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Theor Appl Genet (2009) 119:1193–1204
DOI 10.1007/s00122-009-1120-4ORIGINAL PAPER
Exploiting rice–sorghum synteny for targeted development of EST-SSRs to enrich the sorghum genetic linkage map
P. Ramu · B. Kassahun · S. Senthilvel · C. Ashok Kumar · B. Jayashree · R. T. Folkertsma · L. Ananda Reddy · M. S. Kuruvinashetti · B. I. G. Haussmann · C. T. Hash
Received: 6 March 2009 / Accepted: 20 July 2009 / Published online: 8 August 2009© Springer-Verlag 2009
Abstract The sequencing and detailed comparative func-tional analysis of genomes of a number of select botanicalmodels open new doors into comparative genomics amongthe angiosperms, with potential beneWts for improvement ofmany orphan crops that feed large populations. In thisstudy, a set of simple sequence repeat (SSR) markers wasdeveloped by mining the expressed sequence tag (EST)database of sorghum. Among the SSR-containingsequences, only those sharing considerable homology withrice genomic sequences across the lengths of the 12 ricechromosomes were selected. Thus, 600 SSR-containingsorghum EST sequences (50 homologous sequences on
each of the 12 rice chromosomes) were selected, with theintention of providing coverage for corresponding homolo-gous regions of the sorghum genome. Primer pairs weredesigned and polymorphism detection ability was assessedusing parental pairs of two existing sorghum mappingpopulations. About 28% of these new markers detected poly-morphism in this 4-entry panel. A subset of 55 polymorphicEST-derived SSR markers were mapped onto the existingskeleton map of a recombinant inbred population derivedfrom cross N13 £ E 36-1, which is segregating for Strigaresistance and the stay-green component of terminaldrought tolerance. These new EST-derived SSR markersmapped across all 10 sorghum linkage groups, mostly toregions expected based on prior knowledge of rice–sorghum synteny. The ESTs from which these markers werederived were then mapped in silico onto the alignedsorghum genome sequence, and 88% of the best hitscorresponded to linkage-based positions. This study
Communicated by T. Sasaki.
P. Ramu and B. Kassahun contributed equally to this work.
Electronic supplementary material The online version of this article (doi:10.1007/s00122-009-1120-4) contains supplementary material, which is available to authorized users.
P. Ramu · B. Kassahun · S. Senthilvel · C. Ashok Kumar · B. Jayashree · R. T. Folkertsma · C. T. Hash (&)M. S. Swaminathan Applied Genomics Laboratory, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), ICRISAT-Patancheru PO, Hyderabad, Andhra Pradesh 502 324, Indiae-mail: [email protected]
P. Ramu · L. A. ReddyDepartment of Genetics, Osmania University, Hyderabad, Andhra Pradesh 500 007, India
B. Kassahun · M. S. KuruvinashettiUniversity of Agricultural Sciences, Dharwad, Karnataka 580 005, India
B. KassahunCollege of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Ethiopia
Present Address:C. Ashok KumarDepartment of Plant Pathology & Crop Physiology, Louisiana State University, Baton Rouge, LA 70803, USA
R. T. FolkertsmaDepartment of Phytopathology, De Ruiter Seeds, Leeuwenhoekweg 52, 2661 CZ, Bergschenhoek, The Netherlands
B. I. G. HaussmannInternational Crops Research Institute for the Semi-Arid Tropics (ICRISAT), BP 12404, Niamey, Niger
123
1194 Theor Appl Genet (2009) 119:1193–1204
demonstrates the utility of comparative genomic informa-tion in targeted development of markers to Wll gaps in link-age maps of related crop species for which suYcientgenomic tools are not available.
Introduction
Sorghum [Sorghum bicolor (L.) Moench, 2n = 20] is one ofthe most important cereal crops and well adapted to harshenvironments characterized by drought and high tempera-tures. In addition to being an important source of caloriesfor millions of poor people living in the semi-arid tropics ofAfrica and Asia, and an essential livestock feed there andelsewhere, sorghum has been identiWed as a potentialsource of bio-fuel (Antonopoulou et al. 2008). Sorghum isa model organism for tropical grasses having the ‘C4’ pho-tosynthetic pathway and is a logical complement to the ‘C3’grass Oryza sativa (Kresovich et al. 2005), which was theWrst monocot with a completely sequenced genome (GoVet al. 2002; Yu et al. 2002; International Rice GenomeSequencing Project 2005). Sorghum has a relatively smallgenome (»760 Mb; Arumuganathan and Earle 1991) that isless complex than those of other major C4 crops like maize(Zea mays L.) and sugarcane (Saccharum oYcinarum).Genome sequencing of sorghum was initiated at the end of2005 through the ‘Community sequencing program ofDepartment of Energy-Joint Genome Institute, USA’ andduring the course of this study the complete alignedgenome sequence (8£) information for this species wasmade available to public use (Paterson et al. 2009; http://www.jgi.doe.gov/sorghum). This has provided an opportu-nity to better understand genome organization in sorghum,its wild relatives including Johnson grass (Sorghum hale-pense), and even maize.
Sorghum is the Wrst species in the crop improvementmandate of the International Crops Research Institute forthe Semi-Arid Tropics (ICRISAT) for which a reasonableamount of genomic tools are available that can be exploitedfor applied crop improvement. Construction of molecularmarker-based linkage maps in sorghum started during the1990s with restriction fragment length polymorphism(RFLP) markers (Hulbert et al. 1990; Pereira et al. 1994;Chittenden et al. 1994; Ragab et al. 1994; Xu et al. 1994;Dufour et al. 1997; Tao et al. 1998a; Peng et al. 1999) fol-lowed by maps adding other marker systems like ampliWedfragment length polymorphism (AFLP), simple sequencerepeat (SSR), and recently diversity array technology(DArT) markers (Boivin et al. 1999; Kong et al. 2000;Bhattramakki et al. 2000; Klein et al. 2000; Subudhi andNguyen 2000; Haussmann et al. 2002a; Menz et al. 2002;Bowers et al. 2003; Mace et al. 2008). Several genomicregions associated with important agronomic traits including
a range of abiotic stress tolerances [primarily mid-seasonand terminal drought tolerance (Tuinstra et al. 1996, 1997;Crasta et al. 1999; Subudhi et al. 2000; Tao et al. 2000; Xuet al. 2000; Kebede et al. 2001; Haussmann et al. 2002b;Sanchez et al. 2002; Harris et al. 2007) and aluminumtolerance (Magalhaes et al. 2004)], host plant resistances tohemi-parasitic weeds [Striga spp. (Haussmann et al.2004)], insect pests [aphids (Agrama et al. 2002; Katsaret al. 2002; Nagaraj et al. 2005; Wu et al. 2007), midge(Tao et al. 2003), and shoot Xy (Folkertsma et al. 2003)],and diseases [of both foliage (Oh et al. 1996; Tao et al.1998b; Nagy et al. 2007) and panicles (Klein et al. 2001)],and a range of traits related to grain quality (Lijavetskyet al. 2000), crop phenology [height and maturity (Lin et al.1995; Pereira and Lee 1995; Klein et al. 2001; Feltus et al.2006a)], and yield components (Hart et al. 2002; Hickset al. 2002) have been mapped. Now high-density geneticmaps are available for sorghum (Klein et al. 2000; Bowerset al. 2003). However, these maps have some signiWcantgaps and many genomic regions are covered by only AFLPand RFLP markers. At the onset of this study there werecirca 300 publicly available primer pair sequences formapped sorghum SSR loci (Brown et al. 1996; Taraminoet al. 1997; Kong et al. 2000; Bhattramakki et al. 2000;Menz et al. 2002; Schloss et al. 2002).
