has
relocated sections of chromosomes 6 and 8 to chromosome 4 in the process of
integrating P. acutifolius DNA into the common bean genome. Considering the
apparent presence of retrotransposons in both the contig1455 and contig1701
sequence assemblies discussed above, this is likely to have been facilitated by
transposable element action, however, further studies are required for confirmation.
The difficulty in identifying a location for the full contig1701 sequence within the
OAC Rex genome assembly is that it is located within a region that has yet to be
completely assembled. Perry et al. (2013) compared the location of the PV-ctt001
marker and its surrounding area within OAC Rex with the G19833 sequence (Schmutz
et al. 2014). Although there was high conservation in the genomic region between
102
varieties, there was a 12 bp sequence difference between PV-ctt001 in OAC Rex, and
the corresponding location in G19833. There was also a large section (~200 kb) of the
G19833 sequence which did not match any of the assembled contigs within the OAC
Rex assembly. Since CBB resistance in OAC Rex resulted from an interspecific cross
between P. vulgaris and P. acutifolius (Parker 1985; Scott and Michaels 1992; Michaels
et al. 2006), it is possible that the area in question has higher amounts of the P.
acutifolius DNA, which is not present in the G19833 genome. However, the genomic
comparisons performed by Perry et al. (2013) indicated that differences between OAC
Rex and G19833 sequences were limited to single genes or up to 3 genes, as opposed
to a large stretch of highly different sequence.
The matching patterns observed by Perry et al. (2013) are similar to what was observed
in the current study for the comparison between section contig1701-1 and the the
G19833 sequence. The genes found in contig1701-1 (genes 1-5) matched to a segment
of G19833 chromosome 6 that contained all 5 genes in the same orientations.
However, an additional gene was predicted in the G19833 sequence between
contig1701 genes 3 and 4 (Figure 2.6). In contrast, there were multiple differences in
the number and size of genes identified in section contig1701-2 compared to those
identified in the associated region within the G19833 sequence assembly (genes 6-10).
This may be a reflection of the presence of multiple retrotransposon like elements in this
sequence, whith gene predictions identifying multiple sections of transposable element
polyproteins.
103
2.5.3.1 CBB Resistance Markers and CG G19833 Genome Location
Two CBB resistance QTLs, SU91 and UBC420, have previously been reported
on chromosomes 6 and 8 (Pedraza et al. 1997; Yu et al. 2000b; Vandemark et al. 2008;
Shi et. al 2011). The QTLs associated with these markers have also been shown to
have epistatic effects which lead to increased disease resistance when both markers
are present (Shi et al. 2011; Durham et al. 2013). SU91 was located initially to
chromosome 8 by linkage mapping (Pedraza et al. 1997). Subsequently, genome
sequence analysis by Perry et al. (2013) physically located the marker sequence to a
contig within the current OAC Rex sequence. Although the marker itself was absent
from the G19833 sequence assembly, the sequence surrounding SU91 in the OAC Rex
contig matched to the segment between 58,994,870-59,444,870 bp in chromosome 8
of G19833. UBC420 was located to chromosome 6 by linkage mapping in various
populations (Yu et al. 2000b; Vandemark et al. 2008; Durham et al. 2013), as well as by
association mapping performed by Shi et al. (2011). BLAST of the UBC420 marker
sequence (EF553635.1) against G19833 results in a match from 8,124,578-8125483
bp, and alignment between the two indicates 77% similarity.
The genes predicted in section contig1701-1 matched to ~5.8 Mbp which is
approximately 2.3 Mbp away from the UBC420 location on chromosome 6. In the case
of contig1701-2 genes, they matched to ~49.7 Mbp which is approximately 10 Mbp
away from SU91 on chromosome 8 (Perry et al. 2013). Schmutz et al. (2014) reported
the recombination rate of euchromatic arms to be 220 kb/cM, which indicates that the
regions to which the contig1701-1 and contig1701-2 genes have similarity to are 10.45
cM and 45.45 cM from the location of UBC420 on chromosome 6 and SU91 on
104
chromosome 8. Thus, the likelihood that CGs CBB1, CBB2, CBB3 and CBB4 are the
resistance genes associated with these CBB resistance markers is very small.
However, it is interesting that similar sequences are found in chromosomes 4, 6 and 8;
all of which have been associated with CBB resistance in various studies.
105
2.6 Conclusion
Candidate common bacterial blight (CBB) resistance genes CBB1-4 were
identified in the sequence of OAC Rex BiBAC2 library clones associated with CBB
resistance QTL marker PV-ctt001. Characterization of the candidate genes resulted in
the prediction of amino acid sequences which had leucine rich repeat (LRR)
characteristics including a consensus LRR motif sequence (LxxxLxLxLxxL). BLAST
comparisons of CG sequences to CBB susceptible common bean variety G19833
genome sequence identified similarities to retrotransposons in chromosome 6 and 8.
Protein sequence BLAST and secondary structure modelling indicated low similarity
between CGs and retrotransposon proteins. Characterization of gene predictions in the
sequence surrounding CGs CBB1-4 identified gene 5 as an ascorbate oxidase, which
has potential pathogen resistance implications.
106
Chapter 3: Detached leaf Xap susceptibility assay in Arabidopsis thaliana
3.1 Abstract
Efforts are currently underway to identify CGs for CBB resistance in common
bean and test them. As an alternative to transformation of common bean to observe
CG efficacy, a testing method using a model system would be beneficial. Here we
describe methods for inoculating detached Arabidopsis rosette leaves with different Xap
isolates, maintenance of the leaves in a tissue culture system over 192 hours, and
assaying disease progression in the inoculated tissue. Symptom progression and
assays of colony forming units (CFUs)/ unit of leaf tissue from inoculated leaf tissue
samples indicated that one isolate (Xap18) is more aggressive on Arabidopsis leaves
than other isolates. However, significant variation in establishing a disease state with
this system suggests that optimization of the protocol is needed to obtain consistent and
reproducible results.
107
3.2 Introduction
3.2.1 Common Bean Improvement
Breeding for the improvement crop species is a widely used tactic, especially in
the case of disease resistance. A major focus of common bean improvement has been
resistance to the bacterial disease common bacterial blight (CBB). CBB affects
worldwide production of P. vulgaris and is caused by the bacterial pathogen Xap and
fuscans variant Xff (Vauterin et al. 1995). Since little natural CBB resistance is
exhibited in common bean, introgression of resistance has occurred primarily by
interspecific crosses with resistant lines of P. acutifolius (Parker, 1985) and P.
coccineus (Park and Dhanvantari 1987; Miklas et al. 1994). Introgression of loci
associated with resistance into common bean lines has been achieved through
backcrossing, disease screening and marker assisted selection (MAS) and has
resulted in the development of CBB-resistant common bean varieties, including the
navy bean OAC Rex (Michaels et al. 2006). However, the use of markers for selecting
for resistance is limited by the possibility of the gene for resistance segregating from the
marker, creating the potential for false positives. The identification of the gene(s) that
confers resistance to CBB in common bean and subsequent development of a gene-
based marker would reduce the testing time and the frequency of false positives
involved in developing new disease resistant varieties.
3.2.2 CBB in A. thaliana
To test the involvement of a particular candidate gene in CBB resistance, a
testing method for the gene(s) in planta is desired. However, common bean has proven
to be a difficult species to transform (Gepts et al. 2008). This makes the use of gene
108
transformation to test CGs in susceptible varieties a difficult, if not impossible strategy,
and necessitates the use of other means of testing CGs for efficacy. Although common
bean is the primary host of CBB, a study by Perry (2010) indicated that the model plant
A. thaliana can be manually inoculated with Xap to produce CBB-like symptoms.
Chlorotic lesions appeared on Arabidopsis leaves inoculated with a mixture of Xap
isolates by 96 hours post inoculation (HPI). The lesions expanded and caused leaf
curling and eventually considerable tissue damage by 192 HPI. Symptoms also began
to appear around the margins of non-inoculated leaves in proximity to inoculated leaves,
which developed into symptoms similar to those of inoculated leaves. The
demonstration of Arabidopsis as a host makes it possible to test candidate CBB
resistance genes in the model system. By first transforming Arabidopsis with genes of
interest, the transformed plants can then be inoculated with Xap, and tested for
symptoms.
Although inoculation of leaves while still on the plant was shown to produce CBB-
like symptoms on Arabidopsis, for the purpose of testing transformed Arabidopsis
plants, a more precise, sterile and contained environment is preferred. The goal of this
study was to develop a tissue culture system to maintain detached rosette leaves post-
inoculation for the purpose of observing disease progression. This approach has the
potential to reduce the damage to the leaves and plant, as well as the likelihood of
introducing contaminating diseases during inoculation. This will help to improve the
ability to observe CBB symptom progression in Arabidopsis plants transformed with
candidate CBB resistance genes.
109
3.3 Materials and Methods
3.3.1 Bacterial and Plant Growth
A. thaliana ecotype Columbia seeds were suspended in distilled water at
approximately 50 seeds/mL and dispersed into 24-cell flats containing LA4 (Green
Island Distributors, Riverhead, N.Y.) that had been pre-soaked with deionized water and
drained. Flats were covered with clear plastic domes and maintained in a growth
chamber providing 16 h light (150 µmol/m2/s), 8 h dark on a daily cycle at 22 ºC.
Seeds from Phaseolus vulgaris varieties Nautica (susceptible) and OAC Rex
(resistant) were inserted in 6” round pots filled with LA4 and covered with a 1” layer of
medium vermiculite (Green Island Distributors, Riverhead, N.Y.). Pots were soaked with
deionized water and maintained in a growth chamber providing 16 h light and 8 h dark
cycle at 22oC.
Bacterial inoculum was generated by spreading 50 mL of Xap isolates 12, 18, 98
and 118, separately, on yeast salt 1% agar media plates and maintaining them at 28 ºC
for 48 h. Xap cultures were sub-cultured as streak plates for each isolate, and were
incubated for an additional 48 h at 28oC. The resultant colonies were then washed off
the plates into a 50 mL Falcon tube with 20 mL of distilled sterile water. The cell density
of the plate rinse was determined and diluted with distilled sterile water to an OD600 of
0.6 (1x107 colony forming units (CFU)/g) as needed.
3.3.2 Plant Wounding and Inoculation
Healthy rosette leaves were detached from 3-4 week old Arabidopsis plants
using a scalpel so that approximately 2 cm of petiole remained attached to the leaf.
Healthy P. vulgaris leaflets were detached from 3-4 week old plants. Inoculation was
110
performed by wounding each leaf or leaflet with a 10 µl plastic pipette tip once, close to
the mid-vein, and ejecting 10 µl of inoculum onto the wound site. Wound sites were
inoculated with 10 µl of either sterile distilled water or one of the four Xap isolates
(Xap12, Xap18, Xap98, Xap118) collected in Ontario (Park and Dhanvantari 1987). The
liquid inoculum was left on the wound site of each inoculated leaf to ensure infection.
Leaves representative of the 0 HPI were carefully transferred to a light blue background,
pictures were taken for IA, and then a sample of 1 cm2 of the tissue surrounding the
inoculation site was cut from the leaf.
Additional inoculated Arabidopsis, Nautica and OAC Rex leaves were placed in
tissue culture for further observations at 0, 48, 96 and 144 HPI. The Arabidopsis leaves
were placed in petri plates containing 0.7% water agar media. Both bean varieties were
placed in PhytatrayTM II boxes (Sigma-Aldrich Col. LLC) containing 0.7% water agar.
For both Arabidopsis and P. vulgaris, the leaves were kept upright at a 45o angle by
inserting the petiole into the solid media (Chen et al. 2006) to prevent the leaf blade
from contacting the agar. Phytatrays and petri plates were wrapped with Parafilm to
maintain a high relative humidity and placed into a 28 ºC tissue culture growth cabinet
set to 16 h light (150 µmol/m2/s) and 8 h dark in a randomized complete block design
where each experiment was a block. At 48 hour intervals post inoculation, pictures and
~1cm leaf samples were taken as described above, for assessment of disease symptom
progression over time.
111
3.3.3 Assessment of Disease Symptoms
3.3.3.1 Image Collection and Analysis
Disease symptom assessment was accomplished by performing Image Analysis
(IA) on inoculated leaves using the APS Assess 2.0 computer program (The American
Phytopathological Society, St. Paul, MN). Image collection of the inoculated common
bean leaves and subsequent IA was performed as described by Xie et al. (2012) to
determine the percent of the leaf area showing symptoms. The same procedure was
followed for inoculated Arabidopsis leaves. However the distance of the camera from
the Arabidopsis leaves was adjusted to 20 cm, to reflect the smaller size of the
Arabidopsis leaves. Manual IA was performed to determine the area of chlorosis and/or
necrosis for inoculated leaves at 0, 48, 96,144 and 192 HPI. Although there were no
symptoms at 0 HPI, pictures were taken to provide a visual comparison for later time
points when the symptoms had developed.
3.3.3.2 CFU Analysis
Samples of approximately 1 cm2 of the tissue surrounding the inoculation site
were taken from each leaf and homogenized in 0.9 ml of sterile distilled water (Perry,
2010). Serial dilutions of 103-fold and 105 -fold were made for samples taken at 0 HPI
for all inoculum types. The dilutions were plated on XCP media (10 g/L KBr, 0.25 g/L
CaCl2, 10 g/L potato starch, 10 g/L peptone, 10 ml/L Tween 80, 3 mg/L fluorouracil and
0.16 mg/L tobramycin pH 7.0; Remeeus and Sheppard 2006) for a final dilution of 105
and 107, and plates were incubated at 28oC for 48 hours. For samples taken at 48,
96,144 and 192 HPI, 105 and 107 fold serial dilutions were made for all inoculum types.
The dilutions were plated on XCP media plates for a final dilution of 107 and 109 and
112
incubated at 28oC for 48 hours. Visible colonies >2 mm in diameter were marked at 48
hours, and plates were incubated for an additional 96 hours. Colonies with visible
media clearing were then counted to provide the CFU value for the corresponding
inoculum type and time post inoculation.
3.3.4 Statistical Analyses
Variance analysis, lsmeans estimates and comparisons were performed on IA
lesion percent values and CFUs from a single replication of the experriment using
PROC MIXED in SAS 9.4 (SAS institute Inc., Cary, NC). Isolate, genotype and time
were all considered fixed effects. Tests for normality prompted log transformation of the
data, however further analysis was performed using untransformed data since
transformation did not improve the normality of the residuals. The data was sliced to
separate the effects of the different isolates, plant genotypes and time points post
inoculation on the interaction of all factors. ANOVA was performed to determine the
significance of the sliced effects. Letter grouping to show the significant differences
between lsmeans was performed using the PDMIX800 macro (Saxton 2000) with data
sliced for time to make comparisons between all lsmeans at the different time points.
For all analyses, an interaction was considered significant when the p-value was less
than 0.05.
113
3.4 Results
3.4.1 Analysis of Variance
Analysis of variance for OAC Rex and Nautica CFU and IA results showed that
the inoculum, genotype effects were significant (Appendix 5). Interactions between
inoculum and genotype, inoculum and time and genotype and time were also significant
(Appendix 5). Interaction between inoculum, genotype and time was not significant
(Appendix 5). Analysis of variance for Arabidopsis CFU and IA results showed that
inoculum and time effects were significant, and that the interaction between inoculum
and time was significant (Appendix 6).
3.4.2 Visual Observations and IA
3.4.2.1 Common Bean Visible Leaf Symptoms
Nautica and OAC Rex leaves inoculated with water showed no visible disease
symptoms at all sampling time-points, and lsmeans of percent of leaf with disease
symptoms (hereafter known as symptoms) showed no significant differences between
time points or variety (Appendix 7-9; Figure 3.1A; Tables 3.1-3.2 and 3.8-3.9). Xap
inoculated leaves from both common bean varieties were not significantly different for
inoculation with any of the four isolates or water at 0, 48 and 96 HPI (Appendix 7-9;
Figure 3.1B-E). At 144 HPI, significant differences were seen between the symptoms
seen in Nautica and OAC Rex leaves when inoculated with Xap isolates (Figure 3.1;
Table 3.1). OAC Rex leaves showed no significant difference between water and Xap
inoculation (Figure 3.1; Table 3.1). Xap and water inoculated Nautica leaf symptoms
were significantly different when isolates Xap98 and Xap118 were used, with the most
severe symptom being observed in the Xap98 inoculated sample (36.21%) (Figure 3.1
114
Figure 3.1. Symptom progression in inoculated P. vulgaris leaves. Percent leaf area showing symptoms at 0, 48, 96, 144
and 192 hours post inoculation (HPI). Inoculations were performed on leaves of susceptible (Nautica – dark colour) and
resistant (OAC Rex - light) varieties with water (A - Black) or one of four X. axonopodis pv. phaseoli (Xap) isolates; Xap12
(B - Red), Xap18 (C - Purple), Xap98 (D - Blue) and Xap118 (E - Green). Error bars represent the standard error of the
values of the lsmeans (+ 6.18).
0
10
20
30
40
50
60
70
80
0 48 96 144 192
Sym
pto
ms (%
Leaf
Are
a)
Hours Post-Inoculation (HPI)
A) WATER
0
10
20
30
40
50
60
70
80
0 48 96 144 192
Sym
pto
ms (%
Leaf
Are
a)
Hours Post-Inoculation (HPI)
B) Xap12
0
10
20
30
40
50
60
70
80
0 48 96 144 192
Sm
pto
ms (%
Leaf A
rea)
Hours Post-Inculation (HPI)
C) Xap18
0
10
20
30
40
50
60
70
80
0 48 96 144 192
Sm
pto
ms (%
Leaf A
rea)
Hours Post-Inoculation (HPI)
D) Xap98
0
10
20
30
40
50
60
70
80
0 48 96 144 192
Sym
pto
ms
(% L
eaf
Are
a)
Hours Post-Inoculation (HPI)
E) Xap118
115
A, D, E; Table 3.1). At the last time point (192 HPI) there were significant differences
between Nautica and OAC Rex for inoculation with each Xap isolate (Figure 3.1; Table
3.2). Inoculation of OAC Rex leaves, resulted in symptoms that were significantly
different from water inoculation only when isolate Xap118 was used (31.65%) (Figure
3.1 A, E; Table 3.2). All isolates produced symptoms greater than water inoculation in
Nautica leaves, with the highest percentage of affected leaf being observed in the
samples inoculated with Xap118 (66.71%) (Figure 3.1 A-E; Table 3.2).
3.4.2.2 Arabidopsis Visible Leaf Symptoms
Arabidopsis leaves inoculated with water showed no visible disease symptoms at
all sampling time-points, and lsmeans of symptoms showed no significant differences
between time points (Appendix 7-9; Figure 3.2A; Tables 3.1-3.2 and 3.7). Xap
inoculated Arabidopsis leaves were not significantly different than the water controls or
each other with any of the four isolates at 0, 48 and 96 HPI (Appendix 7-9; Figure 3.2;
Table 3.7). At 144 HPI, all Xap isolates produced symptoms that were significantly
higher than the water control in Arabidopsis leaves, with the most severe symptoms
being produced by Xap98 (24.50%) (Figure 3.2; Table 3.1). However, at 192 HPI, the
symptoms in Arabidopsis leaves that were induced by Xap98 (2.10%) were not
significantly different than in the water control (Figure 3.2; Table 3.2). Symptoms
induced by the other isolates at 192 HPI were significantly higher than the water control
for the other isolates with the highest mean symptoms being produced by Xap18
(19.30%) (Figure 3.2; Table 3.2).
116
Figure 3.2. Symptom progression in inoculated A. thaliana rosette leaves. Percent leaf
area showing symptoms for Arabidopsis rosette leaves at 0, 48, 96, 144 and 192 hours
post inoculation (HPI). Inoculations were performed using water (black) as a control,
and one of four X. axonopodis pv. phaseoli (Xap) isolates Xap12 (red) Xap18 (purple)
Xap98 (blue) and Xap118 (green). Error bars represent the standard error of the values
of the lsmeans (+ 3.06).
