Diversity arrays technology (DArT) markers in applefor genetic linkage maps

Henk J. Schouten • W. Eric van de Weg • Jason Carling • Sabaz Ali Khan •

Steven J. McKay • Martijn P. W. van Kaauwen • Alexander H. J. Wittenberg •

Herma J. J. Koehorst-van Putten • Yolanda Noordijk • Zhongshan Gao •

D. Jasper G. Rees • Maria M. Van Dyk • Damian Jaccoud • Michael J. Considine •

Andrzej Kilian

Received: 6 September 2010 / Accepted: 9 April 2011 / Published online: 15 May 2011

� The Author(s) 2011. This article is published with open access at Springerlink.com

Abstract Diversity Arrays Technology (DArT)

provides a high-throughput whole-genome genotyp-

ing platform for the detection and scoring of hundreds

of polymorphic loci without any need for prior

sequence information. The work presented here

details the development and performance of a DArT

genotyping array for apple. This is the first paper on

DArT in horticultural trees. Genetic mapping of

DArT markers in two mapping populations and their

integration with other marker types showed that

DArT is a powerful high-throughput method for

obtaining accurate and reproducible marker data,

despite the low cost per data point. This method

appears to be suitable for aligning the genetic maps of

different segregating populations. The standard

Henk J. Schouten, W. Eric van de Weg these authors

contributed equally to this work.

Electronic supplementary material The online version ofthis article (doi:10.1007/s11032-011-9579-5) contains supple-mentary material, which is available to authorized users.

H. J. Schouten (&) � W. E. van de Weg �S. A. Khan � M. P. W. van Kaauwen �H. J. J. Koehorst-van Putten � Y. Noordijk

Wageningen University and Research Centre, P.O. Box

16, 6700 AA Wageningen, The Netherlands

e-mail: henk.schouten@wur.nl

J. Carling � D. Jaccoud � A. Kilian

Diversity Arrays Technology, PO Box 7141, Yarralumla,

ACT 2600, Australia

S. J. McKay

Department of Horticultural Science, University of

Minnesota, Alderman Hall, 1970 Folwell Ave, St. Paul,

MN 55108, USA

Z. Gao

Department of Horticulture, Zhejiang University,

Hangzhou 310029, China

M. J. Considine

School of Plant Biology, and the Institute of Agriculture,

University of Western Australia, M084, Crawley, WA

6009, Australia

M. J. Considine

Department of Agriculture and Food Western Australia,

South Perth, WA 6151, Australia

A. H. J. Wittenberg

KeyGene bv, P.O. Box 216, 6700 AE Wageningen, The

Netherlands

D. J. G. Rees

ARC: Biotechnology Platform, Agricultural Research

Council, Private Bag X5, Onderstepoort, Pretoria 0110,

South Africa

e-mail: reesj@arc.agric.za

M. M. Van Dyk

Department of Genetics, Forestry and Agricultural

Biotechnology Institute (FABI), University of Pretoria,

Private Bag X20, Hatfield, Pretoria 0028, South Africa

e-mail: daleen.vandyk@up.ac.za

123

Mol Breeding (2012) 29:645–660

DOI 10.1007/s11032-011-9579-5

complexity reduction method, based on the methyla-

tion-sensitive PstI restriction enzyme, resulted in a

high frequency of markers, although there was 52–54%

redundancy due to the repeated sampling of highly

similar sequences. Sequencing of the marker clones

showed that they are significantly enriched for low-

copy, genic regions. The genome coverage using the

standard method was 55–76%. For improved genome

coverage, an alternative complexity reduction method

was examined, which resulted in less redundancy and

additional segregating markers. The DArT markers

proved to be of high quality and were very suitable for

genetic mapping at low cost for the apple, providing

moderate genome coverage.