SSR markers have clear advantages over RFLP andAFLP markers in terms of technical simplicity, throughputlevel and automation (Varshney et al. 2005). SSRs are thepreferred marker system for many breeding applications.Hence, enriching the existing sorghum linkage map withmore SSR markers is a valuable objective for the sorghumbreeding community globally. Conventional SSR markerdevelopment is a costly and time-consuming process.Thanks to the availability of genomic or expressedsequence tag (EST) sequences in public databases and therecent advent of bioinformatics tools, SSR marker develop-ment has become easier and more cost-eVective (e.g.,Jayashree et al. 2006). In the past, SSR markers have beensuccessfully developed by mining EST databases in severalcrops (reviewed in Varshney et al. 2005). EST-SSRs are ahighly valued marker system as they are developed fromtranscribed portions of the genome and often target func-tional diversity. They are also superior in terms of cross-species transferability, and thus are well suited for applica-tion in phylogenetic analysis and comparative genomemapping. The transfer rate of EST-SSR markers from sor-ghum to paspalum (Paspalum spp.) and to maize was 68and 61%, respectively (Wang et al. 2005).
The rice genome exhibits substantial collinearity withthe genomes of other grasses, such as sorghum, maize,wheat (Triticum aestivum L.), and barley (Hordeum vulg-are L.) (Ahn et al. 1993; Chen et al. 2002; Devos and Gale1997; Tarchini et al. 2000). A direct comparison of the
123
Theor Appl Genet (2009) 119:1193–1204 1195
genetic linkage maps of sorghum and rice has been per-formed by Ventelon et al. (2001) using the mapping infor-mation of a common set of RFLP probes. Klein et al.(2003) indicated that the overall architecture of sorghumchromosome 3 and rice chromosome 1 has remainedlargely intact with the exception of one major rearrange-ment. The sorghum genome has now been reasonablyaligned with that of rice through comparative genetic, cyto-genetic, and physical mapping approaches (Draye et al.2001; Bowers et al. 2005, Kim et al. 2005a, Paterson et al.2009). In this study, we attempted to develop a set of EST-SSR markers that are expected to provide coverage forgene-rich regions of the entire nuclear genome using com-parative genomic information from rice as the sorghumgenome sequence information was not available when thestudy was initiated.
Materials and methods
Data mining of sorghum ESTs
Sorghum EST sequences were downloaded in FASTA for-mat from the J. Craig Venter Institute [formerly, The Insti-tute for Genome Research (TIGR)] database (http://www.tigr.org) as of May 2004. The identiWcation of micro-satellites from these EST sequences was carried out usingSSRIT (www.gramene.org/db/searches/ssrtool), and simplescripts (written in Visual Basic) to parse SSRIT output intothe relational database. CAP3 (Huang and Madan 1999)was used to identify the non-redundant EST sequences.Non-redundant sorghum EST sequences containing SSRswere then obtained from this local database and used in thisstudy.
Selection of candidate ESTs and primer design
Non-redundant sorghum EST sequences containing micro-satellites were BLAST searched against the rice genomesequence available in the GRAMENE database (http://www.gramene.org/db/searches/blast) as of May 2004. Eachrice chromosome was divided into Wve arbitrary regionsviz., ‘top’, ‘middle, ‘bottom’, ‘between top and middle’,and ‘between middle and bottom’. The ten top-scoring sor-ghum EST sequences for each region of the rice chromo-some were picked. Thus, a total of 600 SSR-containingEST sequences of sorghum (10 each for each region of the12 rice chromosomes) having sequence homology with ricesequences were identiWed. These 600 candidate EST-SSRsequences were expected to sparsely cover the entirenuclear genome of rice, and thereby the corresponding sor-ghum genomic regions. Primer pairs were designed fromthe selected 600 non-redundant sorghum EST-SSR
sequences using Primer3 (http://biotools.umassmed.edu/bioapps/primer3_www.cgi) after masking the repeat units.The primer pairs were designed with the following condi-tions: primer length (min-18nt, opt-22nt, max-24nt), Tm(min-54°C, opt-57°C, max-60°C), and GC content (min-45,opt-50, max-60%).
Primer optimization and polymorphism assessment
PCR conditions for the EST-SSR primer pairs were opti-mized using template DNA of genetically diverse parentalpairs of two sorghum mapping populations available atICRISAT, Patancheru viz., N13 £ E 36-1 and BTx623 £IS 18551. N13 is Striga resistant while E 36-1 is stay-green, drought tolerant, and Striga susceptible. BTx623 isan elite hybrid parental line chosen for genome sequencing(Paterson et al. 2009). It is susceptible to shoot Xy andbeing used as the recurrent parent for ICRISAT’s explor-atory shoot Xy resistance marker-assisted backcrossing pro-gram. IS 18551 is a shoot Xy resistant donor parent beingused by ICRISAT for shoot Xy resistance QTL mappingand marker-assisted backcrossing. DNA of parental lineswas isolated using a high-throughput DNA extractionprotocol as reported by Mace et al. (2003) and normalizedto a working concentration of 5 ng/�l.
PCR was performed in 5 �l reaction volume with Wnalconcentrations of 2.5 ng DNA, 2 mM MgCl2, 0.1 mM ofdNTPs, 1£ PCR buVer, 0.4 pM of each primer, and 0.1 Uof Taq DNA polymerase (AmpliTaq Gold®, Applied Bio-systems, USA) in a GeneAmp® PCR System 9700 thermalcycler (Applied Biosystems, USA) with the followingcyclic conditions: initial denaturation at 94°C for 15 min(to activate Taq DNA polymerase) then 10 cycles of dena-turation at 94°C for 15 s, annealing at 61°C for 20 s (tem-perature reduced by 1°C for each cycle), and extension at72°C for 30 s. This was followed by 34 cycles of denatur-ation at 94°C for 10 s, annealing at 54°C for 20 s, andextension at 72°C for 30 s with the Wnal extension of20 min at 72°C. AmpliWed PCR products were resolved on6% native polyacrylamide gels coupled with silver stainingas described by Tegelstrom (1992).
Mapping of EST-SSRs
The polymorphic markers were subsequently mapped usingrecombinant inbred lines (RILs) of N13 £ E 36-1 (Hauss-mann et al. 2004). The markers polymorphic between N13and E 36-1 were surveyed on a subset of 94 F3-derived F5
RILs. The segregation data were used to place the newmarkers on to the existing skeleton map with 164 previ-ously mapped RFLP, AFLP, RAPD, and SSR markers(Haussmann et al. 2002a, 2004) at LOD score of 3.0 usingMapmaker 3.0v (Lander et al. 1987). The Haldane mapping
123
1196 Theor Appl Genet (2009) 119:1193–1204
function (Haldane 1919) was used to convert recombina-tion frequency into linkage map distance. The linkagegroups were oriented and designated following Kim et al.(2005b).