0
5
10
15
20
25
30
0 48 96 144 192
Sym
pto
ms (%
Leaf
Are
a)
Hours Post-Inoculation (HPI)
117
Table 3.1. LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 144 hours post inoculation (HPI). Percent of leaf showing disease symptoms for OAC Rex, Nautica and Arabidopsis inoculated with water, Xap12, Xap18, Xap98 and Xap118 at 144 HPI
Symptoms (%)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 1.87 XZ
c 2.72 X
c 3.14 X
c 4.72 X
c 7.90 X
c 4.07 WY
B
Nautica 1.88 X c 3.78
X c 6.38
X c 36.2
X a 14.8
X bc 12.6
W A
Arabidopsis 1.68V x 16.6
V yz 13.9
V y 24.5
V z 9.79
V xz 13.3
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +127.80
WDenotes lsmeans with a standard error of +57.1532
VDenotes lsmeans with a standard error of +3.06
UDenotes lsmeans with a standard error of +1.37
Table 3.2. LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 192 hours post inoculation (HPI). Percent of leaf showing disease symptoms for OAC Rex, Nautica and Arabidopsis inoculated with water, Xap12, Xap18, Xap98 and Xap118 at 192 HPI
Symptoms (%)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 1.62YZ
f 10.7Y
def 2.69Y f 5.27
Y ef 31.7
Y bc 10.4
X B
Nautica 7.07Y def 20.4
Y cd 57.1
Y a 38.7
Y b 66.7
Y a 38.0
X A
Arabidopsis 1.04 V
x 9.3 V xy 19.3
V z 2.10
V x 12.6
V yz 8.87
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +127.80
WDenotes lsmeans with a standard error of +57.1532
VDenotes lsmeans with a standard error of +3.06
UDenotes lsmeans with a standard error of +1.37
118
3.4.3 Leaf Sample CFUs
3.4.3.1 Common Bean CFUs
CFUs produced from leaf samples taken from water-inoculated Nautica and OAC
Rex leaves were not significantly different at all time-points (Appendix 10; Figure 3.3 A;
Table 3.3-3.6). There were also no significant differences between CFU produced from
either bean genotype inoculated with water or the four Xap isolates at 0 HPI (Appendix
10; Figure 3.3 B-E; Table 3.3). At 48, 96, 144 and 192 HPI, there were significant
differences between the CFUs for OAC Rex and Nautica leaf samples inoculated Xap
isolates (Figure 3.3; Table 3.3-3.6). At 48 HPI, OAC Rex CFU means were significantly
different from water when Xap18 and Xap98 were used, with the highest mean being
produced by Xap18 (7.64 x 107 CFU) (Figure 3.3 C-D; Table 3.3). All isolates
produced CFU means that were significantly different from water in Nautica leaves, with
the highest being produced by inoculation with Xap18 (1.07 x 108 CFU) (Figure 3.3;
Table 3.3). At 96 HPI, OAC Rex CFU means were significantly different from water
inoculation when Xap18 and Xap98 were used, with the highest mean being produced
by Xap18 (7.03 x 107 CFU) (Figure 3.3 C-D; Table 3.4). Inoculation of Nautica leaves
by all Xap isolates produced CFUs that were significantly different from water
inoculation, with the highest mean being produced by Xap118 (1.10 x 108 CFU) (Figure
3.3; Table 3.4). At 144 HPI, OAC Rex leaf samples produced significantly more CFU
than the water control only when inoculated with Xap18 (4.57 x 107 CFU) (Figure 3.3 C;
Table 3.5). All isolates produced more CFUs than the water inoculation in the Nautica
leaf samples, with the highest mean being produced by Xap18 (1.18 x 108 CFU) (Figure
3.3; Table 3.5). At 192 HPI all isolates produced CFUs that were significantly higher
119
Figure 3.3. Pathogen growth in inoculated P. vulgaris leaf samples. Colony forming units (CFU) for leaf samples taken
from susceptible (Nautica -dark) and resistant (OAC Rex - light) varieties, respectively at 0, 48, 96, 144 and 192 hours
post inoculation (HPI). Inoculation was performed with water (A - Black) or one of four X. axonopodis pv. phaseoli (Xap)
isolates; Xap12 (B - Red) Xap18 (C - Purple) Xap98 (D - Blue) and Xap118 (E - Green). Error bars represent the
standard error of the values of the lsmeans (+ 142).
0
200
400
600
800
1000
1200
1400
0 48 96 144 192Colo
ny F
orm
ing U
nits (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
A) WATER
0
200
400
600
800
1000
1200
1400
0 48 96 144 192Colo
ny F
orm
ing U
nits (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
B) Xap12
0
200
400
600
800
1000
1200
1400
0 48 96 144 192Colo
ny F
orm
ing U
nit (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
C) Xap18
0
200
400
600
800
1000
1200
1400
0 48 96 144 192Colo
ny F
orm
ing U
nits (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
D) Xap98
0
200
400
600
800
1000
1200
1400
0 48 96 144 192Colo
ny F
orm
ing U
nits (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
E) Xap118
120
than observed for the water inoculated leaf samples for both OAC Rex and Nautica
(Figure 3.3; Table 3.6). The highest mean CFUs produced were produced by
inoculation with Xap18, which had 4.57 x 107 CFU and 1.18 x 108 CFU for OAC Rex
and Nautica, respectively (Figure 3.3 C; Table 3.6).
3.4.3.2 Arabidopsis CFUs
Arabidopsis leaves inoculated with water showed no visible disease symptoms at
all sampling time-points, and lsmeans of symptoms showed no significant differences
between time points (Appendix 10; Figure 3.4; Table 3.3-3.6). At 0 HPI, none of the
Xap isolates produced CFU means that were significantly different from water
inoculation (Appendix 10; Figure 3.4 B-E). At 48 HPI, only Xap98 produced a CFU
mean that was significantly higher than the water sample (4.76 x 107 CFU) (Figure 3.4
D; Table 3.3). At 96 HPI, all Xap isolates leaves produced CFU means that were
significantly higher than water inoculated leaves, with the highest mean being produced
by Xap18 (5.76 x 107 CFU) (Figure 3.4; Table 3.4). At 144 HPI, all Xap isolates
produced CFU means that were significantly higher than water inoculated leaves, with
the highest mean being produced by Xap18 (6.76 x 107 CFU) (Figure 3.4; Table 3.5). At
192 HPI, all Xap isolates leaves produced CFU means that were significantly higher
from water inoculated leaves, with the highest mean being produced by Xap18 (1.04 x
108 CFU) (Figure 3.4; Table 3.6).
121
Figure 3.4. Pathogen growth in inoculated A. thaliana leaf samples. Colony forming
units (CFU) for Arabidopsis leaves 0, 48, 96, 144 and 192 hours post inoculation (HPI).
Inoculation was performed with water (black), Xap12 (red), Xap18 (purple), Xap98
(blue), or Xap118 (green). Error bars represent the standard error of the values of the
lsmeans (+ 96.3).
0
200
400
600
800
1000
1200
0 48 96 144 192
Colo
ny F
orm
ing U
nits (
CF
U x
10
5)
Hours Post-Inoculation (HPI)
122
Table 3.3. LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 48 hours post inoculation (HPI). CFUs were determined by incubating 105 dilutions of ground leaf samples taken from inoculated leaves from resistant (OAC Rex) and susceptible (Nautica) P. vulgaris varieties, and Arabidopsis. Samples were taken at 48 HPI after inoculation with Water, Xap12, Xap18, Xap98 or Xap118.
CFU (x 105)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 108 XZ
de 348 X cde 764
X ab 704
X abc 8.67
X e 387
WY B
Nautica 107 X de 676
X abc 1070
X a 920
X a 452
X bcd 645
W A
Arabidopsis 49.7 Y y 261
Y yz 307
Y yz 476
Y z 297
Y yz 278
W
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +142
WDenotes lsmeans with a standard error of +63.6
VDenotes lsmeans with a standard error of +96.3
UDenotes lsmeans with a standard error of +43.1
Table 3.4. LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 96 hours post inoculation (HPI). CFUs were determined by incubating 105 dilutions of ground leaf samples taken from inoculated leaves from resistant (OAC Rex) and susceptible (Nautica) P. vulgaris varieties, and Arabidopsis. Samples were taken at 96 HPI after inoculation with Water, Xap12, Xap18, Xap98 or Xap118.
CFU (x 105)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 48.7 XZ
de 101 X de 703
X abc 445 cd 171
X de 294
WY B
Nautica 3.00 X e 667
X bc 1070
X a 957
X ab 1100
X a 761
W A
Arabidopsis 26.7 V x 206
V yz 567
V z 420
V yz 310
V yz 306
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +142
WDenotes lsmeans with a standard error of +63.6
VDenotes lsmeans with a standard error of +96.3
UDenotes lsmeans with a standard error of +43.1
123
Table 3.5. LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 144 hours post inoculation (HPI). CFUs were determined by incubating 105 dilutions of ground leaf samples taken from inoculated leaves from resistant (OAC Rex) and susceptible (Nautica) P. vulgaris varieties, and Arabidopsis. Samples were taken at 144 HPI after inoculation with Water, Xap12, Xap18, Xap98 or Xap118.
CFU (x 105)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 57.7 XZ
c 183 X bc 457
X b 207
X bc 204
X bc 222
WY B
Nautica 0.333 X
bc 425 X b 1180
X a 1130
X a 1050
X a 756
W A
Arabidopsis 0V x 321
V y 667
V z 532
V yz 295
V y 363
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +142
WDenotes lsmeans with a standard error of +63.6
VDenotes lsmeans with a standard error of +96.3
UDenotes lsmeans with a standard error of +43.1
Table 3.6. LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 192 hours post inoculation (HPI). CFUs were determined by incubating 105 dilutions of ground leaf samples taken from inoculated leaves from resistant (OAC Rex) and susceptible (Nautica) P. vulgaris varieties, and Arabidopsis. Samples were taken at 192 HPI after inoculation with Water, Xap12, Xap18, Xap98 or Xap118.
CFU (x 105)
Inoculum
Genotype Water Xap12 Xap18 Xap98 Xap118 Genotype Mean
OAC Rex 34.7 XZ
c 789 X ab 863
X ab 804
X ab 592
X b 617
WY A
Nautica 0X c 1100
X a 1180
X a 1070
X a 625
X b 794
Y A
Arabidopsis 0V w 319
V x 1040
V z 316
V x 660
V y 467
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +142
WDenotes lsmeans with a standard error of +63.6
VDenotes lsmeans with a standard error of +96.3
UDenotes lsmeans with a standard error of +43.1
124
Table 3.7. Inoculated A. thaliana leaf symptom progression. Arabidopsis rosette leaves were inoculated with sterile distilled water control and X. axonopodis pv. phaseoli (Xap) isolates 12, 18, 98 and 118. Pictures were taken at 0, 48, 96, 144 and 192 hours post inoculation (HPI)
Inoculum
Hours Post Inoculation
0 48 96 144 192
Water
Xap12
Xap18
Xap98
Xap118
125
Table 3.8. Inoculated common bacterial blight susceptible P. vulgaris variety leaf symptom progression. Trifoliate Nautica leaves were inoculated with sterile distilled water control and X. axonopodis pv. phaseoli (Xap) isolates 12, 18, 98 and 118. Pictures were taken at 0, 48, 96, 144 and 192 hours post inoculation (HPI)
Inoculum
Hours Post Inoculation
0 48 96 144 192
Water
Xap12
Xap18
Xap98
Xap118
126
Table 3.9. Inoculated common bacterial blight resistant P. vulgaris variety leaf symptom
progression. Trifoliate OAC Rex leaves were inoculated with sterile distilled water
control and X. axonopodis pv. phaseoli (Xap) isolates 12, 18, 98 and 118. Pictures
were taken at 0, 48, 96, 144 and 192 hours post inoculation (HPI)
Inoculum
Hours Post Inoculation
0 48 96 144 192
Water
Xap12
Xap18
Xap98
Xap118
127
3.5 Discussion
3.5.1 Symptom Development
3.5.1.1 Common Bean Symptom Evaluation by IA
The highest disease symptoms were generally produced in Nautica, with
significant variability caused by the isolate used. Nautica was included in this study as
a Xap susceptible common bean check variety. Therefore, the increased symptoms
observed in Nautica leaves compared to OAC Rex leaves inoculated with the same Xap
isolate was consistent with the expectation that this variety would show more severe
symptoms in a shorter time after inoculation. Although a direct comparison is not
possible due to the differences between experimental parameters and the resistant
varieties used, a comparison of the symptom severity scores observed in the current
study with detached leaves to those reported for a similar growth chamber study (Xie
et al. 2012) with intact plants, suggests that the disease reaction was more severe in
the current detached leaf assay. In the previous study, the percent lesion area was
6.03% for Nautica and 0.22-0.29% for the resistant varieties (MBE7, Rexeter and Apex)
14-18 days post inoculation (336-432 HPI) (Xie et al.2012). In contrast, Nautica and
OAC Rex symptoms covered 38.0% and 10.4% of the leaves, respectively, at 192 HPI
in the current study (Table 3.2).
There are several potential explanations for the observed differences between
the results reported by Xie et al. (2012) and those obtained in the current study. The
most immediate explanation is that the environment provided by the tissue culture is
more suited for symptom development. However, it is also possible that there are
differences in the reaction to pathogens in detached versus attached leaves. This was
128
observed previously in Arabidopsis by Liu et al. (2007b), when attached and detached
leaves were inoculated with either Colletotrichum linicola A1 or C. higginsianum,
resulting in opposite responses. Inoculation with C. linicola A1 did not affect attached
leaves, but it did infect detached leaves. In contrast, inoculation with C. higginsianum
did affect attached leaves, but not when they were detached.
Other possible causes for the increased symptom severity in the detached leaf
assay are differences in the sizes and developmental stages of the leaves. In both the
common bean study performed by Xie et al. (2012) and the Arabidopsis study
performed by Perry (2010), inoculated leaves remained on the plant for the duration of
the experiment. This allowed the leaves to continue to grow, whereas, the detached
leaves in the current study remained approximately the same size, which would affect
the relative symptom size. Since the media used in this study lacked any additional
nutrients, the detached leaves may have had an impaired ability to produce a resistance
response due to lack of resources.
In the current study, trifoliate leaves with different sizes and developmental
stages were used, whereas, Xie et al. (2012) used only unifoliate leaves. Not only were
the trifoliate leaves smaller than the unifoliate leaves, some of the leaves used for
inoculation were quite new, which may have made them more susceptible to Xap
infection than the unifoliate leaves. This is consistent with the study performed by Jung
et al. (1997), which found that there was a significant strain by organ interaction, and
that certain QTL only contributed to resistance in specific organs and developmental
stages. The Random Amplified Polymorphic DNA (RAPD) marker D13.1000, in
129
particular, was only associated with resistance to Xap isolate DR-7 in the first trifoliate
leaves, and not in later trifoliate leaves, pods or seeds.
3.5.1.2 Arabidopsis Symptom Evaluation by IA
Xap induced symptoms on Arabidopsis leaves were variable compared to those
induced on common bean leaves of both varieties. The mean symptom percent for
Arabidopsis was higher than the means for both Nautica and OAC Rex at 144 HPI,
indicating that it’s response to Xap inoculation was similar to the susceptible Nautica
(Table 3.1). This contrasted to the symptom severity observed in Arabidopsis leaves
at 192 HPI, which was lower than that observed for Nautica or OAC Rex (Table 3.2).
This change from a susceptible symptom mean to a resistant one, over time, is likely
caused by the changes observed in two isolates in particular. The symptoms produced
by isolates Xap12 and Xap98 were the highest at 144 HPI, and then dropped
significantly at 192 HPI (Figure 3.1 B, D; Table 3.1-3.2). However, the symptoms
produced by Xap18 and Xap118 increased from 144 to 192 HPI (Figure 3.1 C, E; Table
3.1-3.2).
This change from high to low symptoms in Xap12 and Xap98 inoculated
Arabidopsis leaves may be a reflection of the ability of these isolates to infect
Arabidopsis. It is also possible that the conditions of those detached leaves were
particularly conducive to disease progression such as increased humidity or light
availability, or that contamination from another pathogen occurred. However, since
only one set of assays was performed, and the results are not entirely consistent with
those observed in the study by Perry (2010), more repetitions of the experiment are
needed to determine if this is a significant trend, or a random occurrence.
130
3.5.1.3 Symptom Evaluation of CFUs
When compared to the collected IA data, the CFU means were more variable
than the data based on symptom development. However, all genotypes showed
significant differences between Xap- inoculation means and water inoculation means as
early as 48 HPI. Additionally, Nautica generally had the highest CFU values compared
to OAC Rex, which is consistent with the trends observed by IA. This supports the
assumption that the symptoms are caused by the proliferation of the pathogen in the
tissue.
Nevertheless, some inconsistencies like the observation that the highest CFU
values were induced by Xap18 on all three leaf types. Although the highest symptoms
observed in Arabidopsis were also produced by inoculation with isolate Xap18, the
highest values induced in leaves from both common bean varieties were from
inoculation with isolate Xap118. The difference in common bean and Arabidopsis
symptom development in response to inoculation with Xap18 is further emphasized by
the lack of difference between the symptoms produced in OAC Rex leaves inoculated
by water and Xap18. It is also interesting to note that leaves from all genotypes
inoculated with Xap18 tended to be a lighter green than leaves inoculated with other
isolates (Figures 3.7-3.9), which indicates that Xap18 affects a larger area within the
leaf, instead of causing localized lesions. This suggests that Xap18 symptoms included
more than localized lesions, and that IA didn’t entirely capture Xap18 symptoms
because the IA parameters measured lesions (chlorosis and necrosis), and the lighter
green colour was not taken into account. These symptom and CFU differences
131
suggest that differences in the interaction between the genotype and Xap isolate are at
play.
The variability in Xanthomonas host specificity, both within and between species
and pathovars, has been well documented (Rademaker et al. 2005: Sun et al. 2006;
Bogdanove et al. 2011), as well as specifically for the Xap-P. vulgaris interaction
(Schuster et al. 1983; Mkandawire et al. 2004; Duncan et al. 2010; Fourie and
Herselman 2011). Within the four Xap isolates used in Ontario breeding efforts, isolates
Xap98 and Xap118 have been observed to be the most virulent on common bean
varieties. It is likely that human error is responsible for the discrepancy between the
Xap18 IA and CFU results observed in both common bean genotypes. Just as the IA
results may be lower than they should be (discussed above), the CFUs may be higher
than actual due to inexperience in counting. Since the IA and CFU means for Xap18
inoculated Arabidopsis leaves progressed in a similar way (Figure 3.2; Figure 3.4), it is
most likely that the suggested higher virulence of this strain on Arabidopsis is reliable.
However, replication of the study is required to determine the significance of these
results.
3.5.2 Suitability of Detached Arabidopsis Leaf CBB Assay
3.5.2.1 Variability in CFU Observations
Considering the variability of the CFU counts over the course of the study, it must
be concluded that CFU count cannot be taken as an independent measure of isolate
virulence. However, the study has limited scope due to the failure to replicate the
results using a single isolate (Xap12) (data not shown). Additional studies with different
parameters might reduce the variability in the results by providing more data, and
132
reducing human error. Regardless of the limitations of the CFU method to compare
virulence between isolates within the current study, it does demonstrate that Xap
accumulates in inoculated leaf samples over time. Therefore, when combined with IA
values, CFU values can be used as an indicator of proliferation within the inoculated
sample.
The failure of the experiments with detached Arabidopsis leaves and a single
Xap isolate (Xap12) to replicate the symptoms observed with attached Arabidopsis
leaves may have been caused by the isolate selection. This isolate initially produced
symptoms in Arabidopsis rosette leaves that were visibly similar to those observed by
Perry (2010) at 144 HPI (Table 7). However, these symptoms have not been observed
in subsequent experiment repetitions, and statistical analysis of the initial results
showed that Xap12 produces low IA symptom means and CFU counts in Arabidopsis,
as well as OAC Rex and Nautica, in comparison to other isolates (Figure 3.1-3.4).
A more appropriate choice of Xap isolates for further replications of this study
would be Xap18, which was shown to produce the highest symptoms in Arabidopsis at
192 HPI (19.3%). This isolate also had a more consistent increase in symptoms and
CFU means over time compared to Xap12. Symptoms produced by Xap12 increased
quickly and then dropped, whereas Xap18 inoculation produced a more steady increase
in symptoms (Figure 3.2). This was even more evident with the CFU means, where
Xap18 CFU means increased at a relatively steady rate over time, whereas Xap12 CFU
means fluctuated around an apparent plateau from 48 to 192 HPI (Figure 3.4).