Keywords Apple � DArT � Genetic mapping �Molecular markers � Diversity

Introduction

The genus Malus has been a focus of molecular

studies since the mid-1980s, when Weeden and Lamb

(1985) used isozymes as a means of discriminating

between different apple cultivars. As new marker

types have been developed, scientists have readily

adopted them into their studies of apple genetics,

progressing from rapid amplification of polymorphic

DNA (RAPD) (Koller et al. 1993), through restriction

fragment length polymorphism (RFLP) and isozymes

(Maliepaard et al. 1998), to amplified fragment length

polymorphism (AFLP) and simple sequence repeat

(SSR) (Guilford et al. 1997, Hokanson et al. 1998)

and on to targeted markers (e.g., Broothaerts 2003;

Calenge et al. 2005; Chagne et al. 2007) and single

nucleotide polymorphism (SNP) arrays (Micheletti

et al. 2011). The progress in the molecular charac-

terisation of the Malus genome has recently gained

further momentum with whole-genome sequencing

(Velasco et al. 2010).

Molecular markers have been applied widely to

evolutionary and pedigree studies in apple, including

both wild Malus species (Richards et al. 2009) and

domestic cultivars (e.g., Cabe et al. 2005; Evans et al.

2010). Additionally, markers developed for the apple

have been applied fairly widely to other pome

species, and vice versa, notably pear (Pyrus spp.,

Yamamoto et al. 2001; Hemmat et al. 2003; Dondini

et al. 2004), quince (Cydonia oblonga; Yamamoto

et al. 2004) and loquat (Eriobotrya japonica; Gisbert

et al. 2009; He et al. 2010). Simultaneously, linkage

maps have been constructed for a number of domestic

cultivars, and several map alignments have been

reported (Maliepaard et al. 1998; N’Diaye et al. 2008;

Patocchi et al. 2009; Van Dyk et al. 2010). The

construction of linkage maps has facilitated the

identification of molecular markers associated with

numerous phenotypic traits. Among the traits exam-

ined to date are resistance to apple scab caused by the

fungus Venturia inaequalis (Koller et al. 1994;

Calenge et al. 2004; Bus et al. 2005a, b; Soriano

et al. 2009), fire blight caused by the bacterium

Erwinia amylovora (Peil et al. 2007), columnar

growth habit (Moriya et al. 2009), several fruit

quality traits (e.g., King et al. 2001; Liebhard et al.

2003a; Costa et al. 2005, 2008, 2010; Kenis et al.

2008) and chilling requirement (Van Dyk et al. 2010).

The identification of such molecular markers is

essential for marker-assisted selection in apple

breeding programs (Gianfranceschi et al. 1996;

Liebhard et al. 2003b; Gardiner et al. 2007; Zhu

and Barrett 2008). In recent years, genomic methods

have been embraced by apple researchers. The

enhanced ability to study gene expression has

resulted in new understandings of developmental

processes (Ban et al. 2007; Espley et al. 2009).

Transcription analyses of apple fruit development

using cDNA microarrays (Soglio et al. 2009) and

plant physiological responses to pathogens (Norelli

et al. 2009) has facilitated the development of new

molecular markers (e.g., Chagne et al. 2008; Igarashi

et al. 2008). The further development of high-

throughput genetic technologies will continue to

expand the ability of scientists to investigate the

details of the genetics of apple and its relatives

(Shulaev et al. 2008).

Since the proof-of-concept paper (Jaccoud et al.

2001), Diversity Arrays Technology (DarT) has been

developed as an inexpensive whole-genome profiling

technique for many organisms, especially plants. The

website www.diversityarrays.com has a current list of

organisms for which arrays are available ([50).

DArT, in its current implementation, is a hybridisa-

tion-based genome profiling technology that does not

require sequence information and uses microarrays to

identify and type DNA polymorphisms. As the DArT

markers are typed in parallel, it is possible to identify

hundreds or even thousands of polymorphic markers

646 Mol Breeding (2012) 29:645–660

123

in a single experiment (Wittenberg et al. 2009). This

highly parallel assay results in a reduction of the price

per data point to around US $0.01 in organisms with

well-developed arrays. The DArT assay primarily

detects dominant markers, mostly resulting from

single nucleotide polymorphisms and indels in

restriction sites and differences in methylation of

restriction sites. When methylation-sensitive restric-

tion enzymes (like PstI; see Gruenbaum et al. 1981)

were used in the large genomes of cereals (Wenzl

et al. 2004, 2006; Akbari et al. 2006), DArT markers

were located preferentially at the gene-rich, subtelo-

meric regions of the chromosomes. The use of

methylation-sensitive enzymes may provide also an

insight into epigenetic variation (Wenzl et al. 2004).