In silico mapping of ESTs
Aligned sorghum genome sequence information (Sbi 1.4)for elite sorghum inbred BTx623 was made available forpublic use (http://www.jgi.doe.gov/sorghum) during thecourse of this study (Paterson et al. 2009). This aligned sor-ghum genome sequence information was downloaded andformatted into a database. All mapped SSR-containing ESTsequences (55 markers) were searched against this databaseusing Paracel BLAST (Altschul et al. 1990) on a ParacelHigh Performance Computing system. These sequenceswere then aligned on to the sequence-based physical mapaccording to their hit location on each linkage group.
Results
Data mining of sorghum ESTs
In the TIGR database, about 187,282 sorghum ESTsequences were available when this study was initiated. WeidentiWed 39,106 EST sequences with SSRs using theSSRIT tool. These sequences were clustered using theCAP3 program to identify 10,044 non-redundant ESTsequences containing microsatellites.
A set of 1,486 non-redundant sorghum EST sequencescontaining microsatellites were BLAST searched against therice genome in the GRAMENE database. From the sequencesimilarity search, 150 sorghum EST sequences had no hitson rice genome sequence; 180 sequences had homology withsequences on rice chromosome 1; 130 on chromosome 2,243 on chromosome 3, 98 on chromosome 4, 115 on chro-mosome 5, 77 on chromosome 6, 67 on chromosome 7, 66each on chromosomes 8 and 9, 71 on chromosome 10, 144on chromosome 11, and 79 on chromosome 12. On eachchromosome, 50 sorghum SSR-containing EST sequenceswith highest BLAST search score that provided coverageacross the entire length of each rice chromosome were iden-tiWed. Thus, 1,486 non-redundant EST sequences wereBLAST searched against the rice genome to identify 600sequences (50 per rice chromosome). Primer pairs Xankingthe SSR motifs were designed using Primer3. These primerpairs were designated as ‘ICRISAT Sorghum EST Primers(ISEP)’ (listed as electronic supplementary information S1).Among the selected 600 SSR-containing sorghum ESTsequences, 470 (78%) sequences have putative annotations.The majority of these are classiWed as transcription factors orDNA binding proteins.
Out of the 600 sorghum EST-SSR markers developed,63 were di-nucleotide repeats (10.5%); 425 were tri-nucleo-tide repeats (70.8%); 78 were tetra-nucleotide repeats(13.0%); and 34 were penta-nucleotide repeats (5.6%). Themost abundant repeats among the selected EST sequenceswere AG and CCG. A total of 79 SSR motifs (13%) were ofClass I type of SSRs (¸20 nucleotides in length) and 496SSR motifs were Class II type of SSRs (>12 but <20 nucle-otides in length), and remaining 25 SSR motifs were 10nucleotides in length. Further details on SSR frequency anddistribution in the set of EST sequences used here havebeen published by Jayashree et al. (2006).
Primer optimization and polymorphism assessment
PCR conditions for the 600 primer pairs were optimizedusing template DNA from the four inbred parental lines ofthe two mapping populations, and parental polymorphismwas simultaneously scored. Out of 600 primer pairs, 457(76.1%) ampliWed the template and 386 (84.5%) producedsimple and easy to score ampliWcation products, whereasthe remaining 15.5% of template-amplifying primer pairsproduced multiple fragments that were diYcult to score.Most of the primer pairs that produced no ampliWcation orgave non-speciWc ampliWcation were targeting tri-nucleo-tide repeats. Of the 386 primer pairs that produced goodampliWcation proWles, 133 primer pairs (34.5%) detectedpolymorphism between N13 and E 36-1 and 140 primerpairs detected polymorphism between BTx623 andIS 18551 (listed as electronic supplementary informationS1). In both crosses, di-nucleotide repeats were found mostpolymorphic (30–38%), followed by tetra-nucleotiderepeats in the N13 £ E 36-1 cross, and penta-nucleotiderepeats in the BTx623 £ IS 18551 cross.
Mapping of EST-SSRs
The polymorphic markers were surveyed on 94 RILsderived from the cross N13 £ E 36-1 and the segregationdata were scored. A total of 55 EST-SSR markers wereadded (Table 1) to the existing skeleton map of this map-ping population. These markers mapped to all 10 sorghumlinkage groups and were well-distributed within each link-age group except in the case of SBI-06 for which the newlymapped markers clustered along the bottom of the linkagegroup in a region corresponding to the long arm of the sor-ghum chromosome. Among these 55 newly mapped EST-SSR markers, 9 mapped to SBI-09, 8 markers each mappedto SBI-02 and SBI-03, 7 mapped to SBI-01, 6 markers eachmapped on SBI-04 and SBI-07, 3 markers each mapped onSBI-05, SBI-06, and SBI-10, and 2 markers mapped onSBI-08, with an average of 5.5 EST-SSR markers per link-age group. The linkage map augmented with these 55
123
Theor Appl Genet (2009) 119:1193–1204 1197
Tab
le1
Det
ails
of
55 g
enet
ical
ly m
appe
d so
rghu
m E
ST-S
SR
mar
kers
and
thei
r co
rres
pond
ing
phys
ical
map
loca
tions
on
the
alig
ned
sorg
hum
gen
ome
sequ
ence
Mar
ker
Sor
ghum
ES
T
sequ
ence
ID
Rep
eat
mot
ifF
orw
ard
prim
er s
eque
nce
(5�–
3�)
Rev
erse
pri
mer
seq
uenc
e (5
�–3�
)A
ppro
x.