133
3.5.2.2 Detached Leaf vs. Attached Leaf Symptom Progression
The symptom progression in detached Arabidopsis leaves did not follow the
pattern of symptom development that was observed in inoculated leaves on the plant,
where chlorotic symptoms developed around 96 HPI and increased to the point of
considerable damage by 192 HPI (Perry 2010). However, the much slower
development of symptoms in the detached leaves, which were not significantly different
from water until 144 HPI, and varied in severity at 192 HPI depending on which isolate
was used, may have been due to the amount of inoculum and delivery method used in
this study compared to the one performed by Perry (2010). This study inoculated the
detached leaves with 10 µl of inoculum, with a directed injury to the adaxial side of the
leaf, where the inoculum was left on top of the injury location. This contrasts with the
~200 µl of inoculum used in the previous study, which was forced into the intercellular
matrix by infiltration on the abaxial side of the leaf. The use of the infiltration method
would likely have caused injury not only to the site of inoculation, but the region
surrounding it, causing artificially high symptoms compared to the single small injury
location used in this study.
The increased damage potential and resultant effect on symptom development of
the infiltration method on attached leaves was one of the motivations for the
development of the detached leaf tissue culture method. It also provided a more
controllable environment, which was hypothesized to decrease the variability and
increase reproducibility of the results, as was observed by Chen et al. (2006) in their
detached leaf assay for observing Fusarium graminearum infection in Arabidopsis.
However, Chen et al. (2006) required the use of an external disease factor
134
deoxynivalenol (DON) to provide consistency to the symptoms caused by wounding and
inoculation with F. graminearum, and a similar option is not available for Xap
inoculation.
A possible combination of the infiltration and detached leaf methods would be to
inoculate detached Arabidopsis leaves with Xap isolates using the infiltration method. A
similar technique was reported for peach detached leaves by Randhawa and Civerolo
(1985). In their study, they used paper towels to cushion and support detached peach
leaves while they were infiltrated with Xanthomonas campestris pv. pruni. They
reported that this resulted in little damage to the leaves, suggesting that infiltration of
detached Arabidopsis leaves may be possible with the use of cushioning such as
sterilized filter paper.
Another possible explanation of the differences in symptoms seen in the previous
study (Perry 2010) and the current study is that the latter used a mixture of all four
isolates to inoculate the leaves on the plant, whereas, the current study used individual
isolates. The use of the bacterial mixture may have resulted in exposure of the leaf
tissue to several effectors, simultaneously, thus enabling infection of Arabidopsis, even
though it is not a natural host. This has been documented before in literature, such as
the infection of Arabidopsis by non-host Pseudomonas syringae pv. tomato DC3000 (Li
et al. 2005), where the tomato pathovar overcomes non-host defense by the secretion
of multiple effectors.
135
3.6 Conclusion
The use of a detached leaf assay indicate the susceptibility of A. thalianarosette
leaves inoculated with Xap isolates could be an important tool when testing CBB
resistance genes in the model plant system. This study demonstrated that CBB
symptoms and increased Xap CFUs accompany the inoculation of detached
Arabidopsis and common bean leaves with Xap isolates at 192 HPI. However, variability
in disease response compared to previous common bean and Arabidopsis Xap
inoculation studies prevent conclusions to be made about the efficacy of this bioassay.
More work needs to be performed to optimize this method.
136
Chapter 4: Candidate Common Bacterial Blight Resistance Gene Expression in a
Resistant (OAC Rex) and Susceptible (Seaforth) Variety of Phaseolus vulgaris
4.1 Abstract
Resistance to common bacterial blight, caused by Xanthomonas axonopodis pv.
phaseoli (Xap) is a quantitative trait in common bean (P. vulgaris), introduced from
tepary bean (P. acutifolius) and selected for in common bean to produce resistant
varieties such as OAC Rex (Michaels et al. 2006). Although selection for QTLs by their
associated markers has been successful in producing resistant varieties of common
bean, direct selection for a gene underlying the QTL would provide greater speed and
power of selection. This study aimed to measure the expression of candidate CBB R
genes CBB2, CBB3 and CBB4 in resistant (OAC Rex) and susceptible (Seaforth)
varieties after inoculation with water (control) or Xap, for up to 168 HPI. To measure
expression, leaf samples were collected at 0, 12, 24, 36, 48, 72, 96, 120, and 168 HPI,
RNA was isolated and cDNA synthesized via RT-PCR was examined by gel
electrophoresis. Expression of CGs was not observed consistently, suggesting that
none of the CGs are involved in resistance to CBB, or that there were some limitations
to the experimental protocol that prevented expression of the CGs to be measured.
Further studies are needed to confirm these results, and to identify and test more CGs.
137
4.2 Introduction
4.2.1 Significance of Common Bean
Common dry bean (P. vulgaris) is a widely grown legume crop species, which is
produced in Canada for its dry grain and fresh pods. Edible dry beans are a
recommended part of a healthy human diet (Health Canada, www.hc-sc.gc.ca)
because they contain high levels of protein (Yañez et al. 1995), dietary fibre and
complex carbohydrates, vitamins such as folate, and minerals (Tosh and Yada 2010).
They are also low in fats and high in resistant starches. In Canada, common bean is
grown in Ontario, Manitoba, and Alberta (Goodwin 2005). Most of the production is
primarily exported to the US and Europe, as only a small portion is consumed in
Canada.
Common bean production is restricted due to a variety of abiotic factors such as
frost, humidity and soil quality as well as biotic factors, in particular weeds and diseases
(Goodwin 2005). A combination of management practices and variety selection are
employed to reduce the effect of these factors on yield quality and quantity, however
there is room for improvement, especially for increased disease resistance.
4.2.2 CBB in Common Bean
One of the major diseases of common dry bean, which affects producers world-
wide is CBB, caused by the bacterial pathogen Xap and its fuscans variety Xff (Vauterin
et al. 1995). The disease affects producers yearly, with severity dependent on the
susceptibility of the variety and environmental factors, such as humidity and
temperature, with yield reduction between 10-45% being observed (Saettler 1989;
Gillard et al. 2009). Since the symptoms may develop on the leaves, stems, pods and
138
seeds of infected plants (Vidaver 1993), CBB not only affects yield potential, but the
quality of the marketable portion of the plant – the seeds and pods.
4.2.3 CG Testing in Common Bean
P. vulgaris has little natural resistance to Xap. However, close relatives of the
species, P. acutifolius (tepary bean) and P. coccineus (scarlet runner bean) have
resistant genotypes (Mohan 1982; Drijfhout and Blok 1987; Singh and Muñoz 1999).
These relatives have been used to introduce resistance to CBB into P. vulgaris lines,
and have resulted in the production of varieties which are considered resistant, as they
exhibit delayed and/or reduced symptoms. CBB resistance is a quantitative trait in
common bean, with multiple major and minor quantitative trait loci (QTLs) being
mapped in many populations (Miklas et al. 2000b; Tar’an et al. 2001; Blair et al. 2003;
Cordoba et al. 2010; Shi et al. 2011). However, it has been shown that P. acutifolius
has a high level of leaf and pod resistance which is controlled by one dominant gene
and displays a characteristic hypersensitive response (Drijfhout and Blok 1987).
Although mapping of CBB resistance QTLs has helped to identify regions of the
genome that are associated with the trait, specific genes and their expression patterns
in response to Xap inoculation have yet to be identified. The aim of this study was to
measure expression from candidate CBB R genes (predicted in Chapter 2) in response
to the inoculation by Xap in resistant and susceptible bean cultivars. The study tested
the hypothesis that CBB R genes would be upregulated in leaf samples inoculated with
Xap in resistant P. vulgaris compared to water inoculated resistant, and water and Xap-
inoculated susceptible P. vulgaris.
139
4.3 Materials and Methods
4.3.1 Plant and Inoculum Preparation
4.3.1.1 Plant Growth
A total of 50 plants each for P. vulgaris resistant variety (OAC Rex) and
susceptible variety (OAC Seaforth) were potted in 5” round pots filled with pre-
moistened LA4 mix (Green Island Distributors, Riverhead, N.Y.) at 5 seeds per pot, and
covered with medium vermiculite. The pots were soaked with deionized water with
fertilizer (20-20-20 N-P-K), and maintained in a growth room providing 16h light (150
µmol/m2/s), 8h dark cycle at 22oC until the uni-foliate stage (~10 days). At this point, all
plants from each variety were inoculated, placed in a misting chamber, and the
temperature was raised to 28oC daytime temperature and 20oC night temperature, with
80% humidity. A second replication was performed which included 90 plants to
accommodate additional time points.
4.3.1.2 Inoculum Preparation
Bacterial inoculum was generated by spreading 50 mL of Xap isolate 98 (Xap98)
on 5 yeast salt media plates with 1% agar, and maintaining them at 28oC for 48 hours.
To generate a liquid inoculum, the colonies were washed off the plates with distilled
sterile water and diluted with distilled sterile water to an OD600 of 0.3. Control inoculum
was prepared by autoclaving distilled water.
4.3.1.3 Plant Inoculation
Plant inoculations were performed using the multiple needle method (Yu et al.
2000b). Both uni-foliate leaves of each plant were pierced by needles into a sterile
140
sponge soaked in inoculum. The needles were removed and inoculum soaked sponges
were squeezed gently against either side of the punctured leaf.
4.3.2 Sample Collection and Analysis
4.3.2.1 Sample Collection and Preparation
Single whole-leaf samples were taken from three plants per treatment (Xap98
and water control) per time point for OAC Rex and Seaforth varieties respectively.
Samples were removed from the plant and immediately frozen in liquid nitrogen to
preserve RNA present in the leaf. Samples were taken at 0, 12, 24, 48, 72, 96, 120 HPI
for the first replication (January 2013) and 0, 12, 24, 36, 48, 72, 96, 120 and 168 HPI for
the second replication (February 2013). Frozen leaf samples were maintained in a -
80oC freezer until grinding and RNA isolation.
Whole leaf samples were ground to a fine powder using a mortar and pestle
chilled to -80oC by liquid nitrogen. Ground tissue samples were transferred to liquid
nitrogen chilled 1.5 mL centrifuge tubes in ~100 mg aliquots and stored in a -80oC
freezer until further analysis.
4.3.2.2 RNA Isolation
RNA was isolated from ~100 mg samples of ground leaf tissue using Qiagen
RNeasy Plant RNA isolation kit. Aliquots of ground leaf tissue were placed in liquid
nitrogen to maintain -80oC temperature and added to 450 µl of RLT buffer – β-
mercatoethanol mixture (1 mL RLT buffer and 10 µL β-mercaptoethanol) then vortexed
for ~5 seconds. The mixture was then added to the QIAshredder column and
centrifuged for 2 minutes at 15,000 RPM. The supernatant was then mixed with ~225
µL 100% ethanol, the mixture was added to an RNeasy Mini spin column and
141
centrifuged for 15 seconds at 10,000 RPM. The flow-through was discarded, 700 µL of
RW1 buffer was added to the RNeasy spin column and centrifuged for 15 seconds at
10,000 RPM. The flow-through was discarded and 500 µL of RPE buffer was added to
the spin column and centrifuged at 15 seconds at 10,000 RPM. This step was repeated
with centrifugation lasting for 2 minutes. The spin column was then transferred to a 1.5
µL tube, 50 µL of RNase-free water was added to the column membrane and the tube
was centrifuged for 1 minute at 10,000 RPM to elute the RNA.
The RNA concentrations of the eluted samples were measured by applying 1 µL
of the RNA sample to the Nanodrop ND-1000 Spectrophotometer (Thermo Fisher
Scientific Inc. © 2013, Wilmington DE) pedestal. RNA quality was determined by both
by the 260/280 (>1.90) and 260/340 (> 1.80) absorbance ratios, and by visualization of
band patterns when ~1 µg of each sample was run in 1% agarose gel electrophoresis at
100 V. The sample was considered to be good quality when the most intense band was
present at ~1100 bp, with the second most intense band present at ~700 bp.
DNAse digestion was performed using the Ambion® Turbo DNA free (Life
Technologies Inc., Burlington, Ontario) kit and protocol. A total of 10 µg of RNA for
each sample was mixed with 5 µL of DNAse buffer and 1 µL of Turbo DNAse, mixed
and incubated for 25 minutes at 37oC in a water bath. Post-incubation, 5 µL of DNAse
inactivation buffer was added to the sample and incubated for 2 minutes at room
temperature, then centrifuged for 1.5 minutes at 10,000 RPM. The supernatant was
transferred to a new tube, and the concentration and quality of the RNA was determined
by applying 1 µL of the sample to the Nanodrop pedestal. Only samples with
142
absorbance ratios higher than 1.90 at 260/280 and 1.80 at 260/230 were used for cDNA
synthesis.
4.3.2.3 cDNA Transcription
Isolated RNA was transcribed to cDNA using the qScriptTM cDNA SuperMix. A
standard of 1 µg of RNA template was used in each reaction and incubated as per kit
instructions in a PCR cycler. Transcription of cDNA from RNA was confirmed by using 2
µL of the cDNA product as the nucleotide template in a PCR reaction using CG specific
primers and actin primers. The products were visualized via 1% agarose gel
electrophoresis, which was run for 1.25 hours at 100 volts.
4.3.2.4 Primer Design and PCR Amplification
CG primers were designed using PRIMER3 software
(http://frodo.wi.mit.edu/primer3) to amplify sections of the predicted coding region for
each of the CGs. Primers were designed to amplify sequences either between or within
predicted exons of CGs (Figure 4.1). The primers that produced the most intense and
distinct bands from genomic DNA were used for RNA expression analysis (Table 4.1).
PCR reactions consisted of 2.5 µl 10x PCR Buffer without MgCl2, 2.5 µl MgCl2, 1 µl 10
mM dNTP, 1 µl each for reverse and forward primers, 0.5 µl Jumpstart Taq Polymerase
(Sigma-Alderich Co.), 14.5 µl sterile distilled H2O and 2 µl DNA template for a total
reaction size of 25 µl. The PCR reaction cycling parameters were initial denaturation at
94oC for 1 minute, 25 cycles of denaturation (94oC for 30 seconds), annealing
(temperature dependent on primer, 30 seconds) and extension (72oC for 1 minute), a
final extension cycle for 10 minutes at 72oC and held at 4oC until gel electrophoresis.
PCR reaction products were loaded with a 100 bp ladder as size reference into a 1%
143
agarose 1x TBE gel stained with ethidium bromide and run at 100 volts for 1.5 hours in
1x TBE buffer. Visualization was performed using UV light.
144
Figure 4.1. Locations of RNA expression primers within CGs. For CG CBB2, yellow
arrows indicate the locations of reverse and forward primers. For CG CBB3, red arrows
indicate the locations of reverse and forward primers. For CG CBB4, green arrows indicate
the locations of reverse and forward primers. The red and yellow arrow indicates a
shared primer location between CBB2 and CBB3.
145
Table 4.1. Candidate common bacterial blight R gene primer sequences for real time quantitative RT-PCR. Expected genomic and CDS template product sizes and annealing locations within the CG sequences are indicated.
Target Gene
Primer Name
Reverse Sequence Forward Sequence Genomic Band Size
CDS Band Size
CG Location
CBB2
CBB2R1 CCTTAAACTAAGCCTTCACC GGCTCAACTACAATTTTCAC 1,627 bp - CDS2-CDS6
CBB2CS CCGAACGCTCTTTTAACTCG CGACTCATCCCTCAGGAAAC 1,635 bp - CDS2-CDS6
CBB3
CBB3R1 GGAAACACCTATTCAAGG GTTTATCACTACACCACTC 582 bp - CDS3-CDS4
CBB3CS CCGAACGCTCTTTTAACTCG TGCTCGATGAACTAGGCTCA 1,470 bp 719 bp CDS2-CDS5
CBB4
CBB4R3 CAACCTCCAACCACCTTAG GTTTTGCCACTTCTCAAG 1,503 bp - CDS3-CDS6
CBB4CS TATGTTCGAAGCTCGACCCT GCACTCTTGGGCCTACTCAG 2,662 bp 1,320 bp CDS1-CDS6
ACTIN
Act-R/F (Chen et al.
2008)
TTTCCTTGCTCATTCTGTCCG GAAGTTCTCTTCCAACCATCC - 180 bp -
146
4.4 Results
4.4.1 CG Expression
4.4.1.1 CBB Susceptible Genotype (Seaforth)
Initial RNA isolation and cDNA synthesis from Seaforth ground leaf samples from
the first experiment replication showed amplification of actin, CBB2, CBB3 and CBB4
for samples taken at 12HPI and 24HPI with primer sets CBB2R1, CBB3R1, CBB4R2
(Figure 4.2). Amplification of a 200bp band by actin primers was observed for both
water and Xap-inoculated cDNA as well as for the OAC Rex control, and there was no
amplification of actin from the water control (Figure 4.2). Amplification of a 550bp band
by the CBB2 primers was observed at 12 and 24HPI for Xap inoculated samples, but
not for water inoculated samples (Figure 4.2). Amplification of CBB2 was observed in
the OAC Rex genomic DNA control but not the water control (Figure 4.2). CBB3
primers amplified a 300 bp band from samples taken at both 12 and 24 HPI, when
inoculated by water and Xap98, as well as the OAC Rex genomic DNA (Figure 4.2).
There was no amplification from the water control (Figure 4.2). Amplification of a 200
bp band by CBB4 primers was observed in samples taken at 12 and 24 HPI when
inoculated by Xap98 and water (Figure 4.2). In the case of the water-inoculated 24 HPI
sample, the band was indistinct, and covered a larger range of sizes (100-200 bp). A
200 bp band was amplified from OAC Rex genomic DNA, but not the water control
(Figure 4.2).
When isolation of RNA and synthesis of cDNA was performed using leaf samples from
the first experiment replication for time points 0HPI, 48HPI, 72HPI, 96HPI, and 120 HPI,
no amplification of CGs CBB2, CBB3 and CBB4 was observed when
147
Figure 4.2. Initial CG expression in inoculated P. vulgaris leaves. Expression of CGs CBB2, CBB3 and CBB4, were compared to expression of actin check in resistant (OAC Rex) and susceptible (Seaforth) common bean varieties. The inoculum used was X. axonopodis pv. phaseoli isolate 98 (X) and sterile distilled water (C). RNA was isolated from leaf samples taken from water and Xanthomonas-inoculated OAC Rex and Seaforth plants at 12 (12HPI) and 24 (24HPI) hours post-inoculation. OAC Rex genomic DNA and sterile distilled water were used as positive (+) and negative (-) PCR controls, respectively. CG bands were produced using primers CBB2R1, CBB3R1 and CBB4R2 for CBB2, CBB3 and CBB4, respectively. Band size is indicated by a white arrow for actin, yellow arrow for CBB2, red arrow for CBB3 and green arrow for CBB4.
148
Figure 4.3. Subsequent CG expression in second experiment replication of P. vulgaris leaf inoculation. Expression of CGs CBB2, CBB3 and CBB4 were compared to expression of actin check in resistant (OAC Rex) and susceptible (Seaforth) common bean varieties. The inoculum used was X. axonopodis pv. phaseoli isolate 98 (X) and sterile distilled water (C). RNA was isolated from leaf samples taken from water and Xanthomonas-inoculated OAC Rex and Seaforth plants at 0, 12, 24, 36, and 48 hours post-inoculation (HPI). OAC Rex genomic DNA and sterile distilled water were used as positive (+) and negative (-) PCR controls, respectively. CG bands were produced using primers CBB2CS, CBB3CS and CBB4CS for CBB2, CBB3 and CBB4, respectively. Band size is indicated by a white arrow for actin, yellow arrow for CBB2, red arrow for CBB3 and green arrow for CBB4.
149
primers CBB2R1, CBB3R1 and CBB4R2 were used (data not shown). This was
consistent for both water and Xap- inoculated samples. Multiple repetitions of the RNA
isolation and cDNA synthesis procedures for 12 and 24 HPI samples from both the first
and second experiment replications produced no PCR no amplification of CGs CBB2,
CBB3 and CBB4 when primers CBB2R1, CBB3R1 and CBB4R2 were used (data not
shown). CG primers amplified bands of the previously observed size for CBB2 (550bp),
CBB3 (300bp) and CBB4 (200bp) from Seaforth genomic DNA (data not shown).