Interestingly, while DArT has performed well in

over 50 crops, there are no reported applications of

DArT in horticultural trees. As DArT has been applied

successfully to complex amphidiploid genomes like

wheat (Akbari et al. 2006), oat (Tinker et al. 2009) and

sugarcane (Heller-Uszynska et al. 2010), application to

the duplicated genomes of the pome fruits such as apple

(Velasco et al. 2010), pear and loquat should be

promising too. Here, we present the development and

validation of DArT for apple using a complexity

reduction method similar to the one used for the cereal

genomes. We compare this with a second complexity

reduction method that is similar to the method used for

the fungus Mycosphaerella graminicola (Wittenberg

et al. 2009), and we discuss the characteristics of the

detected markers. We combined DArT markers with

other marker types in genetic linkage maps, providing

insight into the coverage of the DArT markers in the

apple genome. We used as a starting point the progeny

and genetic linkage map of Prima 9 Fiesta, which was

the first genetic linkage map for apple covering all 17

chromosomes (Maliepaard et al. 1998). In addition, we

used a more recent progeny of other parents for genetic

mapping. Furthermore, we evaluated the performance

of DArT in a genetic diversity analysis of 44 diverse

apple accessions and a set of Australian breeding lines.

Materials and methods

Plant material

For the building of the DArT libraries, care was taken

to represent a wide genetic diversity, including

several major founders in apple breeding worldwide,

founders of more local breeding programs, modern

cultivars and some very recent selections from

ongoing breeding programs. Forty-four accessions

of Malus were used for the library development

(Online Resource 1a).

For mapping, two populations were used. The first,

Prima 9 Fiesta, was used to examine the reliability

of the DArT data by evaluating the ease by which the

DArT markers were integrated in an existing, well-

established linkage map. This population consists of

156 individuals (Maliepaard et al. 1998), of which a

subset of 121 individuals were DArT genotyped. The

second population, 2000–2012 (Soriano et al. 2009),

was used to demonstrate the ease by which DArT

markers allow for the alignment between mapping

populations. In addition, this population was used to

compare two DArT complexity reduction methods

with respect to the number of markers and genome

coverage. It comprises 894 individuals, 399 of which

were used in the current study. The parentages of

both populations are presented in Fig. 1.

DNA extraction

For the development of the DArT libraries and genetic

diversity studies, leaves were collected from grafted

trees with a preference for younger, actively expanding

leaf material. Genomic DNA was extracted using a

modified cetyltrimethylammonium bromide (CTAB)/

chloroform/isoamylalcohol protocol based on the

method of Doyle and Doyle (1987). The addition of

2% w/v polyvinylpyrrolidone (PVP-40, Sigma,

K value: 29–32) (Aljanabi et al. 1999; Kim et al.

1997) appeared to be essential for preventing the

inhibition of restriction endonuclease digestion in

many of the apple leaf samples tested. For the mapping

populations, DNA was extracted according to Maliep-

aard et al. (1998) and Soriano et al. (2009).

Construction of DArT arrays

A crucial step in the Diversity Arrays Technology is

the complexity reduction of genomic representations.

In this manuscript, complexity reduction refers to the

reproducible selection of a subset of DNA fragments

from a whole genome. These fragments, after being

cloned into E. coli vectors (TOPO) and amplified

with M13 primers, were printed onto slides as probes

Mol Breeding (2012) 29:645–660 647

123

for microarray hybridisations. The complexity reduc-

tion method used most often in DArT involves

digestion with the methylation-sensitive restriction

enzyme, PstI. In conjunction with digestion using this

relatively rarely-cutting restriction enzyme (six bp

recognition site plus methylation sensitivity; Gruen-

baum et al. 1981), an enzyme with frequent cutting

capabilities is used (Wenzl et al. 2004). In this study,

the frequently-cutting enzymes AluI, BstNI, TaqI or

MseI were used. PCR adapters were ligated to the

PstI fragment ends, and the PCR-amplification was

performed using primers complementary to the PstI

adapters, according to Wenzl et al. (2004). Only those

fragments with PstI adapters at both ends were

amplified.