ampl
icon
si
ze in
B
Tx6
23 (
bp)
Ali
gnm
ent p
osit
ion
on r
ice
geno
me
sequ
ence
BL
AST
sc
ore
Lin
kage
gr
oup
Phy
sica
l m
ap
posi
tion
Xis
ep01
01A
W67
9887
TG
(9)
CA
GA
TC
TC
CG
GT
TG
AA
GA
GC
TG
AG
CC
GA
GC
TC
AA
CA
TA
CA
205
chr1
: 193
1190
-128
4781
013
50S
BI-
03S
BI-
03
Xis
ep01
02A
W56
5338
AA
G(4
)C
GC
TG
GA
GT
AC
CA
GA
GG
AA
GA
AC
AA
AA
TC
CG
AG
CC
TG
TT
G68
0ch
r1: 4
1937
5-22
7804
7896
8S
BI-
03S
BI-
03
Xis
ep01
07A
W74
4864
TG
G(4
)G
CC
GT
AA
CA
GA
GA
AG
GA
TG
GT
TT
CC
GC
TA
CC
TC
AA
AA
AC
C20
5ch
r1: 4
9463
97-4
9468
6271
1S
BI-
03S
BI-
03
Xis
ep01
10B
E36
0507
CG
(6)
GA
GG
GG
AA
GC
TG
GA
GA
CC
TC
AA
GT
GT
AC
AA
CG
CA
TC
CA
G48
0ch
r1:
8105
89-3
1327
180
1821
SBI-
09SB
I-03
Xis
ep01
38A
W92
3239
TA
(6)
GA
GA
TC
GA
GA
GG
CA
CT
TT
GG
CA
GC
GA
CA
AG
CC
AA
TA
CC
A21
0ch
r1: 4
0999
721-
4128
3498
1349
SB
I-03
SB
I-03
Xis
ep02
02A
W67
9616
TG
A(7
)C
AA
CC
TG
TG
AT
TG
AC
CC
AT
TT
AA
AC
AT
GT
CC
AG
AT
TC
AT
CA
AG
G19
5ch
r2: 3
9576
94-3
9583
7612
35S
BI-
04S
BI-
04
Xis
ep02
24A
W56
3693
CT
G(4
)A
CT
GG
GG
TT
CC
TT
TT
CC
TG
TT
CC
CT
GA
TT
TC
CC
CT
CT
TT
T20
0ch
r2: 1
3206
311-
2603
7486
824
SB
I-04
SB
I-04
Xis
ep02
28B
E35
6910
GA
GG
(3)
GA
CA
TG
GC
CA
GC
TA
AG
AG
GA
CC
AT
GC
AG
TG
AT
CG
TT
GT
GT
220
chr2
: 763
5368
-305
6099
474
6S
BI-
04S
BI-
04
Xis
ep03
10A
W28
6133
CC
AA
T(4
)T
GC
CT
TG
TG
CC
TT
GT
TT
AT
CT
GG
AT
CG
AT
GC
CT
AT
CT
CG
TC
200
chr3
: 104
7959
7-10
4800
1771
1S
BI-
02S
BI-
02
Xis
ep03
14B
E35
8851
GC
C(4
)G
TT
CG
AC
GA
CG
AC
GA
CC
TG
TC
CT
CG
AA
CC
CG
AC
CT
T40
5ch
r3:
1696
130-
2881
2187
730
SBI-
10SB
I-01
Xis
ep03
27A
W68
0959
GT
T(4
)C
TG
TT
TG
TG
CT
TG
CA
AC
TC
CT
CA
TC
GA
TG
CA
GA
AC
TC
AC
C20
0/21
0ch
r3: 1
6826
707-
3071
4737
730
SB
I-01
SB
I-01
Xis
ep03
28B
E35
9052
AA
G(4
)C
AT
CT
TC
CT
CC
GT
CA
AC
CA
TA
TC
CT
GC
GA
CC
CT
TC
TC
AC
300
chr3
: 207
5686
8-33
4796
0114
19S
BI-
07S
BI-
07
Xis
ep04
22A
W28
5124
GC
AT
(3)
TG
CC
CG
TA
AT
TA
AG
CC
CA
TA
CC
CA
CT
GC
TC
CA
GG
TA
AG
AA
300
chr4
: 281
0717
-300
5033
541
0S
BI-
06S
BI-
06
Xis
ep04
39A
W74
5664
GA
C(4
)T
AG
TC
GA
AG
CA
GC
AG
TC
GT
GG
TG
TT
CA
AG
TT
CG
AC
GA
GC
A62
0ch
r4: 3
1792
724-
3183
2792
863
SB
I-07
SB
I-07
Xis
ep04
43B
E35
5584
GC
A(7
)T
CA
TG
TA
CA
GA
GG
CG
AC
AC
GA
GG
TC
GC
AA
CA
GA
CA
CC
TT
C19
0ch
r4: 2
9104
052-
2912
2456
734
SB
I-06
SB
I-06
Xis
ep04
49B
E35
7875
TC
A(7
)C
CG
CT
CA
TC
AG
TC
AT
CA
CA
TA
CA
AA
AT
CC
AT
CC
CA
CA
AC
G20
0ch
r4: 3
6595
7-34
7436
4618
08S
BI-
06S
BI-
06
Xis
ep05
06A
W92
2528
AA
CG
(3)
CG
TG
CA
AG
TT
TG
GA
AT
TT
GT
CC
GG
GC
AG
GT
AT
AA
GG
TG
TT
G22
5/43
0ch
r5: 2
0763
88-4
4028
6669
7S
BI-
09S
BI-
09
Xis
ep05
13A
W74
5388
GG
C(5
)G
AG
GG
AA
GA
AG
AA
AA
CC
CA
GA
AG
CC
TC
TC
CT
CC
TC
CT
CC
T30
0ch
r5: 8
0303
4-17
0974
8710
53S
BI-
09S
BI-
09
Xis
ep05
22B
E36
1646
CA
G(8
)T
CA
TG
GA
CC
GT
GT
CA
TC
GG
CG
TA
CT
TG
CT
CC
AC
CT
CT
C33
0ch
r5:
1594
3072
-221
6622
611
10SB
I-04
SBI-
02
Xis
ep05
23B
E35
8885
TG
C(4
)A
CG
AC
AT
GG
AC
GA
CA
TC
AG
AA
AC
AA
AA
AC
AC
AC
GG
GA
AG
G22
0/30
5ch
r5: 1
7631
682-
1763
2292
911
SB
I-09
SB
I-09
Xis
ep05
50A
W74
6901
GA
(11)
GC
GG
CG
AG
AG
AG
AG
AG
TT
CC
GA
GC
TT
GA
TC
TT
CT
CG
TT
GA
185
chr5
: 303
9650
-253
3801
867
0S
BI-
09S
BI-
09
Xis
ep06
07A
W92
3923
AG
A(4
)C
AC
GA
GG
AT
TT
CA
CC
AA
AC
CT
GC
AC
GT
GT
TC
GA
AA
TA
GG
A19
5ch
r6: 2
2385
20-2
2406
3154
3S
BI-
10S
BI-
10
Xis
ep06
08B
E35
5471
AG
A(4
)T
TT
CA
CC
AA
AC
CA
AG
CT
AA
GG
GT
AG
AG
GC
AG
CC
CT
TC
TC
CT
205
chr6
: 22
3852
0-22
4063
154
3SB
I-04
SBI-
10
Xis
ep06
32B
E35
5933
CA
TG
(4)
AG
AG
AG
GA
GG
TC
CC
AA
AT
GC
TT
AA
GG
CC
CA
AA
CA
AA
CT
GG
195
chr6
: 890
8340
-281
2850
372
9S
BI-
08S
BI-
08
Xis
ep06
39B
E35
7831
TC
T(6
)T
CG
GA
CG
GA
GT
CA
TC
AG
AT
AG
CC
TT
CG
TG
TC
TT
CT
GT
CC
T20
0ch
r6: 2
6216
943-
2646
0093
628
SB
I-10
SB
I-10
Xis
ep07
01B
E36
0023
TT
CT
T(3
)C
GG
TG
GG
AG
AG
AC
AG
AG
AG
AC
CA
AT
CA
AT
AC
CA
CT
CC
TG
TG
A20
0ch
r7: 4
0610
86-4
0614
4712
28S
BI-
02S
BI-
02
Xis
ep07
04A
W68
0310
GT
(5)
CA
AG
TC
CG
TC
GT
GC
TA
GA
GG
CC
CT
TT
AA
TT
AG
CC
CC
AA
AC
A20
0ch
r7: 5
2476
30-5
2479
4390
8S
BI-
07S
BI-
07
Xis
ep07
33B
E35
7808
TG
TA
A(5
)G
TG
AT
GC
AT
CT
CA
CG
GA
CA
GG
CA
GC
TA
CT
GC
AT
GC
TT
GT
C40
0ch
r7: 2
2294
109-
2698
5575
1443
SB
I-02
SB
I-02
Xis
ep07
47B
E35
7135
TC
C(5
)A
GG
CA
GC
CT
GC
TT
AT
CA
CA
AA
CA
AG
CT
CA
GG
TG
GG
TG
GT
210
chr7
: 372
151-
2672
6597
897
SB
I-02
SB
I-02
Xis
ep08
09A
W74
7322
TA
TG
(4)
GG
AA
AC
TC
TT
GT
GG
GT
TG
GA
TT
GA
CC
TC
TC
TA
CA
AA
TG
AT
CC
AC
200
chr8
: 102
2442
-102
2570
221
SB
I-08
SB
I-08
Xis
ep08
24A
W56