The bands produced by actin primers with cDNA and genomic DNA templates
were either of inconsistent intensity, or not present (data not shown). Therefore,
multiple repetitions of cDNA synthesis were performed using samples from all time
points from both experiments until consistent quality was obtained. The most consistent
cDNA quality was achieved when absorbance ratios above 1.90 (260/280) and 1.80
(260/340) were observed for isolated RNA post DNAse treatment. Consistency of
cDNA quality was identified by the presence of actin bands for all samples, although
variability in the intensity was still observed (data not shown).
To determine if primers from different locations within the CG sequence were
capable of amplifying bands from cDNA, new primers were designed (Table 4.1; Figure
4.1). Newly designed primers (CBB2CS, CBB3CS and CBB4CS) produced no
amplification of CGs from synthesized cDNA from samples taken at 0, 12, 24, 48, 72,
96, and 120 HPI for the first experiment replication (Appendix 11) and 0, 12, 24, 36, 48,
72, 96, 120, and 168 HPI for the second experiment replication (Figure 4.3, samples
from 0-48 HPI). These primers produced bands of the expected size for CBB2 (1,635
bp), CBB3 (1,470 bp) and CBB4 (2,662 bp) from Seaforth genomic DNA (Figure 4.3).
150
Amplification of actin was observed for all time points and inoculum types, as well as
Seaforth genomic DNA control, but no amplification was observed with the water control
(Figure 4.2-4.3).
4.4.1.2 CBB Resistant Genotype (OAC Rex)
Initial RNA isolation and cDNA synthesis from OAC Rex ground leaf samples
from the first replication showed amplification of actin, CBB3 and CBB4 for samples
taken at 12HPI and 24HPI with primer sets CBB2R1, CBB3R1, CBB4R2 (Figure 4.2).
Amplification of a 200bp band by actin primers was observed for both water and Xap-
inoculated cDNA as well as for the OAC Rex control, and there was no amplification of
actin from the water control (Figure 4.2). There was no amplification of a 550bp band
by the CBB2 primers at either the 12 or 24HPI for water and Xap-inoculated OAC Rex
leaf samples (Figure 4.2). Amplification of CBB2 was observed in the OAC Rex
genomic DNA control but not the water control (Figure 4.2). CBB3 primers amplified a
300 bp band from samples taken at both 12 and 24 HPI, when inoculated by Xap98, as
well as from the OAC Rex genomic DNA (Figure 4.2). There was faint amplification of a
300 bp band from the water inoculated sample at 24HPI, and no amplification at 12HPI
or from the water control (Figure 4.2). Amplification of a 200 bp band by CBB4 primers
was observed in samples taken at 12 and 24 HPI when inoculated by Xap98 as well as
the OAC Rex genomic DNA control (Figure 4.2). Water-inoculated samples and the
water control produced no observed amplification of the 200 bp band (Figure 4.2).
When isolation of RNA and synthesis of cDNA was performed using leaf samples
from the first experiment replication for time points 0HPI, 48HPI, 72HPI, 96HPI, and 120
HPI for OAC Rex leaf samples, no amplification of CGs CBB2, CBB3 and CBB4 was
151
observed when primer sets CBB2R1, CBB3R1, CBB4R2 were used (data not shown).
This was consistent for both water and Xap- inoculated samples. Repetition of RNA
isolation and cDNA synthesis for 12 and 24 HPI samples from both the first and second
replicates produced no PCR amplification of CGs CBB2, CBB3 and CBB4 with the
same primers (data not shown). CG primers amplified bands of the previously observed
size for CBB2 (550bp), CBB3 (300bp) and CBB4 (200bp) from OAC Rex genomic DNA
(data not shown).
The bands produced by actin primers with cDNA and genomic DNA templates
were either of inconsistent intensity, or not present (data not shown). Therefore,
multiple repetitions of cDNA synthesis were performed using samples from all time
points from both experiments until consistent quality was obtained. The most consistent
cDNA quality was achieved when absorbance ratios above 1.90 (260/280) and 1.80
(260/340) were observed for isolated RNA post DNAse treatment. Consistency of
cDNA quality was identified by the presence of actin bands for all samples, although
variability in the intensity was still observed (data not shown).
Since the CGs primers (CBB2R1, CBB3R1, and CBB4R3) were still unable to
amplify bands from the cDNA, new primers were designed (CBB2CS, CBB3CS and
CBB4CS) (Figure 4.1; Table 4.1). When new primers were used (CBB2CS, CBB3CS
and CBB4CS), no amplification was observed for all time points for both water and Xap-
inoculated leaves over both replicates (Appendix 11; Figure 4.3; Table 4.1). These
primers produced bands of the expected size for CBB2 (1,635 bp), CBB3 (1,470 bp)
and CBB4 (2,662 bp) from OAC Rex genomic DNA (Figure 4.3). Amplification of actin
was observed from OAC Rex cDNA samples at all time points and inoculation types, as
152
well as from OAC Rex genomic DNA, but no amplification was observed from water
control (Figure 4.3).
153
4.5 Discussion
4.5.1 Observed CG Expression
Despite initial results at 12 and 24 HPI suggesting that there were differences in
expression of candidate CBB CGs CBB2, CBB3 and CBB4 between resistant (OAC
Rex) and susceptible (Seaforth) varieties, these results could not be repeated both with
the initial (CBB2R1, CBB3R1, CBB4R2) and subsequent primers (CBB2CS, CBB3CS,
CBB4CS) (Figures 4.2-4.3). The inability of these primers to show CG expression may
be caused by the location of CGs. Since the design and use of the primers used in this
experiment (Table 4.1), predictions for exon locations within CBB2, CBB3 and CBB4
have changed, based on the same program used previously to identify exons
(FgeneSH). This re-analysis also caused the incorporation of a previously disregarded
CG (CBB1) into bioinformatics analyses due to improved gene feature prediction (see
Chapter 2). It was also shown that the contig1701 sequence was not continuous, which
resulted in the ~20 kb sequence where CBB3 was predicted to be discarded (see
Chapter 2).
In the case of primers CBB2R1, CBB2CS, CBB3R1 and CBB4R3, one of the pair
of primers is located outside of predicted coding regions, which is the likely cause of the
inability to amplify from cDNA (Figure 4.1). This corresponds to the observed
differences between expected and actual band sizes produced (Figure 4.2). The initial
bands produced by CBB2R1 (~550 bp), CBB3R1 (~300 bp) and CBB4R3 (~170 bp)
were the same regardless of whether cDNA or genomic DNA were used. These bands
were also significantly smaller than the than the expected genomic DNA size (Figure
154
4.2; Table 4.1). This indicates the likelihood that the initial results were produced by
DNA contamination, and that the primers were amplifying an unexpected target.
It is also important to note that the both primer sets designed for CBB2 have at
least one primer located outside the exon (Figure 4.2). Consequently, these primers
would not successfully indicate the presence of CBB2 coding sequence within the
synthesized cDNA (Table 4.1). This raises the possibility that although current results
indicate that CBB3 and CBB4 are not expressed as a result of Xap inoculation, CBB2
may have been expressed, but the designed primers lacked the ability to show this.
4.5.2 Expected CG Expression Patterns
Disease resistance gene expression patterns have been previously characterized
in multiple plants and in different plant-pathogen models, with examples including
common bean, coffee, orange, Arabidopsis and tobacco (Anderson et al. 2004; Ganesh
et al. 2005; Ahn et al. 2011; Borges et al. 2012; Rodríguez et al. 2014). Expression
patterns can take a variety of forms and may be different depending on the plant, tissue,
pathogen and genes involved as was evidenced by the study performed by Borges et
al. (2012). Different expression patterns were observed for multiple genes in the 96 HPI
with Colletotrichum lindemuthianum (anthracnose). These responses to pathogen
recognition include constant expression (PR16a), up-regulation from low expression
(PR2), rapid induction of unexpressed genes (PR1b), and down-regulation (PGIP).
Another example of resistance gene expression patterns includes the measurement of
PAL in P. vulgaris inoculated with the same pathogen, C. lindemuthianum (Fraire-
Velázquez and Lozoya-Gloria 2003). In the resistant reaction, PAL expression was
strong for the first 2 HPI, decreased until 16 HPI and then increased more significantly.
155
Large scale mRNA expression profiling performed by Tao et al. (2003),
demonstrated that in the Arabidopsis-Pseudomonas syringae patho-system, increased
gene expression of ~ 2000 genes occurred at 6-9 HPI in the resistant interaction as
opposed to 30 HPI in the susceptible one. Although the CBB resistant source for OAC
Rex, P. acutifolius accession (P1440795), exhibits a hypersensitive response to CBB
(Parker 1985; Drijfhout and Blok 1987), the response to CBB in OAC Rex is
characterized by an increased time to development of CBB symptoms, and decreased
severity of symptoms. Considering that the resistant reaction in OAC Rex causes
retardation in disease progression and not complete immunity, it is hypothesized that
this is due to slower pathogen recognition and/or response. Based on this hypothesis, it
is therefore expected that the R gene(s) involved would be expressed less strongly or at
a later time post-inoculation when compared to the same response in P. acutifolius.
156
4.6 Conclusion
This study aimed to observe three candidate CBB resistance genes for changes
in their expression over time in common bean when resistant (OAC Rex) and
susceptible (OAC Seaforth) varieties were inoculated with either water or Xap.
Expression of the CGs was not observed within the parameters of the experiment.
Further studies of these CGs and further identification and testing of CGs in the area of
the PV-ctt001 QTL region will help to progress current knowledge about the
mechanisms for CBB resistance and the genes involved.
157
Chapter 5: Future Directions and Recommendations
5.1 OAC Rex Genome Sequence Assembly
Since a location within the OAC Rex genome has not been identified for
contig1701, it is important to continue to search for this. This is highly dependent on the
completion of the full OAC Rex genome sequence. The scaffolds and contigs identified
in BLAST searches discussed above have yet to be included in the pseudochromosome
assembly, making it difficult to identify the location and surrounding region of the
candidate genes reported in this study. Once a location for the candidate genes is
determined, it will be possible to explore further their position relative to the PV-ctt001
marker as well as other markers and disease resistance genes in the surrounding area.
Despite the possibility that this marker was associated to CBB resistance as the result
of a false positive (see Chapter 1), the marker provides a targeted region to look at
genome details such as the repetitive nature surrounding identified disease resistance
genes.
5.2 Candidate CBB R Gene Analysis
5.2.1 Identification and Characterization of New CGs
The evidence indicating the possible retrotransposon characteristics of candidate
genes CBB1-4 (see Chapter 2), and the lack of candidate gene expression (see
Chapter 3) suggest that identification of new candidate genes would further the aims of
identifying CBB resistance genes more effectively. Several potential locations for the
identification of candidate resistance genes exist, including the sequence in the regions
surrounding CBB resistance markers that was analyzed by Perry et al. (2013).
158
The sequence characterized by Perry et al. (2013) surrounding CBB resistance
QTLs PV-ctt001 (Chromosome 4), SU91 (Chromosome 8) and SAP6 (Chromosome 10)
provide a source for identification of additional candidate resistance genes based on
predicted function. A total of 114 genes reported within 5 OAC Rex contigs that
matched to the PV-ctt001 region of chromosome 4. Of the identified genes, several
categories have potential as the source of disease resistance, including
defense/signalling/stress (21.9%), unknown (7.9%) and hypothetical (27.5%) genes.
The defense/signalling/stress gene predictions especially would be an excellent target
group, considering the large percent of the predicted genes it comprises, as well as the
fact that they are easily comparable to previously characterized genes. Testing of
multiple candidate genes identified in the region surrounding PV-ctt001 to observe
expression changes could be performed by real time PCR. Alternatively, genome wide
gene expression observations could be performed using RNAseq.
In a previous study, Shi et al. (2012) identified 16 candidate genes associated
with CBB resistance marker SU91, which is present in OAC Rex Pv08, to test for
increased marker precision. Although two candidate gene markers were reported to
have improved association to CBB resistance, this was only related to disease ratings,
and not gene expression. The use of these candidate gene markers in RNA expression
studies would have more power in confirming the involvement of the associated
candidate resistance genes in resistance to CBB. An interesting line of inquiry could
explore candidate resistance gene expression identified in both the PV-ctt001 and SU91
QTL regions.
159
5.2.2 CG Expression Analysis
The inclusion of additional collection time points and tissue sources would
increase the ability to make observations about candidate gene expression patterns.
Multiple studies have shown the first 24 hours post-inoculation to be a critical period for
the induction of disease resistance-related genes, with peaks of induction occurring at a
variety of different time points within that critical period (Fraire-Velázquez and Lozoya-
Gloria 2003; Tao et al. 2003; Ahn et al. 2011; Borges et al. 2012), However, the
expected increased time to resistance gene induction, for the reasons discussed above,
suggests that sample collection after a longer time period (perhaps up to 36 HPI), with
higher frequency (perhaps every 2-6 hours) would provide the best coverage and
increase the likelihood of detecting changes in expression.
5.3 Model Plant CBB Inoculation Procedure
Disease progression was shown in Xap-inoculated Arabidopsis leaves (see
Chapter 3), showing that Arabidopsis is a host when manually inoculated. However,
repetitions of the initial experiment have been unsuccessful. It is therefore imperative
that the study be repeated, to decrease variability and improve the power of any
conclusions made. Since the subsequent repetitions used only isolate Xap12, which
was shown to be a less virulent isolate, future replications should use Xap18, which
produced the highest symptoms and CFU count in Arabidopsis. Future inoculations of
detached leaves should also be performed using a mixture of the inoculation method
described (see Chapter 3), and the infiltration method used by Randhawa and Civerolo
(1985) in peach. The use of a mixture of isolates as an additional inoculum to compare
to inoculation with a single isolate (i.e. Xap18) would also indicate whether a mixture of
160
effectors contributed from the four isolates is what is required for non-host resistance to
be overcome.
161
Chapter 6: Summary
Disease susceptibility is one of the primary limitations to yield for all plant species
produced across the globe. One of the major diseases affecting common bean (P.
vulgaris L.) yield quantity and quality is the disease CBB, caused by bacteria pathogen
Xap and its fuscans variant Xff. The resistant variety OAC Rex provides reduced
disease symptoms and increased yield under disease pressure (Michaels et al. 2006;
Gillard et al. 2009). The source of its resistance is a wild relative P. acutifolius (tepary
bean) accession P1440795 (Parker 1985). Although resistance QTLs have been
identified and associated with markers in OAC Rex, such as PV-ctt001 (Tar’an et al.
2001; Perry, 2010; Perry et al. 2013) and SU91 (Perry et al. 2013), no resistance genes
have been identified to date. It is important to determine the genes involved in
resistance to CBB to increase the current understanding of the resistance reaction, and
also to improve selection capabilities for breeding new resistant varieties.
The current study aimed to identify candidate CBB resistance genes within
contigs for BAC clone Rex021F10 of OAC Rex selected with the PV-ctt001marker, and
test them in a variety of ways. The characterization of genes identified through
homology to previously reported candidate genes revealed that retrotransposon
elements comprised a high proportion of the sequence of the selected contig sequences
(contig1701 and contig1455). Retrotransposons integrate most often in genic regions
(Miyao et al. 2003; Le et al. 2007), and have been shown to interact with resistance
genes by disrupting gene function (Song et al. 1997; Hernández-Pinzón et al. 2009),
causing chimeric proteins (Kashkush et al. 2003; Frost et al. 2004) changing promoter
162
function and modifying the epigenetome (Hayashi et al. 2009; McDowell and Meyers,
2013; Tsuchiya and Eulgem, 2013). Characterization of the identified candidate genes
revealed retrotransposon features including similarity to GAG/POL poly proteins,
reverse transcriptases, and Gypsy/Ty-3 retro-element proteins. Although the similarities
to these proteins were not high (30-47%), when combined with the presence of multiple
other retrotransposons identified within the same contig indicates the likelihood the CGs
are retrotransposons. The presence of several genes in the associated contig
sequence with potential disease resistance functions (i.e ascorbate oxidase, callose
synthase, hypothetical protein), provides additional areas for testing additional
candidate CBB resistance genes.
Candidate CBB resistance gene expression was tested in susceptible and
resistant common bean genotypes. However, no gene expression was observed in
cDNA at multiple time points for candidate genes CBB2-CBB4. This could be due to
human error during primer design. However, the subsequent characterization of the
candidate genes as retrotransposons indicates that expression is not likely to be
measured, even with experimental parameter alterations. A more promising target is
the putative ascorbate oxidase gene identified in contig1701, since this gene family has
previously been shown to be involved in regulating reactive oxygen species levels,
which are associated with stress and disease resistance responses (Pavet et al. 2005;
Pignocchi et al. 2006; Sanmartin et al. 2007; Fotopoulos et al. 2008).
Since genetic manipulation of common bean is difficult (i.e. genetic
transformation), testing candidate CBB resistance gene function within resistant
common bean genotypes is an unattractive option. The development of a detached leaf
163
A. thaliana Xap-inoculation method was aimed at providing an alternative method of
testing candidate gene function in a susceptible model. Although optimization is still
required, symptom progression was shown in the model plant, and provides a more
controlled environment to test candidate genes in a more targeted way.
164
8.0 References
Abedon, B. G. and Tracy, W. F. 1996. Corngrass 1 of maize (Zea mays L. delays development of adult plant resistace to common rust (Puccinia sorghi Schw.) and European corn borer (Ostrinia nuvilalis Hubner). J. of Heredity. 87: 219-223
Aggour, A.R., Coyne, D.P. and Vidaver, A.K. 1989. Comparison of leaf and pod disease reactions of beans (Phaseolus vulgaris L.) inoculated by different methods with strains of Xanthomonas campestris pv. phaseoli (Smith) dye. Euph. 43: 143-152
Agriculture and Agri-Food Canada. 2011. Canada: Pulse and special crops outlook. Obtained Aug 23 2011 from World Wide Web: http://www.agr.gc.ca/pol/mad-dam/index_e.php?s1=pubs&s2=spec&s3=php&page=spec_2011-07-05
Health Canada. 2014. Canada’s Food Guide. Obtained December 9 2014 from World Wide Web: http://www.hc-sc.gc.ca/fn-an/food-guide-aliment/choose-choix/meat-viande/index-eng.php
Agrios, G.N. 2005. Chapter six. How plants defend themselves against pathogens. In 5th Ed. Plant Pathology. Elsevier Academic Press. Burlington, MA, USA
Ahn, E.-R., Sarowar, S., Jeon, Y., Pai, H.-S. 2011. Molecular characterization of NLP function in Nicotiana benthamiana. J. Plant Biol. 54: 199-208
Alghisi, P. and Favaron, F. 1995. Pectic degrading enzymes and plant parasite interactions. Eur. J. Plant Pathol. 101: 365-375
Ameline-Torregrosa, C., Wang, B.-B., O’Bleness, M.S., Deshpande, S., Zhu, H., Roe, B., Young, N.D., and Cannon, S.B. 2008. Identification and characterization of nucleotide-binding site-leucine-rich repeat genes in the model plant Medicago truncatula. Plant Physiol. 146(1): 5-21
Anderson, P.A., Lawrence, G.J., Morrish, B.C., Ayliffe, M.A., Finnegan, E.J. and Ellis, J.G. 1997. Inactivation of the flax rust resistance gene M associated with loss of a repeated unit within the leucine-rich repeat coding region. Plant Cell. 9(4): 641-651
165
Anderson, J.P., Badruzsaufari, E., Schenk, P.M., Manners, J.M., Desmond, O.J., Ehlert, C., Maclean, D.J., Ebert, P.R. and Kazan, K. 2004. Antagonistic interaction between abscisic acid and jasmonate-ethylene signaling pathways modulates defense gene expression and disease resistance in Arabidopsis. Plant Cell. 16: 3460-3479
Arnold K, Bordoli L, Kopp J, and Schwede T. 2006. The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics. 22:195-201
Asai, T., Tena, G., Plotnikova, J., Willmann, M.R., Chiu, W.-L., Gomez-Gomez, L., Boller, T., Ausubel, F.M. and Sheen, J. 2002. MAP kinase signalling cascade in Arabidopsis innate immunity. Nature. 415:977-983
Bakker, E.G., Toomajian, C., Kreitman, M. and Bergelson. 2006. A genome-wide survey of R gen polymorphisms in Arabidopsis. Plant Cell. 18(8):1803-1818
Bernoux, M., Ve, T., Williams, S., Warren, C., Hatters, D., Valkow, E., Zhang, X., Ellis, J. G., Kobe, B. and Dodds, P. N. 2011. Structural and functional analysis of a plant resistance protein TIR domain reveals interfaces for self-association, signaling and autoregulation. Cell Host Microbe. 9(3): 200-211
Bewley, J.D., Black, M. and Halmer, P. 2006. The encyclopedia of seeds: Science, technology and uses. CAB International 875 Massachusetts Ave., Cambridge MA, USA. pg 35-36
Bitocchi, E., Nanni, L., Bellucci, E., Rossi, M., Giardini, A., Spagnoletti Zeuli, P., Logozzo, G., Stougaard, J., McClean, P., Attene, G., and Papa, R. 2012. Mesoamerican origin of the common bean (Phaseolus vulgaris L.) is revealed by sequence data. PNAS. www.pnas.org/cgi/doi/10.1073/pnas.1108973109
Blair, M. W., Pedraza, F., Buendia, H. F., Gaitán-Solís, E., Beebe, S. E. and Tohme, J. 2003. Development of a genome-wide anchored microsatellite map for common bean (Phaseolus vulgaris L.). Theor. Appl. Genet. 107:1362-1374
Block, A., Guangyong, L., Fu, Z. Q. and Alfano, J. R. 2008. Phytopathogen type III effector weaponry and their plant targets. Curr. Opin. Plant Biol. 11: 396-403
166
Bogdanove, A.J., Koebnik, R., Lu, H., Furutani, A., Angiuoli, S.V., Patil, P.B., Van Sluys, M.-A., Ryan, R.P, Meyer, D.F., Han, S.-W., Aparna, G., Rajaram, M., Delcher, A.L., Phillippy, A.M., Puiu, D., Schatz, M.C., Shumway, M., Sommer, D.D., Trapnell, C., Benahmed, F., Dimitrov, G., Madupu, R., Radune, D., Sullivan, S., Jha, G., Ishihara, H., Lee, S.-W., Pandey, A., Sharma, V., Sriariyanun, M., Szurek, Vera-Cruz, C.M., Dorman, K.S., Ronald, P.C., Verdier, V., Dow, J.M., Sonti, R.V., Tsuge, S., Brednel, V.P., Rabinowicz, P.D., Leach, J.E., White, F.F. and Salzberg, S.L. 2011. Two new complete genome sequences offer insight into host and tissue specificity of plant pathogenic Xanthomonas spp. J. Bacteriol. 193(19):5450
Bollini, R. and Chrispeels, M. J. 1978. Characterization and subcellular localization of
vicilin and phytohemagglutinin, the two major reserve proteins of Phaseolus vulgaris L. - Planta 142: 291–298.