Initial assessment of the enzyme combinations was

performed by agarose gel electrophoresis, as

described by Jaccoud et al. (2001). On this basis,

the genomic representations produced by the diges-

tion with PstI, in combination with either AluI or

BstNI (PstI/AluI and PstI/BstNI), were considered to

be the most suitable due to the absence of visible

bands in the gel smear (Kilian et al. 2005). An initial

library of 768 clones was prepared for PstI/AluI and a

second initial library of the same size for PstI/BstNI,

using DNA from 15 diverse heritage apple varieties

(Online Resource 1a). The inserts of the 2 9 768

clones were amplified and printed on glass slides to

provide small arrays for testing. The 15 cultivars

listed in Table 1 were hybridised in duplicate to the

arrays, according to Wenzl et al. (2004). The PstI/

AluI complexity reduction method was found to give

a higher number of candidate polymorphic markers

(16% of clones) than the PstI/BstNI method (10% of

clones). The PstI/AluI library was therefore expanded

by an additional 3,840 clones derived from the 15

heritage cultivars, and 9,984 clones from modern

apple cultivars and breeding lines (Online Resource

1a). The total size of the expanded library for the

PstI/AluI complexity reduction was 14,592 clones.

Fig. 1 Pedigree of the two

mapping populations

examined. Common parents

are highlighted

648 Mol Breeding (2012) 29:645–660

123

Hybridisation to the expanded array

To gain insight into the applicability of DArT in

mapping, two segregating populations were hybridised

to the expanded array. All genotypes were hybridised

with two to four replicate arrays per genotype, using

both Cy-3 and Cy-5 fluorescent labelling. Hybridisa-

tion, subsequent processing and data analysis were

performed according to Wenzl et al. (2004).

Integration of existing genetic markers

into genetic linkage maps

The genetic linkage map of Prima 9 Fiesta was the

first for apple covering all 17 chromosomes (Maliep-

aard et al. 1998). It consisted of 138 dominant

markers (mainly RAPDs and some AFLPs) and 152

essentially co-dominant markers (mainly RFLP, some

isozymes and SSRs). Since then, 313 new markers

have been added through successive European pro-

jects, of which 180 are dominant (mainly AFLP) and

133 are co-dominant, mainly consisting of SSR

markers from the gDNA-based CH and Hi series

(Liebhard et al. 2003b, Silfverberg-Dilworth et al.

2006) as gathered from expressed sequence tag (EST)

sequences (Soglio et al. 2009). Some of the new

markers were specifically designed for fruit-quality

genes (Costa et al. 2005, 2008, 2010) and allergy

genes (Gao et al. 2005a, b, c). The quality of the map

was thoroughly validated and improved, using Join-

Map� (Van Ooijen and Voorrips 2008). This newly

enriched, evaluated and extended map of Prima 9 -

Fiesta covers approximately 90% of the apple

genome, and was used as a starting point for the

mapping of DArT markers.

An alternative method for complexity reduction

We evaluated an alternative complexity reduction

method that was applied by Wittenberg et al. (2005)

to microbial genomes. This approach involved diges-

tion with two six-base cutters, PstI and EcoRI. A

standard adapter was ligated to the PstI ends of the

restriction fragments and a long, asymmetric adapter

with a 30-amino (NH2) group on the short strand was

ligated to the EcoRI ends. The amino group,

Table 1 Number of DArT markers from the standard complexity reduction method, during successive mapping stages in the

Prima 9 Fiesta population

Mapping stages Prima Fiesta’ Both parents Total

No. of

events

No.

cumulative

No. of

events

No.

cumulative

No. of

events

No. cumu-

lative

No. of

events

%

events

No.