4458
CC
G(4
)T
CC
TG
AA
AG
AA
AC
GC
AC
AC
AG
AG
GA
GG
GT
GT
GG
AG
GT
GT
A20
0ch
r8: 1
3585
814-
1358
6034
428
SB
I-03
SB
I-03
Xis
ep08
29B
E12
5697
AG
(6)
CG
CT
GC
CA
AA
AT
CT
AA
GC
TC
CA
CG
GT
GG
TC
AC
AT
CA
GA
AG
205/
243
chr8
: 277
3824
4-27
7385
5412
25S
BI-
07S
BI-
07
Xis
ep08
31B
E36
0943
AA
AA
G(3
)T
CC
AT
GA
CC
TT
GA
GG
AG
GA
GT
TG
AA
GC
AG
GA
CA
AC
AC
AC
C20
0ch
r8: 2
4781
619-
2478
1723
943
SB
I-07
SB
I-07
Xis
ep08
39B
E35
7549
AT
TA
C(4
)T
AC
GC
AT
AG
CG
CC
TT
TC
AA
TA
TT
TC
AT
TA
TG
CC
GG
TC
TC
G20
0ch
r8: 2
7711
931-
2771
2047
378
SB
I-01
SB
I-01
Xis
ep08
41B
E35
8373
GC
A(1
0)T
AG
GA
AT
GA
CG
AC
AC
CA
CC
AC
AA
AG
GC
AA
GG
GT
TT
TG
CT
A21
0ch
r8: 2
4665
284-
2466
5519
299
SB
I-02
SB
I-02
123
1198 Theor Appl Genet (2009) 119:1193–1204
Tab
le1
cont
inue
d
Mar
kers
conX
ictin
g in
phy
sica
l and
link
age
map
pos
itio
ns a
re h
ighl
ight
ed in
bol
d
Mar
ker
Sor
ghum
EST
se
quen
ce I
DR
epea
t m
otif
For
war
d pr
imer
seq
uenc
e (5
�–3�
)R
ever
se p
rim
er s
eque
nce
(5�–
3�)
App
rox.
am
plic
on
size
in
BT
x623
(bp
)
Ali
gnm
ent p
osit
ion
on r
ice
geno
me
sequ
ence
BL
AS
T
scor
eL
inka
ge
grou
pPh
ysic
al
map
po
siti
on
Xis
ep08
43B
E35
7146
AG
CT
G(3
)C
CC
AA
AC
AT
TC
CC
AC
GT
AA
CG
TG
AA
CA
GA
GG
AG
GC
AG
AG
G20
0ch
r8: 2
9918
52-2
4982
703
993
SB
I-03
SBI-
03
Xis
ep08
44B
E35
6742
CG
T(4
)G
TG
TT
CA
AG
TT
CG
AC
GA
GC
AT
AG
TC
GA
AG
CA
GC
AG
TC
GT
G60
0ch
r8: 1
6414
13-2
5156
453
941
SB
I-07
SBI-
07
Xis
ep09
38A
W74
7241
TG
GG
T(6
)T
GC
TG
TT
CT
TG
AA
CG
TG
TT
TG
TT
TT
GC
AC
AA
AG
TT
GC
GT
GT
225
chr9
: 172
1048
6-17
2109
4477
9S
BI-
02SB
I-02
Xis
ep09
48B
E35
8472
TA
(5)
AG
GC
CG
AA
TC
AC
AA
TA
AT
GG
AG
TG
CA
TG
AA
CA
GG
GC
AT
C20
5ch
r9: 2
0568
536-
2056
8726
297
SB
I-04
SBI-
04
Xis
ep09
49A
W56
4537
GC
A(5
)C
AG
TG
CC
AA
TA
AG
CT
CG
TC
TC
CA
TC
GA
TC
TC
TG
CT
TC
TG
CT
T10
0ch
r9: 1
9365
772-
1936
5933
271
SB
I-01
SBI-
01
Xis
ep10
08A
W28
5562
CA
G(7
)G
AT
GC
GC
AA
GC
AG
AA
CA
AG
CA
GC
AA
TG
GA
AA
TA
GC
TC
AG
G34
0ch
r10:
249
1921
-130
6650
463
2SB
I-09
SBI-
01
Xis
ep10
13B
E36
0610
CG
G(7
)C
GG
TT
AC
GG
CG
GA
TT
AT
TA
CA
TG
GT
GG
CG
AT
GC
AG
AC
TA
220
chr1
0: 4
4143
94-1
6362
660
402
SB
I-02
SBI-
02
Xis
ep10
14A
W28
3055
GT
(5)
AC
CG
CC
GA
CG
TC
AT
AG
TA
AG
GG
CA
GT
AA
CA
TA
GC
AT
CC
AT
CA
240
chr1
0: 1
3864
191-
1386
4421
391
SB
I-09
SBI-
09
Xis
ep10
25A
W67
2031
GC
G(5
)A
CC
TT
CT
CG
TC
CT
CG
TC
CT
CA
GA
AC
AT
GA
CC
GG
AT
CG
AA
G49
0ch
r10:
852
6382
-218
1396
593
1SB
I-02
SBI-
01
Xis
ep10
28A
W74
7772
GC
A(4
)C
AG
CG
AC
CA
TG
AG
GA
TG
AC
TG
GC
AT
GC
AT
CA
AA
CA
AG
AT
200
chr1
0: 1
1501
109-
2094
1969
638
SB
I-01
SBI-
01
Xis
ep10
31B
E35
5884
CG
G(6
)T
GC
TC
CT
GC
CT
CG
TT
CT
CT
AG
TC
CT
CG
GT
CG
AC
TC
CA
T69
0ch
r10:
555
4237
-217
6595
432
6S
BI-
03SB
I-03
Xis
ep10
32B
E35
6267
TT
CA
G(3
)G
CA
AG
CT
CT
AC
GG
GA
TC
TT
CG
CA
GC
TG
GA
AA
AT
AA
TC
GA
AA
200
chr1
0: 1
4058
773-
2160
9683
1532
SB
I-01
SBI-
01
Xis
ep10
39A
W28
7556
CC
TG
(5)
GT
GG
AT
TC
AA
AT
CC
GC
TG
AC
GG
CA
AT
TT
GG
CA
AG
CA
AT
200
chr1
0: 1
3165
407-
1773
0031
492
SB
I-01
SBI-
01
Xis
ep10
47A
W28
5966
TG
CG
T(4
)T
CT
TT
GC
CC
TC
CC
GC
TA
TT
CC
AT
GA
AA
TG
AG
CA
AA
CG
A16
0ch
r10:
189
0192
3-18
9021
7423
5S
BI-
03SB
I-03
Xis
ep11
07B
E12
5211
GC
A(6
)G
GA
TA
AT
CT
GC
AG
GC
GA
CT
TC
CA
TC
TG
CT
GC
TC
TG
AC
TT
G21
0ch
r11:
534
1585
-536
2168
830
SB
I-05
SBI-
05
Xis
ep11
11A
W28
6876
CG
AG
(3)
CC
TC
CT
CT
CC
TC
AT
CC
CT
CT
AT
GG
GT
AG
CG
GG
TT
TC
TT
G22
0ch
r11:
139
2730
-139
3672
711
SB
I-05
SBI-
05
Xis
ep11
28A
W56
5976
AT
(6)
GG
CG
GG
AA
AA
AG
TT
CC
TT
TA
CG
CA
CA
CC
CA
TT
TC
AA
TT
C22
0ch
r11:
142
4987
4-23
8498
8179
3SB
I-09
SBI-
05
Xis
ep11
33A
W56
4774
CC
A(5
)C
GA
TG
CA
GC
TC
CA
AC
TC
AT
AG
TG
TA
TG
TC
GC
CG
AA
GT
GG
220
chr1
1: 2
9439
34-2
1608
323
350
SB
I-05
SBI-
05
Xis
ep12
13B
E35
8492
GA
A(5
)A
GG
TC
AG
CG
TC
TT
GC
AA
TC
TA
CA
AA
TT
GA
AA
GG
GC
GA
GA
G20
2ch
r12:
165
8936
-210
4613
931
5S
BI-
01SB
I-01
Xis
ep12
41B
E36
0849
AG
CT
G(5
)G
AG
GG
CG
AG
AC
AG
AG
GA
GA
TC
TA
CC
TT
TG
AG
CC
CA
CC
GT
A19
0ch
r12:
248
1225
2-24
8125
2328
8S
BI-
09SB
I-09
123
Theor Appl Genet (2009) 119:1193–1204 1199
newly mapped loci spanned 2,838 cM (Fig. 1). Markerssuch as Xisep0841, Xisep0733, and Xisep0938 on SBI-02,and Xisep0138, Xisep0824, and Xisep0843 on SBI-03,mapped to the vicinity of previously reported stay-greenQTLs (Haussmann et al. 2002b) whereas Xisep0747,Xisep0701, and Xisep1013 on SBI-02 mapped in the vicin-ity of previously reported Striga resistance QTLs (Hauss-mann et al. 2004).