Bollini, R., Van der Wilden, W., and Chrispeels, M.J. 1982. A precursor of the reserve-protein, phaseolin, is transiently associated with the endoplasmic reticulum of developing Phaseolus vulgaris cotyledons. Physiologia Plantarum. 55: 82-92
Bonas, Ul, Schulte, R., Fenselau, S, Minsavage, G. V., Staskawcz,j B. J. and Stall, R. E. 1990.
Borges, A., Melotto, M., Tsai, S. M., and Gregorio Gomes Caldas, D. 2012. Changes in spatial and temporal gene expression during incompatible interaction between common bean and anthracnose pathogen. J. Plant Physiol. 169:1216-1220
Botella, M. A., Parker, J. E., Frost, L. N., Bittner-Eddy, P. D., Beynon, J. L., Daniels, M. J., Holub, E. B. and Jones, J. D. G. 1998. Three genes of the Arabidopsis RPP1 complex resistance locus recognize distinct Peronospora parasitica avirulence determinants. Plant Cell 10: 1847-1860
Bressani, R. 1983. Research needs to upgrade the nutritional quality of common beans (Phaseolus vulgaris). Qualitas Plantarum Plant foods Human Nutrition. 32: 101-110
Campa, A., Giraldez, R. and Ferreira, J. J. 2011. Genetic analysis of the resistance to eight anthracnose races in the common bean differential cultivar Kaboon. Pytopath. 101(6):757-764
167
Century, K. S., Lagman, R. A., Adkisson, M., Morlan, J., Tobias, R., Schwartz, K., Smith, A., Love, J., Ronald, P. C., and Whalen, M. C. 1999. Developmental control of Xa21-mediated disease resistance in rice. Plant Journal. 20(2): 231-236
Chan SL, Mukasa T, Santelli E, Low LY and Pascual J. 2010. The crystal structure of a TIR domain from Arabidopsis thaliana reveals a conserved helical region unique to plants. Protein Sci. 19:155–161
Chang, J.H., Tai, Y.S., Bernal, A.J., Lavelle, D.T., Staskawicz, B.J., and Michelmore, R.W. 2002. Functional analyses of the pto resistance gene family in tomato and the identification of a minor resistance determinant in a susceptible haplotype. Mol. Plant-Microbe Interact. 15:281-291
Chen, X., Steed, A., Harden, C. and Nicholson, P. 2006. Characterization of Arabidopsis thaliana-Fusarium graminearum interactions and identification of variation in resistance among ecotypes. Mol Plant Pathol. 7(5):391-403
Chen, Q., Han, Z., Jiang, H., Tian, D. & Yang, S. 2010b. Strong positive selection drives rapid diversification of R-Genes in Arabidopsis relatives. J Mol Evol. 70: 137-148
Chinchilla, D., Bauer, Z., Regenass, N., Boller, T. and Felix, G. 2006. The Arabidopsis receptor kinase FLS2 binds flg22 and determines the specificity of flagellin perception. Plant Cell. 18: 465-476
Chinchilla, D., Zipfel, C., Robatzek, S., Kemmerling, B., Nüremberger, T., Jones, J.D.G., Felix, G. and Boller, T. 2007. A flagellin-induced complex of the receptor FLS2 and BAK1 initiates plant defence. Nature. 448: 497-500
Collmer, A.. and Keen, N. T. 1986. The role of pectic enzymes in plant pathogenesis. Annu Rev. Phytopathol. 24: 383-409
Cook, B. J., Clay, R. P., Bergmann, C. W., Albersheim, P. and Darvill, A. G. 1999. Fungal polygalacturonases exhibit different substrate degradation patterns and differ in their susceptibilities to polygalacturonase-inhibiting proteins
Córdoba, J. M., Chavarro, C., Schlueter, J. A., Jackson, S. A. and Blair, M. W. 2010. Integration of physical and genetic maps of common bean through BAC-derived microsatellite markers. BMC Gen. 11: 436
168
Dangl, J. L. and Jones, J. D. G. 2001. Plant pathogens and integrated defence responses to infection. Nature. 411: 826-833
Darrasse, A., Bureau, C., Samson, R., Morris, C. E. and Jacques, M.-A. 2007. Contamination of bean seeds by Xanthomonas axonopodis pv. phaseoli associated with low bacterial densities in the phyllosphere under field and greenhouse conditions. Eur. J. Plant Pathol. 119: 203-215
David, P., Chen, N.W.G., Pedrosa-Harrand, A., Thareau, V., Sévignac, M., Cannon, S. B., Debouck, D., Langin, T., and Geffroy, V. 2009. A nomadic subtelomeric disease resistance gene cluster in common bean. Plant Physiol. 151(3): 1048-1065
Debouck, D. G., Rubiano, H. and del Carmen Menéndez, M. S. 1988. Determinate climbers among Argentinean materials of Phaseolus vulgaris L. Ann. Rep. Bean Improv. Coop. 31:189-190
Debouck, D., G., Toro, O., Paredes, O. M., Johnson, W. C. and Gepts, P. 1993. Genetic diversity and ecological distribution of Phaseolus vulgaris in northwestern South America. Econ Bot. 47:408-423
De Lorenzo, G., D’Ovidio, R. and Cervone, F. 2001. The role of polygalacturonase-inhibiting proteins (PGIPs) in defense against pathogenic fungi. Annu. Rev. Phytopath. 39:313-335
De Lorenzo, G. and Ferrari, S. 2002. Polygalacturonase-inhibiting proteins in defense against phytopathogenic fungi. Curr. Opin. Plant Biol. 5: 295-299
Desaki, Y., Miya, A., Venkatesh, B., Tsuyumu, S., Yamane, H., Kaku, H., Minami, E., and Shibuya, N. 2006. Bacterial lipopolysaccharides induce defense responses associated with programmed cell death in rice cells. Plant Cell Physiol. 47(11): 1530-1540
Desiderio, A., Aracri, B., Leckie, F., Mattei, B., Salvi, G., Tigelaar, H., Van Roekel, J.S., Baulcombe, D.C., Melchers, L.S., De Lorenzo, G. and Cervone, F. 1997 Polygalacturonase-inhibiting proteins (PGIPs) with different specificities are expressed in Phaseolus vulgaris. Mol Plant Microbe Interact. 10: 852–860
169
Develey-Rivière, M.-P. and Galiana, E. 2007. Resistance to pathogens and host developmental stage: A multifaceted relationship within the plant kingdom. New Phytol. 175(3):405-416
de Wit, P. J., Brandwagt, B. F., van den Burg, H.A., Cai, X., van der Hoorn, R. A., de Jong, C. F., van Klooster, J., de Kock, M. J., Krujit, M, Lindhout, W. H., Luderer, R., Takken, F. L., Westerink, N., Vervoort, J. J., Joosten, M. H. 2002.The molecular basis of co-evolution between Cladosporium fulvum and tomato. Antonie Van Leeuwenhoek. 81: 409-412
Di Matteo, A., Federici, L., Mattei B., Salvi, G., Johnson, K. A., Savino, C., De Lorenzo, G., Tsernoglou, D. and Cervone, F. 2003. The crystal structure of polygalacturonase-inhibiting protein (PGIP), a leucine-rich repeat protein involved in plant defense. PNAS. 100 (17): 10124-10128
Dodds,P.N., Lawrence,G.J. and Ellis,J.G. 2001. Six amino acid changes confined to the leucine-rich repeat b-strand/b-turn motif determine the difference between the P and P2 rust resistance specificities in flax. Plant Cell. 13: 163-178
Dorey, S., Baillieul, F., Pierrel, M.-A., Saindrenan, P., Fritig, B. and Kauffmann, S. 1997. Spatial and temporal induction of cell death, defense genes and accumulation of salicylic acid in tobacco leaves reacting hypersensitively to a fungal glycoprotein elicitor. MPMI. 10(5): 646-655
Dow, J. M., Clarke, B. R., Milligan, D. E., Tang, J.-L. and Daniels, M. J. 1990. Extracellular proteases from Xanthomonas campestris pv. campestris, the black rot pathogen. App. Env. Micro. 56 (10): 2994-2998
Drijfhout, E. and Blok, W.J. 1987. Inheritance of resistance to Xanthomonas campestris pv. phaseoli in tepary bean (Phaseolus acutifolius). Euphytica 36:803-808
Duncan, R.W., Singh, S.P. and Gilbertson, R.L. 2010. Interaction of common bacterial blight bacteria with disease resistance quantitative trait loci in common bean. Phytopathol.101(4): doi:10.1094/PHYTO-03-10-0095
Durham, K. M., Xie, W., Kangfu, Y., Pauls, K. P., Lee, E. and Navabi, A. 2013. Interaction of common bacterial blight quantitative trait loci in a resistant inter-cross population of common bean. Plant Breeding. Doi10.1111/pbr.12103
170
Ellendorff, U., Zhang, Z. and Thomma, B.P.H.J. 2008. Gene silencing to investigate the roles of receptor-like proteins in Arabidopsis. Plant Sign. Behav. 3(10):893-896
Ellis, J. G., Lawrence, G. J., Luck, J. E. and Dodds, P. N. 1999. Identification of regions of alleles of the flax rust resistance gene L that determine differences in gene-for-gene specificity. Pl Cell. 11: 495-506
Ellis, J., Dodds, P., Pryor, T. 2000. Structure, function and evolution of plant disease resistance genes. Curr. Opin. Plant Biol. 3: 278-284
Fabro, G., Steinbrenner, J., Coates, M., Ishaque, N., Baxter, L., Studholme, D. J., Körner, Allen, R. L., Piquerez, S. J. M., Cardoso-Rougon, A., Greenshields, D., Lei, R., Badel, J. L., Caillaud, M.-C., Sohn, K.-H., van den Acherveken, G., Parker, J. E., Beynon, J., and Jones, J. D. G. 2011. Multiple candidate effectors from the oomycete pathogen Hyaloperonospora arabidopsidis supress host plant immunity. PLOS Pathogens. 7(11): e1002348
Federici, L. Di Matteo, A., Fernandez-Recio, J., Tsernoglou, D. and Cervone, F. 2006. Polygalacturonase inhibiting proteins: players in plant innate immunity?. Trends in Plant Sci. 11:
Felix, G., Duran, J. D., Volko, S. and Boller. 1999. Plants have a sensitive perception system for the most conserved domain of bacterial flagellin. Plant J. 18(3): 265-276
Ferreira, J. J., Campa, A., and Kelly, J. D. 2013. Chapter 9: Organization of conferring resistance to anthracnose in common bean. Ed. Varshney, R. K. and Tuberosa, R. in Translational Genomics for Crop Breeding
Ferrier-Cana, E., Geffroy, V., Macadré, C., Creusot, F., Imbert-Bolloré, P., Sévignac, M. and Langin, R. 2003. Characterization of expressed NBS-LRR resistance gene candidates from common bean. Theor. Appl. Genet. 106:251-261
Finnegan, D. J. 1989. Eukaryotic transposable elements and genome evolution. Trends Genet. 5 (4): 103-107
Fotopoulos, V., De Tullio, M.C., Barnes, J. and Kanellis, A.K. 2008. Altered stomatal dynamics in ascorbate oxidase over-expressing tobacco plants suggest a role for dehydroascorbate signalling. J. Exp. Bot. 59(4): 729-737
171
Fourie, D. and Herselman, L. Pathogenic and genetic variation in Xanthomonas axonopodis pv. phaseoli and its fuscans variant in Southern Africa. African Crop Sci. 19(4): 393-407
Fraire-Velázquez, S. and Lozoya-Gloria, E. 2003. Differential early gene expression in Phaseolus vulgaris to Mexican isolates of Colletotrichum lindemuthianum in incompatible and compatible interactions. Phys Mol Plant Pathol. 63: 79-89
Frost, D., Way, H., Howles, P., Luck, J., Manners, J., Hardham, A., Finnegan, J. and Ellis, J. 2004. Tobacco transgenic for the flax rust resistance gene L expresses allel-specific activation of defense responses. Mol Plant Microbe Interact. 17: 224-232
Fu, D., Uauy, C., Distelfeld, A., Blechl, A., Epstein, L., Chen, X., Sela, H., Fahima, T., Dubcovsky, J. 2009. A kinase-START gene confers temperature-dependent resistance to wheat stripe rust. Science 323: 1357-1360
Gabriel, D.W., Kingsley, M.T., Hunter, J.E., Gottwyld, T. 1989. Reinstatement of Xanthomonas citri and X. phaseoli to species and reclassification of all X. campestris pv. citri strains. Int. J. Syst. Bacteriol. 39:14-22
Ganesh, D., Petitot, A.-S., Silva, M. C., Alary, R., Lecouls, A.-C. and Fernandez, D. 2006. Monitoring of the early molecular resistance responses of coffee (Coffea arabica L.) to the rust fungus (Hemileia vastatrix) using real-time quantitative RT-PCR. Plant Sci. 170:1045-1051
Geffroy, V., Sicard, D., De Oliviera, J.C.F., Sevignac, M., Cohen, S., Gepts, P., Neema, C., Langin, T. and Dron, M. 1999. Identification of an ancestral resistance gene cluster involved in the coevolution process between Phaseolus vulgaris and its fungal pathogen Colletotrichum lindemuthianum. Mol. Plant Microbe Interact. 12:774-784
Geffroy, V., Sévignac, M., De Oliviera, J. C. F., Skroch, P., Toquet, P., Gepts, P., Langin, T and Dron, M. 2000. Inheritance of partial resistance against Colletotrichum lindemuthianum in Phaseolus vulgaris and co-localization of QTLs with genes involved in specific resistance. Mol Plant-Microbe Interact. 13:287-296
172
Gepts, P., Aragão,F. J. L., de Barros, E., Blair, M. W., Brondani, R., Broughton, W., Galasso, I., Hernández, G., Kami, J., Lariguet, P., McClean, P., Melotto, M., Miklas, P., Pauls, P., Pedrosa-Harand, A., Porch, T., Sánchez, F., Sparvoli, F. and Yu, K. 2008. 5.1.1 “Economic, agronomic, and societal importance of phaseolus beans” in Genomics of Tropical Crop Plants edited by Moore, P. H. and Ming, R. Springer Science + Business Media, LLC, 233 Spring Street, New York, NY 10013, USA
Gepts, P. and Debouck, D. 1991. Origin, domestication and evolution of the common bean (Phaseolus vulgaris L.). In: van Schoonhoven, A. and Voysest, O. (Editors) Common beans: research for crop improvement. Wallingford/Colombia: CAB International/CIAT, pp 7-53.
Gepts, P. 1988. Phaseolin as an evolutionary marker. In ‘Genetic resources of Phaseolus beans’. (Ed. P Gepts) pp. 215-241. Kluwer Academic Publishers: Dordrecht, the Netherlands
Gepts, P. and Bliss F. A. 1986. Phaseolin variability among wild and cultivated common beans (Phaseolus vulgaris) from Columbia. Economic Botany. 40: 469-478
Gepts, P. and Bliss, F. A. 1984. Enhanced available methionine concentration associated with higher phaseolin levels in common bean seeds. Theor Appl. Genet. 69:47-53
Gillard, C.L., Conner, R.L., Howard R.J., Pauls, K.P., Shaw L. and Tar’an, B. 2009. The performance of dry bean cultivars with and without common bacterial blight resistance in field studies across Canada. Can J. Plant Sci. 89: 405-416
Glazebrook. J. 2005. Contrasting mechanisms of defense against biotrophic and necrotrohic pathogens. Annu Rev Phytopath. 43:205-227
Glémin, S. and Bataillon, T. 2009. A comparative view of the evolution of grasses under domestication. New Pytol. 183(2): 273-290
Gómez-Gómez, L., Felix, G. and Boller, T. 1999. A single locus determines sensitivity to bacterial flagellin in Arabidopsis thaliana. Plant J. 18(3): 277-284
Gómez-Gómez, L. and Boller, T. 2000. FLS2: An LRR receptor–like kinase involved in the perception of the bacterial elicitor flagellin in Arabidopsis. Cell Press.