cumulative

Preparation data

Polymorphic 257 234 285 776

Unclear parentage 11 246 14 220 0 285 25 3.2 751

Polymorphic Information

Content \ 0.10

47 199 49 171 3 282 99 12.8 652

Mapping

Redundant, completely

identical

1 198 40 131 73 209 114 14.7 538

Remaining ungrouped 0 198 4 127 0 209 4 0.5 534

Insufficient linkage for phase

determination

1 197 4 123 32 177 37 4.8 497

Irregular segregation pattern 2 196 4 119 1 176 7 0.8 490

Redundant, differences only

for missing values

112 83 42 77 96 80 250 32.2 240

Double recombinant 0 83 1 76 0 80 1 0.1 239

Unique mapped 83 76 80 239

Markers with solved

parentages

3 86 3 79 2 82 8 1.0 247

Total uniquely mapped 86 79 82 247

Mol Breeding (2012) 29:645–660 649

123

combined with PCR suppression (Siebert et al. 1995;

Broude et al. 2000), was used to prevent amplification

of the EcoRI–EcoRI fragments. Only the PstI–PstI

and PstI–EcoRI fragments were amplified. To further

reduce the complexity of the genomic representa-

tions, a third endonuclease, the four-basepair cutter

MboI, was used. No adapters were ligated to the MboI

sites. Consequently, the fragments cut by MboI were

not amplified (Wittenberg et al. 2005).

For this alternative complexity reduction method,

the DNA of the apple selection 1980-015-025, a

parent of population 2000–2012 (Fig. 1), was used to

construct a library of 6,144 fragments, which were

printed onto slides (Wittenberg et al. 2005). Target

DNA from this selection’s progeny, population

2000–2012, was assayed with this array, using the

same alternative complexity reduction method. The

adapters ligated to the target DNA of this progeny

differed from those of the parental fragments printed

on the slides, in order to prevent hybridisation of

adapters to one another (Wittenberg et al. 2005).

The alternative array was used for the genotyping

of 244 progenies of population 2000–2012, all of

which had also been genotyped with the standard

method too. The maternal map of the heterozygous

parent 1980-015-025 was constructed using DArT

markers from both complexity reduction methods. In

addition, several SSR markers were used as refer-

ences on the linkage map; they were generated

according to Patocchi et al. (2009).

Results

Mapping of DArT markers in Prima 9 Fiesta

The Prima 9 Fiesta progeny were hybridised to the

expanded DArT array for the standard complexity

reduction method, which provided 776 polymorphic

markers. The call rate for the parental genotypes was

99.2%. The call rate is the percentage of targets that

could reliably be assigned a score of ‘0’ or ‘1’ for a

given candidate marker. The average call rate for the

entire Prima 9 Fiesta mapping population was 96.7%.

Of the aforementioned 776 Prima 9 Fiesta DArT

markers, 247 (32%) were mapped to a unique

position (Fig. 2). The other 68% were eliminated

during the mapping process for several reasons

(Table 1). Only 4.6% of the markers were discarded

due to possible scoring problems. Of these, 3.5%

were due to incomplete data on the mapping parents,

leaving only 1.1% of the markers being possibly

discarded for inadequate scoring, remaining

ungrouped or showing irregular segregation patterns.

The two latter phenomena could also be due to

reasons other than scoring difficulties, such as a lack

of marker coverage of the genomic regions or the

presence of duplicated loci. Online Resource 1b

documents the fact that adding DArT markers did not

affect the previous high overall map quality, as

measured by the average v2 value.

A considerable number of clones exhibited iden-

tical segregation patterns in Prima 9 Fiesta com-

pared to other clones, and therefore did not provide a

higher genetic resolution in the map. As a result, a

total of 364 (54%) of the 677 clones (=776–99;

Table 1) were classified as redundant.

Genome coverage

The current DArT array provided moderate genome

coverage, as illustrated in Fig. 2. Many markers

clustered, producing several short genomic segments

containing multiple markers, such as a segment of

4 cM at the top of linkage group (LG) 7 that

contained eight unique Prima-specific DArT markers

and one marker for both parental cultivars. However,

several extended regions had no or very few markers,

such as the entire LG1 of Prima, which contained

only one Prima-specific and one common marker.