In silico mapping of SSR containing ESTs
All genetically mapped SSR-containing ESTs were thenmapped physically by BLAST search against the alignedsorghum genome sequence. These markers were thenaligned on to the sorghum physical map (Fig. 1). Physicalmap positions were essentially as expected from the genetic
linkage analysis of these markers, except in case ofXisep0110, Xisep0314, Xisep0522, Xisep0608, Xisep1008,Xisep1025, and Xisep1128. Physical and linkage map posi-tions for all 55 mapped markers are listed in Table 1.
Discussion
The nature and frequency of SSRs in sorghum EST collec-tion has been comprehensively discussed in Jayashree et al.(2006). Generally, EST-derived SSR markers are found tobe less polymorphic than genomic SSRs. In this study, only28% of the EST-SSR markers developed were polymorphicamong the four sorghum genotypes initially screened. Asimilar percentage of polymorphism (25%) was reportedfor EST-SSRs in durum wheat (Eujayl et al. 2002), whereas
Fig. 1 Distribution of EST-SSR markers across sorghum linkage groups. Linkage group nomenclature follows Kim et al. (2005b). Newly addedmarkers are highlighted in bold font. Striga resistance QTL and stay-green QTL
Xisep1039Xisep1008
73.8 Mb
SBI-01
Xisep0327
Xisep0839Xisep0949
Xisep1028
Xisep1032
Xisep1213
10
20
30
40
50
60
70
Linkage map Physical map
Xisep1025
Xisep0314
Xisep08390.0Xisep094919.0Xtxp208_A40.8Xisep032750.2Xumc107_HindIII_A64.9E33_M50_F-561-P280.9E13_M61_F-188-P2109.6E11_M48_F-177-P2121.4E14_M60_F-151-P2122.9E14_M50_F-218-P2135.6Xisep1032140.8Xisep1213143.1Xisep1039149.0E12_M47_F-238-P1154.8E12_M47_F-274-P2159.3E11_M49_F-326_P1162.6E11_M60_F-132-P2164.6E11_M60_F-89-P2169.1E11_M48_F-156-P1177.6Xtxp43_A181.6Xtxp88_A183.0Xisep1028205.7Xtxp37_A235.1Xisp324_A245.9Xisp203_A274.7Xbnl05.0_HindIII_A287.8Xtxp61_A298.1Xtxp340_A319.2Xtxp248_A330.1
Xtxp96_B0.0Xtxp197_B16.2Xisep074722.2XSbAGH0429.5E14_M60_F-141-P136.8Xisep070147.0Xtxp50_B54.0Xisep1013102.0Xtxp201_B133.1E14_M61_F-385-P1142.7E33_M50-F-155-P1145.1Xisp366153.6XSbAGB03_B175.0Xumc136_HindIII_B192.7Xumc098_HindIII_B195.1E14_M61-F-115-P2205.2Xisp336212.4Xisep0938224.3Xtxp100_kaf_B239.8Xisep0841248.3Xisep0733251.5E14_M48-F-462-P1253.3Xtxp296_B258.6E11_M49-F-485-P1263.1Xisep1025268.7E14_M48-F-181-P2274.2Xtxp8_B279.4E14_M50-F-192-P2290.8Xisep0310299.6
77.9 Mb
SBI-02Xisep0747
Xisep0701
Xisep1013
Xisep0938
Xisep0733
Xisep0841Xisep0310
Xisep0522
Linkage map Physical map
74.4 Mb
SBI-03Xisep0110Xisep0107Xisep0101
Xisep1047Xisep1031
Xisep0102
Xisep0138Xisep0843
Xisep0824
Linkage map Physical map
Xisep01010.0
Xisp33152.6Xisep010780.1Xisp282_C105.8Xtxp228_C137.3E14-M48-F-209-P2162.8Xisep1047169.7E14_M48-F-173-P2177.3Xisep1031190.5E14_m48-F-88-P1193.1E14_M50-F-512-P1214.3Xtxp33_C236.9E11_M60-F-172-P1246.8Xisep0102252.7E14_M50-F-72-P1257.3Xumc063_EcoRI_C269.7Xisp307_C285.2Xtxp114_C311.4
E11-M60-F-459-P2362.2Xtxp38_I_C384.0Xisp361403.6Xbnl05.37_HindIII_C421.7Xisep0843438.3Xisep0824445.3E12_M47-F-174-P1454.9Xisp323_C466.7
Xisep0138499.0
Xisep09480.0Xisep02249.2Xisep020236.4E14_M61-F-49-P143.9E14_M60-F-438-P244.1E12_M47-F-199-P155.8Xisep022888.5E12_M47-F-226-P1106.2Xisep0522113.0Xisep0608119.7E14_M48-F-130-P2119.8Xtxp343_D123.3Xgap10_D136.6Xbnl05.71_EcoRV_D141.8E14_M61-F-365-P1144.4E14_M50-F-345-P1160.1Xtxp41_D175.9Xtxp327_D180.5Xisp229_D206.7Xtxp27_D239.2
SBI-04Xisep0224
Xisep0948Xisep0202Xisep0228
68 Mb
Linkage map Physical map
Xisp215_J0.0Xisep111130.6Xisp258_J39.2Xumc133_EcoRl_J52.4E13_M61-F-158-P254.0E14_M48-F-186-P276.6E11_M60-F-341-P283.2Xtxp303_J99.8E11_M49-F-67-P2130.1Xisep1107132.6E11_M49-F-270-P2137.4Xisep1133150.2E14_M50-F-382-P2155.7E11_M49-F-584-P2160.5E14_M61-F-142-P1163.8E14_M50-F-157-P1174.4E13_M61-F-71-P1190.4E14_M50-F-137-P1205.7Xtxp123_Kaf2_J217.1
62.3 Mb
SBI-05
Xisep1111
Xisep1107
Xisep1133
Xisep1128
Linkage map Physical map
123
1200 Theor Appl Genet (2009) 119:1193–1204
Thiel et al. (2003) reported 8–54% polymorphism on threediVerent mapping population parental line pairs in barley.Di-nucleotide repeats were more polymorphic (listed aselectronic supplementary information S1) than other repeatclasses, as reported by Thiel et al. (2003) in barley. In ourstudy, a total of 169 EST-SSR markers (28%) detectedpolymorphism between parental lines of two mapping pop-ulations. Among these, 104 EST-SSR markers were poly-morphic in both populations whereas 36 and 29 detectedpolymorphism speciWc to the shoot Xy and the Striga resis-tance mapping populations, respectively.