173
Gómez-Gómez, L. and Boller, T. 2002. Flagellin perception: A paradigm for innate immunity. Trends in Pl Sci. 7(6): 251-256
Goodwin, M. 2005. Crop profile for dry bean in Canada. Agriculture and Agri-Food Canada
Goritschnig, S., Krasileva, K. V., Dahlbeck, D. and Staskawicz, B. J. 2012. Computational prediction and molecular characterization of an oomycete effector and the cognate Arabidopsis resistance gene. PLOS Genet. 8(2): e1002502
Gos, G., Slotte, T. and Wright, S. I. 2012.Signatures of balancing selection are maintained at disease resitance loci following mating system evolution and a population bottleneck in the genus Capsella. BMC Evol. Biol. 12:152
Graham, M., A., Marek, L.F., and Shoemaker, R.C. 2002. Organization, expression and evolution of a disease resistance gene cluster in soybean. Genet. 162: 1961-1977
Gunn, N., Byrne, J. and Holub E. B. 2002. Outcrossing of two homothallic isolates of Peronospora parasitica and segregation of avirulence matching six resistance loci in Arabidopsis thaliana. In Advances in Downy Mildew Research. Ed. Spencer-Phillips, P. T. N., Gisi, U. and Lebeda A. 185-188. Springer, Netherlands
Gupta, Y.P. 1987. Anti-nutritional and toxic factors in food legumes: a review. Plant Foods Hum Nutr. 37:201-228
Gutierrez, J.R., Balmuth, A.L., Ntoukakis, V., Mucyn, T.S., Gimenez-Ibanez, S., Jones, A. M.E. and Rathjen, J.P. 2009. Prf immune complexes of tomato are oligomeric and contain multiple Pto-like kinases that diversify effector recognition. Plant J. 61(3): 507-518
Hayashi, K. and Yoshida, H. 2009. Refunctionalization of the ancient rice blast disease resistance gene Pit by the recruitment of a retrotransposon. Plant J. 57:413-425
Hayward, A.C.1993. 1 The hosts of Xanthomonas, in Xanthomonas edited by Swing, J.G. and Civerolo, E.L., Chapman & Hall, 2-6 Boundary Row, London SE1 8HN, UK
174
Hernández-Pinzón, I., de Jesús, E., Santiago, N. and Casacuberta, J.M. 2009. The frequent transcriptional readthrough of the tobacco Tnt1 retrotransposon and its possible implications for the control of resistance genes. J. Mol. Evol. 68(3): 269-278
Huang, Q and Allen, C. 2000. Polygalacturonases are required for rapid colonization and full virulence of Ralstonia solanacereaum on tomato plants. Physiol. Mol. Plant Pathol. 57:77-83
Huard-Chauveau, C., Perchepied, L., Debieu, M., Rivas, S., Kroj, T., Kars, I., Bergelson, J., Roux, F. and Roby, D. 2013. An atypical kinase under balancing selection confers broad-spectrum disease resistance in Arabidopsis. PLoS Genet 9(9): e1003766. doi:10.1371/journal.pgen.1003766
Hulbert, S. H., Webb, C. A., Smith, S. M. and Sun Q. 2001. Resistance gene complexes: Evolution and utilization. Annu. Rev. Phytopathol. 39: 285-312
Hwang, C. F., Bhakta, A. V., Truesdell, G. M., Pudo, W. M., and Williamson, V. M. 2000. Evidence for a role of the N terminus and leucine-rich repeat region of the Mi gene product in regulation of localized cell death. Plant Cell. 12: 1319-1329
Hwang, B. H., Bae, H., Lim, H.-S., Kim, K. B., Kim, S. J., Im, M.-H., Park, B.-S., Kim, D. S. and Kim, J. 2010. Overexpression of polygalacturonase-inhibiting protein 2 (PGIP2) of Chinese cabbage (Brassica rapa ssp. pekinensis) increased resistance to the bacterial pathogen Pectobacterium carotovorum ssp. Carotovorum. Plant Cell Tiss Organ Cult. 103:293-305
Jaffe, D.B., Butler J., Gnerre, S., Mauceli, E., Lindblad-Toh, K., Mesirov, J. P., Zody, M.C. and Lander, E.S. 2003. Whole-genome sequence assembly for mammalian genomes: Arachne 2. Genome Research. 13:91-96
Jones, T. M., Anderson, A. J. and Albersheim, P. 1972. Host-pathogen interactions IV. Studies on the polysaccharide-degrading enzymes secreted by Fusarium oxysporum f. sp. lycopersici. Phys Plant Path. 2: 153-166
Jones, D.A., Thomas, C.M, Hammond-Kosack, K.E., Balint-Kurti, P.J., Jones, J.D.G. 1994. Isolation of the tomato Cf-9 gene for resistance to Cladosporium fulvum by transposon tagging. Science. 266:789-793
175
Jones D. A. and Jones, J. D. G. 1997. The role of leucine-rich repeat proteins in plant defenses. Adv. Bot. Res. 24:90-167
Jones, J. D. G. and Dangl, J. L. 2006. The plant immune system. Nature. 444(16): 323-329
Jorgensen. T.H. 2012. The effect of environmental heterogeneity on RPW8-mediated resistance to powdery mildews in Arabidopsis thaliana. Ann. Bot. doi:10.1093/aob/mcr320, available online at www.aob.oxfordjournals.org
Joshi, R.K. and Nayak, S. 2013. Perspectives of genomic diversification and molecular recombination towards R-gene evolution in plants. Physiol Mol Biol Plants. 19(1):1-9
Jung, G., Skroch, P.W., Coyne, D. P., Nienhuis, J., Arnaud-Santana, E., Ariyarathne, H.M., Kaepller, S. M., Bassett. 1997. Molecular-marker-based genetic analysis of tepary bean-derived common bacterial blight resistance in different developmental stages of common bean. J. Amer. Soc. Hort. Sci. 122(3): 329-337
Kajava, A.V. 1998. Structural diversity of leucine-rich repeat proteins. J. Mol Biol. 277 (3): 519-527
Kajava, A. V. and Kobe, B. 2002. Assessment of the ability to model proteins with leucine-rich repeats in light of the latest structural information. Prot. Science: 11: 1082-1090
Kamoun, S. and Kado, C.I. 1990. A plant-inducible gene of Xanthomonas campestris pv. campestris encodes an exocellular component required for growth in the host and hypersensitivity on nonhosts. J. Bacteriol. 172(9): 5165-5172
Kashkush, K., Feldman, M. and Levy, A.A. 2003. Transcriptional activation of retrotransposons alters the expression of adjacent genes in wheat. Nat Gen. 33(1):102-106
Kelley L. A. and Sternberg M. J. E. 2009. Proteins tructure prediction on the web: A case study using the Phyre server. Nature Protocols 4: 363-371
Kelly, J. D., and Vallejo, V. 2004. A comprehensive review of the major genes conditioning resistance to anthracnose in common bean. HortScience 39, 1196—1207.
176
Kim, K. D., Shin, J., H., Van, K., Kim, D. H. and Lee, S.-H. 2009. Dynamic rearrangements determine genome organization and useful traits in Soybean. Genome Anal. 151:1066-1076
Kobe B and Deisenhofer J. 1993. Crystal structure of porcine ribonuclease inhibitor, a protein with leucine-rich repeats. Nature. 366:751-756.
Kobe, B. and Kajava, A. W. 2001. The leucine-rich repeat as a protein recognition motif. Curr Op in Struct Biol. 11:725-732
Koch, M. F., and Mew, T. W. 1991. Effects of plant age and leaf maturity on the quantitative resistance of rice cultivars to Xanthomonas campestris pv. oryzae. Plant Disease. 75: 901-904
Krasileva, K. V., Dahlbeck, D., and Staskawicz, B. J. 2010. Activation of an Arabidopsis resistance protein is specified by the in planta association of its leucine-rich repeat domain with the cognate oomycete effector. Plant Cell. 22: 2444-2458
Krasileva, K. V., Zheng, C., Leonelli, L., Goritschnig, S., Dahlbeck, D., and Staskawicz, B. J. 2011. Global analysis of Arabidopsis/downy mildew interactions reveal prevalence of incomplete resistance and rapid evolution of pathogen recognition. PLoS ONE. 6(12): e28765
Kruijt, M., de Kock, M.J.D. and de Wit, P.J.G.M. 2005. Receptor-like proteins involved in plant disease resistance. Mol. Plant Pathol. 6(1):85-97
Kuykendall, D., Shao, J. and Trimmer. K. 2009. A nest of LTR retrotransposons adjacent the disease resistance-priming gene NPR1 in Beta vulgaris L. U.S. hybrid H20. Int J. Pl Gen. doi:10.1155/2009/576742
Larkan, N.J., Lydiate, D.J., Parkin, I.A.P., Nelson, M.N., Epp, D.J., Cowling, W.A., Rimmer, S.R. and Borhan, M.H. 2013. The Brassica napus blackleg resistance gene LepR3 encodes a receptor-like protein triggered by the Leptospaeria maculans effector AVRLM1. New Phytol. 197:595-605
177
Larsen, R.J.A. 2005. Discovery and utilization of molecular markers for genetic studies of common bacterial blight resistance and seed coat colour in Phaseolus vulgaris L. Thesis, University of Guelph
Lawrence, M.C., Suzuki, E., Varghese, J.N., Davis, P.C., Van Donkelaar, A., Tulloch and Colman, P.M. 1990. The three-dimensional structure of the seed storage protein phaseolin at 3 A resolution. EMBO J. 9(1): 9-15
Lawrence, M.C., Izard, T., Beuchat, M., Blagrove, R.J., and Colman, P.M. 1994. Structure of phaseolin at 2-2 A resolution: Implications for a common vicilinlegumin structure and the genetic engineering of seed storage proteins. J. Mol Biol. 238(5): 748-776
Le, Q., Melayah, D., Bonnivard, E., Petit, M., Grandbastien, M. 2007. Distribution dynamics of the Tnt1 retrotransposon in tobacco. Mol. Genet. Genomics. 278(6): 639-651
Leckie, F., Mattei, B., Capodicasa, C., Hemmings, A., Nuss, L., Aracri, B., De Lorenzo, G. and Cervone, F. 1999. The specificity of polygalacturonase-inhibiting protein (PGIP): a single amino acid substitution in the solvent-exposed β-strand/β-turn region of the leucine-rich repeats (LRRs) confers a new recognition capability. EMBO. 18(9): 2352-2363
Lee, S.-K, Song, M.-Y., Seo, Y.-S., Kim, H.-K., Ko, S., Cao, P.-J., Suh, J.-P., Yi, G., Roh, J.-H., Lee, S., An, G., Hahn, T.-R., Wang, G.-L., Ronald, P., and Jeon, J.-S. 2009. Rice Pi5-mediated resistance to Magnaporthe oryzae requires the presence of two coiled-coil-nucleotide-binding-leucine-rich repeat genes. Genetics. 181:1627-1638
Leister, D. 2004. Tandem and segmental gene duplication and recombination in the evolution of plant disease resistance genes. Trends in Gen. 20(3): 116-122
Lescot, M., Rombauts, S., Zhange, J., Aubourg, S., Mathé, C., Jansson, S., Rouzé, P. and Boerjan, W. 2004. Annotation of a 95-kb Populus deltoides, genomic sequence reveals a disease resistance gene cluster and novel class I and class II transposable elements. Theor Appl Genet. 109:10-22
Li, B., and Xu, X. 2002. Infection and development of apple scab (Venturia inaequalis) on old leaves. J. of Phytopath. 150: 687-691
178
Li, J. Wen, J., Lease, K.A., Doke, J.T., Tax, F. E. and Walker, J. C. 2002. BAK1, an Arabidopsis LRR receptor like protein kinase, interacts with BRI1 and modulates brassinosteroid signaling. Cell. 110(2): 213-222
Li, X., Lin, H., Zhang, W., Zou, Y., Zhang, J., Tang, X. and Zhou, J.-M. 2005. Flagellin induces innate immunity in nonhost interactions that is suppressed by Psuedomonas syringae effectors. PNAS. 102(36): 129990-122995
Liu, G., Kennedy, R., Greenshields, D.L., Peng, G., Forseille, L., Selvaraj, G. and Wei Y. 2007a. Detached and attached Arabidopsis leaf assays reveal distinctive defense responses against hemibiotrophic Colletotrichum spp. Mol Plant Microbe Interact. 20(10):1308-1319
Liu, J., Liu, X., Dai, L., and Wang, G. 2007b. Recent progress in elucidating the structure, function and evolution of disease resistance genes in plants. J. Genet and Genom. 34(9): 765-776
Liu, S.Y., Yu, K., Haffner, M., Park, S.J., Banik, M., Pauls, K.P. and Crosby, W. 2010. Construction of a BAC library and a physical map of a major QTL for CBB resistance of common bean (Phaseolus vulgaris L.). Genetica 138: 709-716
Lorković , Z.J., Wieczorek Kirk, D.A., Lambermon, M.H.L., and Filipowicz, W. 2000. Pre-mRNA splicing in higher plants. Trends Plant Sci. 5, 160–167.
Lu, D., Mu, S., Gao, Zhang, Y., Shan, L. and He, P. 2010. A receptor-like cytoplasmic kinase, BIK1, associates with a flagellin receptor complex to initiate plant innate immunity. PNAS. 107(1): 496-501
Luehrsen, K.R., S. Taha, and V. Walbot. 1994. Nuclear pre-mRNA splicing in higher plants. Prog. Nucleic Acids Res. Mol. Biol. 47: 149-193.
Ma, Y. and Bliss, F. A. 1978. Seed proteins of common bean. Crop Sci. 18: 431-437
Mackay, T. F. C. 2001. The genetic architecture of quantitative traits. Annu Rev. Genet. 35: 303-339
179
Maekawa, T., Cheng, W., Spiridon, L. N., Töller, A., Lukasik, E., Saijo, Y., Liu, P., Shen, Q.-H., Micluta, M. A., Somssich, I. E., Takken, F. L. W., Petrescu, A.-J., Chai, J. and Shulze-Lefert, P. 2011. Coiled-coil domain-dependent homodimerization of intracellular barley immune receptors defines a minimal functional module for triggering cell death. Cell Host & Microbe. 9:187-199
Mamidi, S. Rossi, M., Anam, D., Moghaddam, S., Lee, R., Papa, R. and McClean, P. 2011. Investigation of the domestication of common bean (Phaseolus vulgaris) using multilocus sequence data. Funct. Plant. Biol. 38: 953-967
Manfredini, C., Sicilia, F., Ferrari, S., Pontiggia, D., Salvi, G., Caprari, C., Lorito, M. and De Lorenzo, G. 2005. Polygalacturonase-inhibiting protein 2 of Phaseolus vulgaris inhibits BcPG1, a polygalacturonase of Botrytis cinerea important for pathogenicity, and protects transgenic plants from infection. Phys. Mol Plant Path. 67(2): 108-115
Marcel, T.C., Varshney, R.K., Barbieri, M., Jafary, H., de Kock, M.J.D., Graner, A., and Niks, R.E. 2007. A high-density consensus map of barley to compare the distribution of QTLs for partial resistance to Puccinia hordei. And of defence gene homologues. Theor. Appl. Genet. 114:487-500
Mazzola, M., Leach, J. E., Nelson, R. and White, F. F. 1994. Analysis of the interaction between Xanthomonas oryzae pv. oryzae and the rice cultivars IR24 and IRBB21. Phytopath. 84:392-397
McClean, P.E., Mamidi, S., McConnell, M., Chikara, S. and Lee, R. 2010. Synteny mapping between common bean and soybean reveals extensive blocks of shared loci. BMC Genomics 11:184
McDowell, J.M. and Meyers, B.C. 2013. A transposable element is domesticated for service in the plant immune system. PNAS. 110(37): 14821-14822
McHale, L., Tan, X., Koehl, P. and Michelmore, R. W. 2006. Plant NBS-LRR proteins: Adaptable guards. Gen. Biol. 7:212
Melotto, M., Underwood, W., Koczan, J., Nomura, K., He, W. Y. 2006. Plant stomata function in innate immunity against bacterial invasion. Cell. 126: 969-980
180
Messerschmidt, A., Rossi, A., Ladnstein, R., Huber, R., Bolognesi, M., Gatti, G., Marchesini, A., Petruzzelli, R. and Finazzi-Agró. 1989. X-ray crystal structure of the blue oxidase ascorbate oxidase from Zucchini: Analysis of the polypeptide fold and a model of the copper sites and ligands. J. Mol. Biol. 206:513-529
Messerschmidt, A., Luecke, H., and Huber, R. 1993. X-ray structures and mechanistic implications of three functional derivatives of ascorbate oxidase from zucchini: Reduced, peroxide and azide forms. J. Mol. Biol. 230:997-1014
Mestre, P. and Baulcombe, D. C. 2006. Elicitor-mediated oligomerization of the tobacco N disease resistance protein. Plant Cell. 18: 491-501
Meyers, B. C., Chin, D. B., Shen, K.A., Svaramakrishnan, S., Lavelle, D.O., Zhang, Z. and Michelmore, R. W. 1998. The major resistance gene cluster in lettuce is highly duplicated and spans several megabases. Plant Cell.15:1817-1832
Meyers, B. C., Morgante, M., and Michelmore, R.W. 2002. TIR-X and TIR-NBS proteins: Two new families related to disease resistance TIR-NBS-LRR proteins encoded in Arabidopsis and other plant genomes. Plant J. 32(1):77-92
Meyers, B. C., Kozik, A., Griego, A., Kuang and Michelmore, R. W. 2003. Genome-wide analysis of NBS-LRR-encoding genes in Arabidopsis. Plant Cell. 15: 809-834
Meyers, B.C., Kaushik, S. and Sekhar Nandety, R. 2005. Evolving disease resistance genes. Curr Op in Plant Biol. 8:129-134
Michelmore, R. W. and Meyers B. C. 1998. Clusters of resistance genes in plants evolve by divergent selection and a birth-and-death process. Genome Research. 8: 1113-1130
Michaels, T. E., Smith, T. H., Larsen, J., Beattie, A. D. and Pauls, K. P. 2006. OAC Rex common bean. Can. J. Plant Sci. 86: 733-736
Miklas, P. N, Beaver, J. S., Grafton, K. F. and Freytag, G. F. 1994. Registration of TARS VCI-4B multiple disease resistant dry bean germplasm. Crop Sci. 34: 1415
181
Miklas, P.N., Smth, J.R., Riley, R., Grafton, K.F., Singh, S.P., Jung, G. and Coyne, D.P. 2000a. Marker-assisted breeding for pyramided resistance to common bacterial blight in common bean. Annu Rep. Bean. Improv. Coop. 43: 39-40
Miklas, P. N., Stone, V., Daly, M. J., Stavely, J. R., Steadman, J. R., Bassett, M. J., Delorme, R., and Beaver, J. S. 2000b. Bacterial, fungal and viral disease resistance loci mapped in recombinant inbred common bean population ‘Dorado/Xan176). J. Am. Soc. Hortic. Sci. 125:476-481
Miklas. P. N., Coyne, D. P., Grafton, K. F., Mutlu, N., Reiser, J., Lindgren, T. and Singh, S. P. 2003. A major QTL for common bacterial blight resistance derives from the common bean great northern landrace cultivar Montana No. 5. Euphytica 131:137–146
Miklas P.N., Smith, J.R. and Singh, S.P. 2006. Registration of common bacterial blight resistant dark red kidney bean germplasm line USDK-CBB-15. Crop Sci. 46:1005-1006
Mitchell, A., Chang, H.-Y, Daugherty, L., Fraser, M., Hunter S., Lopez, R., McAnulla, C., McMenamin, C., Nuka, G., Pesseat, S., Sangrador-Vegas, A., Scheremetjew, M., Rato, C., Yong, S.-Y., Bateman, A., Punta, M., Attwood, T. K., Sigrist, C.J.A., Redaschi, N., Rivoire, C., Xenarios, I., Kahn, D., Guyot, D., Bork, P., Letunic, I., Gough, J., Oates, M., Haft, D., Huang, H., Natale, D.A., Wu, C.H., Orengo, C., Sillitoe, I., Mi, H., Thomas, P.D. and Finn, R.D. 2014. The InterPro protein families database: the classification resource after 15 years. Nuc. Acids Res. doi: 10.1093/nar/gku1243
Miyao, A., Tanaka, K., Murata, K., Sawaki, H., Takeda, S., Abe, K., Shinozuka, Y., Onosato, K., and Hirochika, H. 2003. Target site specificity of the Tos17 retrotransposon shows preference for insertion within genes and against insertion in retrotransposon-rich regions of the genome. Plant Cell. 15:1771-1780
Mkandawire, A.B.C., Mabagala, R.B., Guzmán, P., Gepts, P. and Gilbertson, R.L. 2004. Genetic diversity and pathogenic variation of common blight bacteria (Xanthomonas campestris pv. phaseoli and X. campestris pv. phaseoli var. fuscans) suggests pathogen coevolution with the common bean. Phytopathol. 94(6): 593-603
Moffett. P., Farnham, G., Peart, J. and Baulcombe, D. C. 2002. Interaction between domains of a plant NBS-LRR protein in disease resistance-related cell death. EMBO. 21(17): 4511-4519
182
Mohan, S.T. 1982. Evaluation of Phaseolus coccineus Lam. germplasm for resistance to common bacterial blight of bean. Turrialba 32:489-490
Monosi, B., Wisser, R.J., Pennill, L. and Hulbert, S.H. 2004. Full-genome analysis of resistance gene homologues in rice. Theor Appl Genet. 109: 1434-1447
Mucyn, T.S., Clemente, A., Andriotis, V.M., Balmuth, A.L., Oldroyd, G.E., Staskawicz, B.J. and Rathjen, J.P. 2006. The tomato NBARC-LRR protein Prf interacts with Pto kinase in vivo to regulate specific plant immunity. Plant Cell. 18:2792-2806
Murthy, K., Deb, A., Goonesekera, S., Szabó and Salzman, A. 2003. Identification of conserved domains in Salmonella muenchen flagellin that are essential for its ability to activate TLR5 and to induce an inflammatory response in vitro. J. Biol Chem. 279: 5667-5675
Muthamilarasan M., and Prasad, M. 2013. Plant innate immunity: An updated insight into defense mechanism. J. Biosci. 38:433-449
Mutlu, N., Vidaver, A. K., Coyne, D. P., Steadman, J. R., Lambrecht, P.A. and Reiser, J. 2008. Differential pathogenicity of Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans strains on bean genotypes with common blight resistance. APS. 92(4): 546-554
Noël, L. Moores, T.L., van Der Bizen, E.A., Parniske, M., Daniels, M.J., Parker, J.E. and Jones, J.D. 1999. Pronounced intraspecific haplotype divergence at the RPP5 complex disease resistance locus of Arabidopsis. Plant Cell. 11(11): 2099-2112
Nüremberger, T., Brunner, F., Kemmerling, B. and Piater, L. 2004. Innate immunity in plants and animals: striking similarities and obvious differences. Immunol. Rev. 198:249-266
Opio, A. F., Allen, D. J. and Teri, J. M. 1996. Pathogenic variation in Xanthomonas campestris pv. phaseoli, the causal agent of common bacterial blight in Phaseolus beans. Plant Path. 45 (6): 1126-1133
183
Ori N, Eshed Y, Paran I, Presting G, Aviv D, Tanksley S, Zamir D and Fluhr R .1997. The I2C1 family from the wilt disease resistance locus I2 belong to the nucleotide binding, leucine-rich repeat superfamily of plant resistance genes. Plant Cell 9:521–532
O'Rourke, J.A., Iniguez, L. P., Fu, F., Bucciarelli, B., Miller, S.S., Jackson, S.A., McClean, P.E., Li, J., Dai, X., Zhao, P.X., Hernandez, G. and Vance, C.P. 2014. An RNA-Seq based gene expression atlas of the common
bean. BMC Genomics. 15:866.