Genome coverage was estimated using the integrated

map of Fig. 2 as a reference and the following

thresholds: (1) only parent-specific markers were

considered, as markers common to both parents carry

little genetic information, and (2) a single marker

covers 10 cM surrounding its position. In these

calculations, the current DArT array offered suffi-

cient coverage for performing classical quantitative

trait loci (QTL) mapping studies on around 55% of

the Prima and 60% of the Fiesta genome. If a single

marker were to sufficiently cover a larger window of

30 cM, then the genome coverage for Prima and

Fiesta would be 76 and 74%, respectively.

Suitability of DArT markers for map alignment

To examine the power of DArT markers for aligning

maps, the second mapping population, 2000–2012,

650 Mol Breeding (2012) 29:645–660

123

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186532+ 54Mald3.02+ 57462170+ 60

186208+ - 62SOD-3+ 66

MC105a - 68553934+ - 71AT000420+ 77

CH01b12z - 91

PF4

186634 + -0

518939 + -1

182651 -5

3O5 + -22

461699 + -

186787 + -26

1M10 + -27

184740 + -28CH02h11 -30460809 + -

441674 + -

525869 + -

32

461271 + -33

186532 +36

182559 # +38

012-4

pAP4a-X - 0CN493139x+ - 7# 182773+ 10

# 183668+ - 12CO-2_C+ 13

461684+ 24MC028b - 26MC127c+ - 28

525645+CH03a09+ -

E36M51-143+E35M48-112+

32

184650+MC030b+

OPAB-14-0700 -33

461614+ -

# 182654+ -

526705+ -

34

MC123a+ 37MC025+ 39

E33M51-127+ 41AC12+ 43

461169+ 45

461279+ 46

461508+ 47MC097b+MC227b+ 48

443333 -

518988+56

442627+ - 57E32M52-375+ 59

460995+ - 60MC095+ -

526764+ -61

442210+ 62

443367+ 63MC109c -

E34M59-251+ 65

E34M55-85 -OPAD-02-0400 -

GD103 -68

E35M50-206 -MC245+ -MC018+ -

69

OPS-10-1100_B+ 71OPAG-15-1250+ 73

E35M47-111+MC024b+

E33M52-177+E33M51-202+

MC204b+

75

OPAC-03-0510+ 76OPL-01-0900 -E35M47-158 -E36M51-243+

E34M59-97 -

525837 -

77

E36M59-171 -CH02b12y+ -

LY29b -78

MC123b+ -

185871+ -79

CH04e03+ - 80E34M48-154 -

E34M55-59 - 81

MC244a+ - 84MC202+ - 88

PF5

7N16 +6

519616 +7

553843 +

183668 # +8

11G4 +9

182773 # +11

185646 + -

184384 # + -Hi04a08 + -

19

1.00E+17 + -21

10N23 + -23

460976 -28

11A15 + -30

10K2 + -31CH05e06 +/-

5J19 + -33

CH04g09z -35186614 -37

525645 + -38

182520 # -41

9.00E+21 + -47

6B6 + -53

183517 # -55

5M22 +59

442210 -

9I22 +60

GD103 +/-70

7K9 +79

7H3 +

5I22 +80

CH02b12 +82186344 +85

185935 + -

526844 + -

183675 # + -

86

6H16 + -88

8D18_D1 + -89

2N15 +91

012-5

OPE-04-1400 - 0E36M59-315 - 3

185017 - 6OPD-10-2000 -E34M48-205 - 7

MC019a+ 10Mald1.05 - 11MC023a+ - 13MC034b+ - 14

186937+ - 15OPAF-13-1800+ 16

OPC-06-1300_B+MC096b+ - 17

E35M51-158+E35M51-110+ 18

E35M51-252 - 21NZ23g04+ - 25

CH03d12+ - 37MC040b - 39

554574 - 40

461879+ -7B9+

42

442310+ - 44E34M55-84+ 48