Sequence-based alignment studies accelerate the Wllingof gaps on linkage maps of related species and can be eVec-tively used for comparative genome mapping across spe-cies (Klein et al. 2003). When searching the homology of1,486 non-redundant sorghum SSR-containing ESTsequences against the rice genome, the highest alignmentscores were obtained for those aligning to the long arms ofrice linkage groups (listed as electronic supplementaryinformation S1). Rice chromosome 3 had the highest num-ber of hits followed by chromosomes 1 and 11. In the
sequence similarity search, 150 of these sorghum ESTsequences did not have any hit on the rice genome. Kleinet al. (2003) also found that 10% of the sorghum ESTsstudied have no homologs in the rice genome. Interestingly,this agrees well with the observation that 7% of the pre-dicted genes from the aligned 8£ shotgun sequence of sor-ghum inbred BTx623 have no apparent homologs inArabidposis, rice or poplar (Paterson et al. 2009).
After incorporating the new markers, the total map dis-tance for the 94-entry (N13 £ E 36-1)-based RIL popula-tion was 2,838 cM, which is similar to that reported by Taoet al. (2000) using 152 RILs and 306 markers. However,the present map is longer than sorghum linkage maps previ-ously reported by several authors (Haussmann et al. 2002a;Pereira et al. 1994; Chittenden et al. 1994). The variation inmap length of diVerent mapping populations is generallyattributed to diVerences in population size, the type of pop-ulation, and the genetic distance between the parents, whichstrongly aVect observed recombination rates, and thus,genetic distances (Menz et al. 2002). A comparison of thepresent map with that of Haussmann et al. (2002a), which
Fig. 1 continued
Xtxp6_I0.0E33_M50-F-354-P25.5E11_M48-F-212-P215.9E11_M48-F-381-P219.2E12_M47-F-101-P239.1E33_M50-F-279-P178.1E14_M60-F-149-P279.2E13_M61-F-257-P182.4E13_M61-F-185-P293.0Xumc044_EcoRl_I108.3Xtxp176_I118.3Xtxp57_I125.5Xisep0422133.2E13_M61-F-367-P1138.1Xisep0449142.1Xisp347_I149.8Xisep0443163.4Xisp225_I180.9
62.2 Mb
SBI-06
Xisep0443
Xisep0422Xisep0449
Linkage map Physical map
Xtxp40_E0.0
Xisp362_E36.7Xumc085_Hindlll_E62.8E11_M60-F-202-P174.1Xtxp312_E88.4Xisep0328122.0E13_M61-F-86-P2153.3E12_M47-F-186-P1162.9E14_M60-F-234-P2163.7E14_M61-F-120-P2172.6
XSbAGF06_E224.6
Xisep0829263.8Xisp344_E278.8Xisep0439289.3Xisep0844296.8Xisu074_Hindlll_E311.5Xisep0831326.3Xisep0704345.6
64.3 Mb
SBI-07
Xisep0328
Xisep0829Xisep0831Xisep0844Xisep0439Xisep0704
Linkage map Physical map
Xisep06320.0Xtxp273_H20.3Xtxp47_H41.5Xcsu030_Hindlll_H79.7E11_M60-F-134-P199.7E11_M60-F-139-P2113.4E14_M60-F-162-P2114.6E11_M60-F-198-P2116.5E14_M48-F-400-P1116.8E11_M49-F-212-P2121.6Xisp198138.3Xisp279163.9E14_M50-F-244-P2178.6E11_M48-F-301-P2194.1Xtxp18_H196.2Xtxp105_H214.4E14_M60-F-250-P1233.9Xisep0809241.0
55.5 Mb
Xisep0632
Xisep0809
SBI-08
Linkage map Physical map
59.6 Mb
Xisep1014Xisep0506
Xisep0513Xisep0550Xisep1214
Xisep0523
Linkage map Physical map
Xisep01100.0E14_M16-F-219-P217.9Xtxp289_F27.6E14_M61-F-182-P239.5E14_M48-F-59-P146.5Xisep101455.6Xisep055073.7Xisep050689.0Xisep051396.3E14_M48-F-110-P1102.8E14_M50-F-213-P2110.8E14_M47-F-257-P1114.7Xisep1008116.3Xisep1241125.3E11_M60-F-189-P2137.6Xisep0523146.2E12_M47-F-157-P1151.6Xbnl05.47_EcoRI_F169.5E14_M48-F-143-P1174.0E14_M48-F-123-P2181.3Xgap32_F215.4E13_M61-F-583-P1273.3Xisep1128290.8
SBI-09
Xisep06070.0E14_M61-F-89-P110.5Xisu136_EcoRV_G23.6Xumc113_EcoRl_G29.7E14_M60-F-116-P245.5Xisep031458.3Xisp359_G78.3Xtxp217_G97.7Xisp263_G116.6E14_M61-F-322-P2145.5E14_M61-F-320-P1149.1Xisep0639158.4Xtxp141_G185.9E14_M60-F-509-P1199.3
60.9 Mb
Xisep0639
Xisep0607
Xisep0608
SBI-10
Linkage map Physical map
123
Theor Appl Genet (2009) 119:1193–1204 1201
was based on a larger sample of progenies from the samemapping population, revealed that 94 out of 113 (83%)common markers had the same linear order in both maps.Some possible rearrangements were detected, which mostlyinvolved alternative orders for closely linked loci. Suchrearrangements are likely due to the use of a sub-sample of94 lines from this mapping population in the current study.The only major change observed in the order of markerswas in the upper part of linkage group SBI-04, inverting theorder of two markers separated by 9 cM. These EST-SSRmarkers, however, Wlled gaps or marker-rare regions in theexisting linkage map of sorghum targeted based on rice–sorghum sequence similarity.