Padmanabhan, M., Cournoyer, P. and Dinesh-Kumar, S. P. 2009. The leucine-rich repeat domain in plant innate immunity: a wealth of possibilities. Cell. Micro. 29(2): 191-198
Park, S. J. and Dhanvantari, B. N. 1987. Transfer of common blight (Xanthomonas campestris pv. phaseoli) resistance from Phaseolus coccineus Lam. to P. vulgaris L. through interspecific hybridization. Can. J. Plant Sci. 67:685-695
Parker, J. P. K. 1985. Interspecific transfer of common bacterial blight resistance from Phaseolus acutifolius A. Gray to Phaseolus vulgaris L. M.Sc. thesis, University of Guelph, Guelph, ON
Parker, J. E., Coleman, M. J., Szabò, V., Frost, L. N., Schmidt, R., van der Biezen, E., Moores, T., Dean, C. Daniels, M. J., and Jones, J. D. G. 1997. The Arabidopsis downy mildew resistance gene RPP5 shares similarity to the Toll and interleukin-1 receptors with N and L6. Plant Cell. 9:879-894
Parniske, M., Hammond-Kosack, K. E., Golstein, C., Thomas, C. M., Jones, D. A., Harrison, K., Wulff, B. B. H. and Jones, J. D. G. 1997. Novel disease resistance specificities result from sequence exchange between tandemly repeated genes at the Cf-4/9 locus of tomato. Cell. 91: 821-832
Pastori, G.M., Kiddle, G., Antoniw, J., Bernard, S., Veljovic-Jovanovic, S., Verrier, P.J., Noctor, G., Foyer, C.H. 2003. Leaf vitamin C contents modulate plant defense transcripts and regulate genes that control development through hormone signaling. Plant Cell.15: 939-951
Pavet, V., Olmos, E., Kiddle, G., Mowla, S, Kumar, S., Antoniw, J., Alvarez, M.E. and Foyer, C.H. 2005. Ascorbic acid deficiency activates cell death and disease resistance responses in Arabidopsis thaliana. Plant Physiol. 139:1291-1303
184
Pedraza, F., Gallego, G., Beebe, S., and Tohme, J. 1997. Marcadores SCAR y RAPD para la resitencia a la bacteriosis comun (CBB). In: Singh S.P., Voysest O., (eds) Taller de mejoramiento de frijol para el Siglo XXI: bases para una estrategia para America Latina. CAT, Cali, pp 130-134
Perry, G. 2010. Common bacterial blight resistance in Phaseolus vulgaris: An examination of the major resistance QTLs of OAC-Rex and HR67, Ph.D. thesis, University of Guelph, Guelph ON
Perry, G., DiNatale, C., Xie, W., Navabi, A., Reinprecht, Y., Crosby, W., Yu, K., Shi, C. and Pauls, K. P. 2013. A comparison of the molecular organization of genomic regions associated with resistance to common bacterial blight in two Phaseolus vulgaris genotypes. Frontiers in Plant Sci. doi: 10.3389/fpls.2013.00318
Petersen, T. N., Brunak, S., von Heijne, G. and Nielsen, H. 2011. Signal 4.0: Discriminating signal peptides from transmembrane regions. Nature Methods. 8: 785-786
Pignocchi, C., Kiddle, G., Hernández, I., Foster, S.J., Asensi, A., Taybi, T., Barnes, J. and Foyer, C.H. 2006. Ascorbate oxidase-dependent changes in the redox state of the apoplast modulate gene transcript accumulation leading to modified hormone signaling and orchestration of defense processes in tobacco. Plant Phys. 141(2): 423-435
Protsenko, M. A., Buza, N. L., Krinitsyna, A. A., Bulanseva, E. A. and Korableva, N. P. 2008. Polygalacturonase-inhibiting protein is a structural component of plant cell wall. Biochem. 73 (10): 1317-1329
Pulse Canada. 2007. Canada and the global pulse industry. Retrieved October 7 2014 from the World Wide Web. http://www.pulsecanada.com/uploads/wv/nr/wvnr5qGWIi8Rqbl22UyY8g/Canadas-Pulse-Industry-in-the-Global-Market-Sep-07.pdf
Pulse Canada. 2015. Canada’s growing regions. Retrieved June 24, 2015 from the World Wide Web. http://www.pulsecanada.com/canadas-growing-regions
Rademaker, J.L.W., Louws, F.J., Schultz, M.H., Rossbach., U., Vauterin, L., Swings, J. and de Bruijn, F.J. 2005. A comprehensive species to strain taxonomic framework for Xanthomonas. Phytopathol. 95:1098-1111
185
Rafiqi, M., Bernoux, M., Ellis, J. G. and Dodds, P. N. 2009. In the trenches of plant pathogen recognition: Role of NB-LRR proteins. Sem Cell & Dev Biol. 20: 1017-1024
Rairdan, G. J., Collier, S. M., Sacco, M. A., Baldwin, T. T., Boettrich, and Moffett, P. 2008. The coiled-coil and nucleotide binding domains of the potato Rx disease resistance protein function in pathogen recognition and signaling. Plant Cell. 20:739-751
Randhawa, P.S. and Civerolo, E. L. 1985. A detached-leaf bioassay for Xanthomonas campestris pv. pruni. Phytopath. 75:1060-1063
Rehmany, A. P. Gordon, A., Rose, L. E., Allen, R. L., Armstrong, M. R., Whisson, S. C., Kamoun, S., Tyler, B. M., Birch, P. R. J. and Beynon, J. L. 2005. Differential recognition of highly divergent downy mildew avirulence gene alleles by RPP1 resistance genes from two Arabidopsis lines. Plant Cell 17: 1839-1850
Remeeus, P.M. and Sheppard, J. W. 2006. Proposal for a new method for detecting Xanthomonas axonopodis pv. phaseoli on bean seeds. ISTA Method Validation Reports. 3:1-11
Rodríguez, A., Shimada, T., Cervera M., Alquézar, B., Gadea, J., Góme-Cadenas, A., De Ollas, C.J., Rodrigo, M.J., Zacarías, L. and Peña, L. 2014. Terpene down-regulation triggers defense responses in transgenic orange leading to resistance against fungal pathogens. Plant Physiol. 164(1):321-339
Rudolph, K. Infection of the plant by Xanthomonas. 1993. In: Swings, J.G., Civerolo, E.L., editors. Xanthomonas. London: Chapman and Hall. P. 193-264
Ryals, J. A., Neuenschwander, U. H., Willits, M. G., Molina, A., Steiner, H.-Y. and Hunt, M. D. 1996. Systemic acquired resistance. Plant Cell. 8: 1809-1819
Saettler, A. W. 1989. Chapter 11: Common bacterial blight. In Bean production problems in the tropics. Eds. Howard F. Schwartz, Marcial A. Pastor Corrales. CIAT. Pp 261-283
Sakamoto, T., Bonnin, E., and Thibault, J.-F. 2003. A new approach for studying interaction of the polygalacturonase-inhibiting proteins with pectins. Biochim. Biophys. Acta. 1621:280-284
186
Sanmartin, M., Pateraki, I., Chatzopoulou, F., and Kanellis, A.K. 2007. Differential expression of the ascorbate oxidase multigene family during fruit development and in response to stress. Planta. 225: 873-885
Saxton, A.M. 2000. PDMIX800. University of Tennessee, Knoxville TN.
Schaad, N. W., Postnikova, E., Lacy, G. H., Sechler, A., Agarkova, I., Stromberg, P.E., Stromberg, V.K. and Vidaver, A.K. 2006. Emended classification of xanthomonad pathogens on citrus. Syst. Appl. Microbiol. 29:690-695
Schmutz, J., Cannon, S. B., Schlueter, J., Ma, J., Mitros, T., Nelson, W., Hyten, D. L., Song, Q., Thelen, J.J., Cheng, J., Xu, D., Hellsten, U., May, G. D., Yu, Y., Sakurai, T., Umezawa, T., Bhattacharyya, M.K., Sandhu, D., Valiyodan, B., Lindquist, E., Peto, M., Grant, D., Shu, S., Goodstein, D., Barry, K., Futrell-Griggs, M., Abernathy, B., Du, J., Tian, Z., Zhu, L., Gill, N., Joshi, T., Libault, M., Sethuraman, A., Zhang, X.-C., Shinozaki, K., Nhuyen, H.T., Wing, R.A., Cregan, P., Specht, J., Grimwood, J., Rokshar, D., Stacey, G., Shoemaker, R.C. and Jackson, S.A. 2010. Genome sequence of the paleopolyploid soybean. Nature. 463:doi:10.1038/nature08670
Schmutz J, McClean PE, Mamidi S, Wu GA, Cannon SB, Grimwood J, Jenkins J, Shu S, Song Q, Chavarro C, Torres-Torres M, Geffroy V, Moghaddam SM, Gao D, Abernathy B, Barry K, Blair M, Brick MA, Chovatia M, Gepts P, Goodstein DM, Gonzales M, Hellsten U, Hyten DL, Jia G,et. al., 2014 A reference genome for common bean
and genome-wide analysis of dual domestications, Nature Genetics, published online 2014
June 08
Schuleter JA, Goicoechea JL, Collura K, Gill N, Lin JY, Yu Y, Kundra D, Zuccolo A, Vallejos CE, Munoz-Torres M, Blair M, Tohme J, Tomkins J, McClean P, Wing RA and Jackson SA (2008). BAC-end-sequence analysis and a draft physical map of the common bean (Phaseolus vulgaris L.). Tropical Plant Biology 1:40-48.
Scott,M.E. and T.E. Michaels. 1992. Xanthomonas resistance of Phaseolus interspecific cross selections confirmed by field performance. HortScience 27:348-350
Shi, C., Navabi, A. and Yu, K. 2011. Association mapping of common bacterial blight resistance QTL in Ontario bean breeding populations. BMC Plant Biol. 11: 52
187
Shi C., Yu, K., Xie, W., Perry, G., Navabi, A., Pauls, K.P., Miklas, P. N. and Fourie, Deidre. 2012. Development of candidate gene markers associated to common bacterial blight resistance in common bean. Theor Appl Genet. 125(7):1525-1537
Schuster, M.L., Coyne, D.P., Behre, T., and Leyna, H. 1983. Sources of Phaseolus species resistance and leaf and pod differential reactions to common blight. HortSci. 18:901-903
Sicilia, F., Fernandez-Recio, J., Caprari, C., De Lorenzo, G., Tsernoglou, D., Cervone, F. and Federici, L. 2005. The polygalacturonase-inhibiting protein PGIP2 of Phaseolus vulgaris has evolved a mixed mode of inhibition of endopolygalacturonase PG1 of Botrytis cinerea. Plant Phys. 139:1380-1388
Singh, S. P. 1982. Key for identification of different growth habits of Phaseolus vulgaris L. Centro Internacional de Agricultura Tropical, Apartado Aéreo 6713, Cali Colombia
Singh, S. P., Gepts, P. and Debouck, D. G. 1991. Races of common bean (Phaseolus vulgaris, Fabaceae). Economic Botany. 45(3): 379-396
Singh, S. P. and Muñoz, C. G. 1999. Resistance to common bacterial blight among Phaseolus species and common bean improvement. Crop Sci 39: 80-89
Smirnoff, N. 2000. Ascorbic acid: Metabolism and functions of a multi-facetted molecule. Curr. Opin. Plant Biol. 3:229-235
Song, W.-Y., Pi, L.-Y., Wang, G.-L., Gardner, J., Holsten, T., and Ronald, P.C. 1997. Evolution of the rice Xa21 disease resistance fene family. Plant Cell. 9:1279-1287
Song, J., Bradeen, J.M., Naess, S.K., Raasch, J.A., Wielgus, S.M., Haberlach, G.T., Liu, J., Kuang, H., Austin-Phillips, S., Buell, C.R., Helgeson, J.P. and Jiang, J. 2003. Gene RB cloned from Solanum bulbocastanum confers broad spectrum resistance to potato late blight. PNAS. 100: 9128-9133
Song, D., Li, G., Song, F., and Zheng, Z. 2008. Molecular characterization and expression analysis of Os BISERK1, a gene encoding a leucine-rich repeat receptor-like kinase, during disease resistance responses in rice.
188
Song W, Han ZF, Sun YD, and Chai JJ. 2014. Crystal structure of a plant leucine rich repeat protein with two island domains. Sci China Life Sci, 57: 137–144
St. Clair, D. A. 2010. Quantitative disease resistance and quantitative resistance loci in breeding. Annu. Re. Pytopathol. 48: 247-268
Sun, X., Cao, Y., Yang, Z., Xu, C., Li, X., Wang, S. and Zhang, Q. 2004. Xa26, a gene conferring resistance to Xanthomonas oryzae pv. oryzae in rice, encodes an LRR receptor kinase-like protein. The Plant Journal. 37: 517-527
Sun, W., Dunning, F.M., Pfund, C., Weingarten, R., and Bent. 2006. Within-species flagellin polymorphism in Xanthomonas campestris pv. campestris and its impact on elicitation of Arabidopsis flagellin sensing2-dependent defenses. Plant Cell. 18:764-779
Taguchi, F., Shimizu, R., Nakajima, R., Toyoda, K., Shiraishi, T. and Ichinose Y. 2003. Differential effects of flagellins from Pseudomonas syringae pv. tabaci, tomato and glycinea on plant defense response. Plant Phys. Bioch. 41(2): 165-174
Tameling, W.I., Elzinga, S.D., Darmin, P.S., Vossen, J.H., Takken, F.L., Haring, M.A., and Cornelissen, B.J. 2002. The tomato R gene products I-2 and Mi-1 are functional ATP binding proteins with ATPase activity. Plant Cell 14: 2929–2939.
Tang, P., Zhang, Y., Sun, X., Tian, D., Yang, S. and Ding, J. 2010. Disease resistance signature of the leucine-rich repeat receptor-like kinase genes in four plant species. Plant Science. 179: 399-406
Tao, Y., Xi, Z., Chen, W., Glazebrook, J., Chang, H.-S., Han, B., Zhu, T., Zou, G., and Katagiri, F. 2003. Quantitative nature of Arabidopsis responses during compatible and incompatible interactions with the bacterial pathogen Pseudomonas syringae. Plant Cell. 15: 317-330
Tar’an, B., Michaels, T. E. and Pauls, K. P. 2001. Mapping genetic factors affecting the reaction to Xanthomonas axonopodis pv. phaseoli in Phaseolus vulgaris L. under field conditions. Genome. 44: 1046-1056
Tornero, P., Mayda, E., Gómez, M. D., Cañas, L., Conejero, V. & Vera, P. 1996. Characterization of LRP, a leucine-rich repeat (LRR) protein from tomato plants that is processed during pathogenesis. Plant J. 10(2): 315-330
189
Torres, M. A., Jones, J. D. and Dangl, J. L. 2005. Pathogen-induced, NADPH oxidase derived reactive oxygen intermediates suppress spread of cell death in Arabidopsis thaliana. Nature Genet. 37: 1130–1134
Tosh, S. M. and Yada, S. 2010. Dietary fibres in pulse seeds and fractions: Characterization, functional attributes, and applications. Food Res Int. 43: 450-460
Tsuchiya, T. and Eulgem, T. 2013. Mutations in EDM2 selectively affect silencing states of transposons and induce plant developmental plasticity. Nature Scientific Reports. 3: 1701 DOI: 10.1038/srep01701
Urrea, C.A., Miklas, P.N. and Beaver, J.S. 1999. Inheritance of resistance to common bacterial blight in for tepary bean lines. J. Amer. Soc. Hort. Sci. 124(1): 24-27
Vallejos, C. E., Astua-Monge, G., Jnes, V., Plyler, T.R., Sakiyama, N. S., and Mackenzie, S. A. 2006. Genetic and molecular characterization of the I locus of Phaseolus vulgaris. Gen. 172:1229-12242
Van der Biezen, E. A., Freddie, C. T., Kahn, K., Parker, J. E. and Jones, J. D. G. 2002.Arabidopsis RPP4 is a member of the RPP5 multigene family of TIR-NBSLRR genes and confers downy mildew resistance through multiple signalling components. Plant J. 29(4): 439-451
Van Gijsefem, F., Gough, C., Zischek, C., Niqueux, E., Ariat, M., Genin, S., Barberis, P., German, S., Castello, P. and Boucher, C.1995. The hrp gene locus of Pseudomonas solanacearum, which controls the production of a type III secretion system, encodes eight proteins related to components of the bacterial flagellar biogenesis complex. Mol. Microbiol. 15: 1095-1114
Vandemark, G. J., Fourie. D. and Miklas, P. N. 2008. Genotyping with real-time PCR reveals recessive epistasis between independent QTL conferring resistance to common bacterial blight in dry bean. Theor Appl Genet. 117:513-522
Vandemark, G. J., Fourie, D., Larsen, R. C. and Miklas, P. N. 2009. Interactions between QTL SAP6 and SU91 on resistance to common bacterial blight in red kidney bean and pinto bean populations. Euph. 170:371-381
190
Vauterin, L., Hoste, B., Kersters, K. and Swings, J. 1995. Reclassification of Xanthomonas. IJSEM. 45(3):472-489
Veronese, P., Nakagami, H., Bluhm, B., AbuQamar, S., Chen, X., Salmeron, J., Dietrich, R.A., Hirt, H. and Mengiste, T. 2006. The membrane-anchored Botrytis-Induced Kinase1 plays distinct roles in Arabidopsis resistance to nectrotrophic and biotrophic pathogens. Plant Cell. 18(1):257-273
Vidaver, A.K. 1993. 1.5 Xanthomonas campestris pv. phaseoli: Cause of common bacterial blight of bean, in Xanthomonas edited by Swing, J.G. and Civerolo, E.L., Chapman & Hall, 2-6 Boundary Row, London SE1 8HN, UK
Wang, Z.-X., Yano, M., Yamanouchi, U., Iwamoto, M., Monna, L., Hayasaka, H., Katayose, Y. and Sasaki, T. 1999. The Pib gene for rice blast resistance belongs to the nucleotide binding and leucine-rich repeat class of plant disease resistance genes. Plant J. 19(1):55-64
Wang, L., Rong, W. and He, C. 2008a.Two Xanthomonas extracellular polygalacturonases, PghAxc and PghBxc, are regulated by type III secretion regulators HrpX and HrpG and are required for virulence. MPMI 21(5): 555-563
Wang, G., Ellendorff, U., Kemp, B., Mansfield, J.W., Forsyth, A., Mitchell, K., Bastas, K., Liu, C.-M., Woods-Tör, A., Zipfel, C., de Wit, P.J.G.M., Jones, J.D.G., Tör, M. and Thomma, B.P.H.J. 2008b. A genome-wide functional investigation into the roles of receptor-like proteins in Arabidopsis. Plant Physiol. 147:503-517
Wang, Y.-H. and Warren, J. T. 2010. Mutations in retrotransposon AtCOPIA4 compromises resistance to Hyaloperonospora parasitica in Arabidopsis thaliana. Gen Mol Biol. 33(1): 135-140
Weller, D. M. and Saettler, A. W. 1976. Chemical control of common and fuscous bacterial blights (Xanthomonas phaseoli, Xanthomonas phaseoli fuscans) in Michigan navy (pea) beans. Plant Dis. Rept. 60: 793-797
Wicker, T., Sabot, F., Hua-Van, A., Bennetzen, J. L., Capy, P., Chalhoub, B., Flavell, A., Leroy, P., Morgante, M., Panaud, O., Paux, E., SanMiguel, P. and Schulman A. H. 2007. A unified classification system for eukaryotic transposable elements. Nat Rev Gen. 8:973-982
191
Xiao, S., Brown, S., Patrick, E., Brearley, C. and Turner, J. G. 2003. Enhanced transcription of the Arabidopsis disease resistance Genes RPW8.1 and RPW8.2 via a salicylic acid-depedent amplification circuit is required for hypersensitive cell death. Plant Cell.15: 33-45
Xie, W., Yu, K., Pauls, K.P. and Navabi, A. 2012. Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem. Phytopath. 102(4): 434-442
Xu, Z. and Wang, H. 2007. LTR_FINDER: An efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acid Res. 35: doi:10.1093/nar/gkm286
Yañez, E., Zacarias, I., Aguayo, M., Vasquez, M. and Guzman, E. 1995. Nutritive value evaluated on rats of new cultivars of common beans (Phaseolus vulgaris) released in Chile. Plant Foods for Human Nutrition. 47: 301-307
Yang, X., Deng, F. and Ramonell, K.M. 2012. Receptor-like kinases and receptor-like proteins: Keys to pathogen recognition and defense signaling in plant innate immunity. Front Biol. 7(2): 155-166
Yi, H. and Richards, E.J. A cluster of disease resistance genes in Arabidopsis is coordinately regulated by transcriptional activation and RNA silencing. Plant Cell. 19(9): 2929-2939
Yu, K., Park, S. J., Zhang, B., Haffner, M and Poysa, V. 2004. An SSr marker in the nitrate reductase gene of common bean is tightly linked to a major gene conferring resistance to common bacterial blight. Euphytica. 138: 89-95
Yu, K., Park S.J., Poysa, V. and Gepts, P. 2000a. Integration of simple sequence repeat markers into a molecular linkage map of common bean (Phaseolus vulgaris L.). Am. Genet. Assoc. 91:429-434
Yu, K., Park, S.J. and Poysa, V. 2000b. Marker-assisted selection of common beans for resistance to common bacterial blight: efficiency and economics. Plant Breed. 119: 411-416
Zaumeyer, W.J. and Thomas, H.R. 1957. A monographic study of bean diseases and methods for their control. United States Department of Agriculture Technical Bulletin 868, 255pp.
192
Zhang, Z. and Thomma, B.P.H.J. 2013. Structure-function aspects of extracellular leucine-rich repeat-containing cell surface receptors in plants. J. Integr Pant Biol. 55(12):1212-1223
Zhou, F., Menke, F. L., Yoshioka, K., Moder, W., Shirano, Y. and Klessig, D. F. 2004a. High humidity suppresses ssi4-mediated cell death and disease resistance upstream of MAP kinase activation, H2O2 production and defense gene expression. Plant J. 39: 920-932
Zhou, T., Wang, Y., Chen, J.-Q., Araki, H., Jing, Z., Jiang, K., Shen, J., Tian, D. 2004b. Genome-wide identification of NBS genes in japonica rice reveals significant expansion of divergent non-TIR NBS-LRR genes. Mol Gen Genomics. 271:402-415
Zipfel, C. and Felix, G. 2005. Plants and animals: A different taste for microbes? Curr. Opin Plant Biol. 8:353-360
Zipfel, C., Kunze, G., Chinchilla, D., Caniard, A., Jones, J. D., Boller, T., and Felix, G. 2006. Perception of the bacterial PAMP EF-Tu by the receptor EFR restricts Agrobacterium-mediated Transformation. Cell. 125: 749-760
Zipfel, C. 2008. Pattern-recognition receptors in plant innate immunity. Curr. Op. in Immunology. 20:10-15
193
7.0 Appendices
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 MSSSRGGAGPSSEAPPPRRIMRTQTAGNLGESVIDSEVVPSSLVEIAPILRVANEVEKTH
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 PRVAYLCRFYAFEKAHRLDPNSSGRGVRQFKTALLQRLERENDPTLKGRVKKSDAREMQS
Gene7 ---------------------------------------MAAWQATFTKPSRNPYATFTN
G2 ---------------------------------MPPWLPDRCDCPPSGPEYIPDVLELSV
Glyma.08G361500 FYQHYYKKYIQALQNAADKADRAQLTKAYNTANVLFEVLKAVNMTQSMEVDREILETQDK
.
Gene7 PSPDLRSSDLHEILTLTPLSAIAASVQG--------------------------------
G2 EFLLGCSSDLHEILTLTPLSAIAASVQG--------------------------------
Glyma.08G361500 VAEKTEILVPYNILPLDPDSANQAIMRFPEIQAAVYALRNTRGLPWPKDFKKKKDEDILD
::**.* * ** * ::
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 WLGSMFGFQKHNVANQREHLILLLANVHIRQFPKPDQQPKLDERALTEVMKKLFKNYKKW
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 CKYLGRKSSLWLPTIQQEVQQRKLLYMGLYLLIWGEAANLRFMPECLCYIYHHMAFELYG
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 MLAGNVSPMTGENVKPAYGGEDEAFLRKVVTPIYNVIAKEAARSKKGRSKHSQWRNYDDL
Gene7 --CFR-------------------------------------------------------
G2 --CFRSVDCFRLGWPMRADADFFCWPVEQLNFDKSN------------------------
Glyma.08G361500 NEYFWSADCFRLGWPMRADADFFCLPAEKLVFDKSNDDKPPSRDRWVGKVNFVEIRSFWH
*
Gene7 ----------------------------DPSAIIDVNVFKKVLNVFIT-AILKLGQ----
G2 -----------------AMIIVAWNGTGDPSAIIDVNVFKKVLNVFIT-AILKLGQAILD
Glyma.08G361500 MFRSFDRMWSFFILCLQAMIVVAWNGSGDPSAIFNGDVFKKVLSVFITAAILKFGQAVLD
*****:: :******.**** ****:**
Gene7 ------------------------------------------------------------
G2 VILSCKSQWSMSMHVKLGYILKVVSAAAWVIVLSVSYAYTWENPPRFAQTIQSWFGSNSN
Glyma.08G361500 VILSWKAQWSMSLYVKLRYILKVVSAAAWVIVLSVTYAYTWDNPPGFAQTIKSWFGSGGS
N-Terminal
1,3-β Glucan Synthase Subunit FKS1-like
194
Gene7 -------------------------------------------------GSLDSTRGMHE
G2 SPSFFIMVVVVYLSPNMLAAMLFLFPLIHR-----------------FLESLDSTRGMHE
Glyma.08G361500 SAPSLFILAVVVYLSPNMLAAIFFLIPFIRRHLERSNYRIVMLMMWWSQPRLYVGRGMHE
* *****
Gene7 STFSLFKK----------------------------------------------------
G2 SIFSLFKK----------------------------------------------------
Glyma.08G361500 SAFSLFKYTMFWVLLIITKLAFSYYIEIKPLVGPTKAIMSVKITTFQWHEFFPHARNNIG
* *****
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 VVIALWAPIILVYFMDTQIWYAIFSTLFGGIYGAFRRLGEIRTLGMLRSRFQSLPGAFNA
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 SLIPEETNEPKKKGLKATLSRRFPEISSNKGKEAARFAQLWNQIITSFRDEDLINDREMN
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 LLLVPYWADTQLDLIQWPPFLLASKIPIALDMAKDSNGKDRELKKRIAADNYMSCAVREC
Gene7 -SSLCSPIKYGP---------------------------------------QCLSLCTKK
G2 -SSLCSPIKYGP---------------------------------------QCLSLCTKK
Glyma.08G361500 YASFKSIIKHLVQGEREIPVIEYMFDEVDKNIETDKLISEFRMSALPSLYAQFVELTQYL
:*: * **: * :.*
Gene7 MKLKVRDAHNLLIGIQ----------VVVNYDDNFHEPDVASG----------APSPNQN
G2 MKLKVRDAHNLLIGIH----------VVVNYDDNFHEPDVASG----------APSPNQN
Glyma.08G361500 LNNDPKDRDNVVILFQDMLEVVTRDIMMEDQDQIFSLVDSSHGGTGHEGMLHLEPEPHHQ
:: . :* .*::* :: :: : *: * * : * *.*:::
Gene7 IRSSGGSKTN--------------------------------------------------
G2 IRSTGGSKTN--------------------------------------------------
Glyma.08G361500 LFASEGAIKFPIEPLTAAWTEKIKRLHLLLTTKESAMDVPSNLEARRRISFFSNSLFMDM
: :: *: .
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 PMAPKVRNMLSFSVLTPYYTEEVLFSLHDLDSQNEDGVSILFYLQKIYPDEWNNFLERVK
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 STEEDIKGSEFDELVEERRLWASYRGQTLTRTVRGMMYYRKALELQAFLDMAKDEDLMEG
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 YKAMENSDDNSRGERSLWTQCQAVADMKFTYVVSCQQYGIDKRSGSLRAQDILRLMTRYP
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 SLRVAYIDEVEEPVQDSKKKINKVYYSCLVKAMPKSNSPSEPEQNLDQIIYKIKLPGPAI
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 LGEGKPENQNHAIIFTRGEGLQTIDMNQDNYMEEALKMRNLLQEFLKKHDGVRFPSILGL
195
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 REHIFTGSVSSLAWFMSNQETSFVTIGQRLLANPLKVRFHYGHPDVFDRLFHLTRGGVSK
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 ASKVINLSEDIFAGFNSTLREGNVTHHEYIQVGKGRDVGLNQISMFEAKIANGNGEQTLS
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 RDVYRLGHRFDFFRMLSCYFTTVGFYFSTLITVLTVYVFLYGRLYLVLSGLEEGLSTQKA
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 IRDNKPLQVALASQSFVQIGVLMALPMLMEIGLERGFRTALSEFILMQLQLAPVFFTFSL
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 GTKTHYFGRTLLHGGAKYRPTGRGFVVFHAKFADNYRLYSRSHFVKGIELMILLVVYEIF
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 GHSYRSTVAYILITASMWFMVGTWLFAPFLFNPSGFEWQKIVDDWTDWNKWISNRGGIGV
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 LPEKSWESWWEEEQEHLQYSGMRGIIVEILLSLRFFIYQYGLVYHLNITKKGTKSFLVYG
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 ISWLVIFVILFVMKTVSVGRRKFSANFQLVFRLIKGMIFLTFVSILVILIALPHMTVQDI
Gene7 ------------------------------------------------------------
G2 ------------------------------------------------------------
Glyma.08G361500 VVCILAFMPTGWGMLQIAQALKPVVRRAGFWGSVKTLARGYEIVMGLLLFTPVAFLAWFP
Gene7 --------------------------------------
G2 --------------------------------------
Glyma.08G361500 FVSEFQTRMLFNQAFSRGLQISRILGGQRKERSSRNKE
Appendix 1. Predicted β-glucan synthase amino acid sequence alignment. ClustalW peptide sequence alignment for contig1701 gene 7, predicted gene in G19833 (G2), and G. max gene annotation (Glyma08G361500). Callose synthase family domains are indicated by boxes. Transmembrane domains are highlighted in grey.
196
gene6 ----MSKTTAIQSRIIRLT---LPDRKYQNNLHNHLKLSKPQSSHSYRSYRRNLRKPHHN
Phvul.008G191100 MHFRMFKPFGLNHAGTKCWGVFGNKVVFENGRVDLVEVFTVAQRKTWSWVTVKEKSAAFS
* *. .:: : . ::*. : ::: . . ::: : :.. ..
gene6 YQN--------------
Phvul.008G191100 YSDWCLDPICCMRYLKV
*.:
Appendix 2. Alignment of P. vulgaris hypothetical proteins. ClustalW alignment of P. vulgaris hypothetical gene predictions were identified from OAC Rex and G19833 genome sequence assemblies.
Appendix 3. Protein secondary structure models for hypothetical proteins. Secondary structure models were created in Phyre2 for P. vulgaris hyothetical gene 6 (A) identified in OAC Rex contig1701, and Phvul.008G191100 (B) identified in G19833 chromosome 8.
Appendix 4. Phyre2 secondary structure modelling (Kelley and Sternberg 2009) for gene 6 and Phvul.008G191100
Gene Name Amino Acids
Modelled Template
Template
Characteristic
Similarity to
Template Confidence
Gene 6 23-49 C4ImgD_ Transcriptional activator 33% 15.2%
Phvul.008G191100 11-33 D2f9ca1 Single-stranded left-handed
beta-helix fold 29% 32.0%
29-65 D1m0da_ Restriction endonuclease-like 27% 12.5%
197
Appendix 5. Analysis of variance for inoculated detached common bean (P. vulgaris) leaves maintained in a water agar tissue culture system. Significance (p < 0.05) of fixed treatment, treatment interaction and error effects are shown. Genotypes include resistant (OAC Rex) and susceptible (Nautica) common bean varieties. Leaves were inoculated with one of four Xanthomonas axonopodis pv. phaseoli isolates (Xap12, Xap18, Xap98 or Xap118) or water control. Leaves were maintained in a water agar tissue culture system at 28oC for up to 192 hours post inoculation (HPI) and samples were taken at different time points post inoculation (0, 48, 96, 144 and 192 HPI). Source df F-value P > F
Inoculum 4 36.55 <0.0001
Genotype 1 47.42 <0.0001
Time 4 14.73 <0.0001
Inoculum x Genotype 4 3.89 0.0059
Inoculum x Time 16 2.57 0.0025
Genotype x Time 4 4.72 0.0017
Inoculum x Genotype x Time 16 1.41 0.1530
Error 41
Appendix 6. Analysis of variance for inoculated detached Arabidopsis thaliana rosette leaves maintained in a water agar tissue culture system. Significance (p < 0.05) of fixed treatment, treatment interaction and error effects are shown. Leaves were inoculated with one of four Xanthomonas axonopodis pv. phaseoli isolates (Xap12, Xap18, Xap98 or Xap118) or water control. Leaves were maintained in a water agar tissue culture system at 28oC for up to 192 hours post inoculation (HPI) and samples were taken at different time points post inoculation (0, 48, 96, 144 and 192 HPI).
Source df F-value P > F
Inoculum 4 21.57 <0.0001
Time 4 11.21 <0.0001
Inoculum x Time 16 2.58 0.0055
Error 26
198
Appendix 7. LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 0 hours post inoculation (HPI). Percent of leaf showing disease symptoms for OAC Rex, Nautica and Arabidopsis leaves inoculated with Water, Xap12, Xap18, Xap98 and Xap118 at 0 HPI
Genotype
Symptoms (%)
Inoculum
Water Xap12 Xap18 Xap98 Xap118 Genotype
Mean
OAC Rex 4.26 x10-2 YZ
a 7.26 x10-2 Y a 7.37 x10
-2 Y a 8.53 x10
-2 Y a 4.33 x10
-2 Y a 6.35 x10
-2 WX
A
Nautica 0.120Y a 0.154
Y a 7.29 x10
-2 Y a 6.23 x10
-2 Y a 5.91 x10
-2 Y a 9.37 x10
-2 W
A
Arabidopsis 0.297 V z 0.236
V z 0.318
V z 0.186
V z 0.367
V z 0.281
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +127.80
WDenotes lsmeans with a standard error of +57.1532
VDenotes lsmeans with a standard error of +3.06
UDenotes lsmeans with a standard error of +1.37
Appendix 8. LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 48 hours post inoculation (HPI). Percent of leaf showing disease symptoms for OAC Rex, Nautica and Arabidopsis leaves inoculated with Water, Xap12, Xap18, Xap98 and Xap118 at 48 HPI
Genotype
Symptoms (%)
Inoculum
Water Xap12 Xap18 Xap98 Xap118 Genotype
Mean
OAC Rex 0.138YZ
a 0.315Y a 9.64 x10
-2 y a 0.276
Y a 0.405
Y a 0.246
WX A
Nautica 0.156Y a 0.335
Y a 0.349
Y a 0.177
Y a 0.657
Y a 0.335
W A
Arabidopsis 0.255 V z 1.26
V z 0.433
V z 0.367
V z 0.973
V z 0.656
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +127.80
WDenotes lsmeans with a standard error of +57.1532
VDenotes lsmeans with a standard error of +3.06
UDenotes lsmeans with a standard error of +1.37
199
Appendix 9. LSmeans for common bacterial blight symptoms on OAC Rex, Nautica and Arabidopsis leaves at 96 hours post inoculation (HPI). Percent of leaf showing disease symptoms for OAC Rex, Nautica and Arabidopsis leaves inoculated with Water, Xap12, Xap18, Xap98 and Xap118 at 96 HPI
Genotype
Symptoms (%)
Inoculum
Water Xap12 Xap18 Xap98 Xap118 Genotype
Mean
OAC Rex 0.627YZ
a 1.42Y a 3.56
Y a 3.25
Y a 3.18
Y a 2.41
WX A
Nautica 2.10Y a 3.20
Y a 4.74
Y a 2.40
Y a 2.34
Y a 2.96
W A
Arabidopsis 0.460V z 4.44
V z 5.46
V z 4.74
V z 1.02
V z 3.22
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +127.80
WDenotes lsmeans with a standard error of +57.1532
VDenotes lsmeans with a standard error of +3.06
UDenotes lsmeans with a standard error of +1.37
Appendix 10. LSmeans for colony forming units for X. axonopodis pv. phaseoli (Xap) bacteria at 0 hours post inoculation (HPI). CFU was determined by incubating 105 dilutions of ground leaf samples taken from inoculated leaves from resistant (OAC Rex) and susceptible (Nautica) P. vulgaris varieties, and Arabidopsis. Samples were taken at 0 HPI after inoculation with Water, Xap12, Xap18, Xap98 or Xap118.
Genotype
CFU (x 105)
Inoculum
Water Xap12 Xap18 Xap98 Xap118 Genotype
Mean
OAC Rex 0XZ
a 173 X a 0
X a 452
X a 147
X a 154
WY A
Nautica 0X a 280
X a 430
X a 142
X a 0
X a 170
Y A
Arabidopsis 0V z 0
V z 217
V z 122
V z 31.7
V z 74.1
U
ZLsmeans followed by the same lower case letter were not significantly different at p=0.05
YLsmeans followed by the same upper case letter were not significantly different at p=0.05
XDenotes lsmeans with a standard error of +174
WDenotes lsmeans with a standard error of +77.9
VDenotes lsmeans with a standard error of +96.3
UDenotes lsmeans with a standard error of +43.1
200
Appendix 11. Candidate gene expression in first experiment replication of Phaseolus vulgaris leaf inoculation. Expression of candidate genes CBB2, CBB3 and CBB4 were compared to expression of actin check in resistant (OAC Rex) and susceptible (Seaforth) common bean varieties. The inoculum used was X. axonopodis pv. phaseoli isolate 98 (X) and sterile distilled water (C). RNA was isolated from leaf samples taken from water and Xanthomonas-inoculated OAC Rex and Seaforth plants at 0, 12, 24, and 48 hours post-inoculation (HPI). OAC Rex genomic DNA and sterile distilled water were used as positive (+) and negative (-) PCR controls, respectively. Candidate gene bands were produced using primers CBB2CS, CBB3CS and CBB4CS for CBB2, CBB3 and CBB4, respectively. Band size is indicated by a white arrow for actin, yellow arrow for CBB2, red arrow for CBB3 and green arrow for CBB4.
201