The newly developed EST-SSR markers have shownpractical signiWcance by virtue of their positions. For exam-ple, Xisep0138, Xisep0843, and Xisep0824, which weremapped to SBI-03, are located in the vicinity of a stay-green QTL reported by Haussmann et al. (2002b) (Fig. 1).Three of the markers mapped to SBI-05 (Xisep1111,Xisep1107, and Xisep1133) are located in close proximityto Striga resistance QTLs (Haussmann et al. 2004). Thesemarkers are currently being used by ICRISAT and ournational program partners in the introgression of stay-greenand Striga resistance QTLs into a wide range of farmer-pre-ferred sorghum genotypes through marker-assisted back-crossing. Two markers [Xisep0107 (SBI-03) and Xisep0310(SBI-02)] were selected based on their linkage map posi-tions and used by the Generation Challenge Programme(GCP) in large-scale SSR-based diversity analysis of over3,000 sorghum accessions in a global composite germplasmcollection. Across this very broad range of wild and culti-vated sorghums, a total of nine alleles were noted forXisep0310 and six alleles for Xisep0107 (data not shown).Such small allele numbers with EST-SSRs in such a largeand diverse set of germplasm, as compared to genomicSSRs agrees with expectations that EST-SSRs are lesspolymorphic than genomic SSRs, as the former are derivedfrom conserved and expressed regions of the genome.Although this makes EST-SSRs less useful than genomicSSRs for Wngerprinting purposes, this lower level of vari-ability is helpful in diversity analysis, in which relation-ships between accessions are much more diYcult to assesswhen there are large numbers of rare alleles. Hence, theseEST-SSRs have potential for use in assessing functionaldiversity among diVerent genotypes, as well as use as Xank-ing markers for foreground selection in marker-assistedbreeding programs.
In silico mapping of the ESTs (from which these newSSRs were developed) on the aligned sorghum genomesequence (Paterson et al. 2009) gave very similar positionsas the conventional linkage analysis, both in terms of chro-mosome arm location and order. The order of these EST-SSRs from the in silico mapping agrees with the linkage
map for all ten sorghum linkage groups provided that thelatter are oriented with the short chromosome arm at thetop, as per the suggestion of Kim et al. (2005a). Only seven(12.7%) out of 55 mapped EST-SSR markers added to theN13 £ E 36-1-based skeleton map were mapped in silico tosorghum chromosomes other than those expected. Some ofthese diVerences are likely because the ESTs have beendrawn of multi-gene families with members distributed onmore than one chromosome as a result of ancestral genomeduplication events or transposition. For example,Xisep1025 mapped in silico to SBI-01 where as it ismapped to SBI-02 based on linkage analysis. However, thesorghum EST sequence (which had a best hit on rice chro-mosome 1) from which the primer pair for Xisep1025 wasderived also has a low e-value hit on SBI-02. This may bedue to presence of duplicate loci on SBI-01 and SBI-02.Recently, 5,012 genomic SSRs were mapped in silico on tothe aligned sorghum genome sequence assembly (Yone-maru et al. 2009).
The sorghum genome sequencing project has revealedthat predicted gene density in sorghum is much higher atthe ends of each chromosome and that heterochromaticregions near the centromere are essentially devoid of pre-dicted genes (Paterson et al. 2009). In silico positions forall mapped EST-SSRs are located at the ends of sorghumchromosome arms, away from the centromeric regions, inagreement with the predicted genomic distribution of sor-ghum genes. The in silico-predicted physical map positionsof candidate markers (including EST-SSRs that have notyet been mapped) can help to choose markers to Wll gapsand better saturate linkage maps. Thus the availability ofgenome sequences and other marker information can helpin selecting or developing markers for targeted mapping notonly in a given crop but also in related crops for whichsuYcient genomic tools are not yet available in the publicdomain.
On-going and future sequencing projects will contributemany more genomic and genic sequences to publicly avail-able databases, facilitating development of diVerent typesof markers at lower cost. As economically importantgrasses have more conserved regions across taxa thanfound in other crop lineages, EST-SSRs should become anextremely powerful tool for better understanding of rela-tionships between the grass species and for genetic map-ping. Our initial attempt to develop EST-SSRs based onsorghum–rice synteny was successful in Wlling importantgaps in the existing sorghum linkage map. We propose toinvestigate further the large number of SSR-containing sor-ghum EST sequences to develop a dense linkage map basedon these functional markers. The newly developed markersin hand, which are tightly linked to genomic regions con-trolling Striga resistance and the stay-green componentof terminal drought tolerance, can be used in functional
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1202 Theor Appl Genet (2009) 119:1193–1204
analysis of these traits. These markers are being used byICRISAT, along with the newly reported CISP markers(Feltus et al. 2006b), for mapping of sorghum resistance toshoot Xy, stem borers, and grain mold. Through this study,we have demonstrated the value of a comparative sequencesimilarity approach for targeted development of PCR-com-patible molecular markers for practical applications in cropgenetics and breeding. It has previously been reported thatmore than half (57%) of EST-SSR markers developed fromsorghum ESTs show cross-species transferability (Wanget al. 2005), hence these markers can also be successfullyused in other related grass species for which insuYcientnumbers of PCR-compatible markers are available. Primerpairs for non-redundant sorghum EST-SSRs are availablefrom our database (http://intranet.icrisat.org/gt1/ssr/ssrdat-abase.html).
Acknowledgments The research fellowship provided to PR by theCouncil of ScientiWc and Industrial Research (CSIR), New Delhi, Indiais greatly acknowledged. KB acknowledges the Wnancial support pro-vided by the Ethiopian Government and ICRISAT. Work reported herewas partially funded by the CGIAR Generation Challenge Program(GCP).
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