OPAB-12-0680 - 49

CH05a05+ -MC204a+ - 63

MC011-+ - 66

PF6

CH03d07? +0

CH03d12 +15

461879 +19

CH02b10? +40

6P2 +43

10H11 +44

3.00E+19 +69

CH05a05 +/-74

012-6

MC056+ - 0MC228b+ 2

2B12a -MC029b -

Sd1 -OPT-14-0800+

3

527002+MC064a+ -

442697+

461103+MC057a+

# 182694+ -

4

526661 -

184957 -5

184765+ 6

186359+

# 183619+7

186460+ 10OPAE-19-1600+ 11

# 182859+ 13MC116a+

E36M51-206+OPAB-13-2600+

15

OPC-08-1700 -E35M47-220 - 16

OPT-09-1200 -

186378+ -18

OPA-09-0700_BD+

# 183153+21

E35M48-131+ 22E34M48-252+

E35M47-275-2+CH04e05z+ -

23

441985+OPAM-19-0800+

443137+ -24

MC014b+ - 25186703+ - 27

182820 - 31OPA-10-1000 - 33

MS06c09+ - 35460767 - 39

553337+ -

461607+ -

185711+ -

41

553964 - 45

525517+ -

186911+ -46

E33M51-64 -E34M59-83 -Conf-8-SSR -

526070+ -

47

PGM-2 - 53

PF7

183165 # +0

11D9 + -3

11B5 + -4

527002 + -

186990 + -6

Hi03a10p +/-22

186378 -30

2D12 +

441985 + -35

183153 # +36

442371 + -

460884 + -37

443137 + -38

186703 + -39

6N4 + -40

184379 # +43

182820 +44

12H8 +

10O2 +CH04e05 +/-

47

184661 +

443057 +54

6I7 + -60

10C5 + -62

184289 # + -

184686 + -

184313 # -

66

185711 -72

518887 +75

553337 +

553964 -76

012-7

518983+ - 0LY21+ - 1

OPAB-14-0600+ 2# 182536 - 3

519609 - 4

443379 - 11

186096 -

461686+

186784+

12

E33M51-68+ 13AAT-2+

OPT-06-0800+ 18

CH01e12+ 21E34M48-323+ 24

MC206+ -Mald4.03 -

LY16 -

185289 -E31M52-230+

26

E31M52-465 - 27MC022+ - 28

OPAF-12-1600+OPD-15-1300+

LAP-2_C+E33M51-280+

CH01f09+ -

29

Mald4.03+

# 182916+ -30

E35M52-124+E34M59-213+ 32

E35M48-326+ 34CH05a02y - 37

MC027+ - 38441714 - 39

OPAF-13-0800 - 43461663+ 44CH01h10+ 45

E35M48-330 - 46E31M52-198 - 48E36M57-142+ 52

186111+OPAC-11-0780+

55

OPT-19-2200 - 58MC104a - 59

E35M50-226 - 60525634 - 68

PF8

182536 # +0

6I3 + -5

461789 +11

186784 +

461737 +15

518577 + -20

CH01c06 +/-349O24 + -

5M2 + -37

5B10 + -39

184826 +

185283 +41

526028 +

442481 +

183036 # +

42

185289 +43CH02g09 +/-459M2 +49

2G7 + -50

441714 + -51

CH01h10 +63

441618 +76

526690 +77

012-8

Fig. 2 Alignment of the 17 linkage groups of the mapping

populations Prima 9 Fiesta (PF) and 2000–2012 (012). DArT

markers are displayed in bold, those segregating in both parents

are in italics and those generated with the alternative complexity

reduction method are underlined. The ? and - symbols next to

a marker name indicate that the DArT marker was polymorphic

in the mother and father, respectively. The # symbols indicate the

DArT markers that have been sequenced

Mol Breeding (2012) 29:645–660 651

123

Conf-12-CAPS - 0E36M51-198 - 5# 184321+ - 6

442368 - 7

# 184050+ - 8

554103+ - 10

441965+ 16OPAC-06-0590 - 21

519109+ -OPAB-14-0800 -

23

460707 - 24OPAB-08-0940+ 26

MC104b+ 29MC007+ 31

CH05c07+ -

186510 -34

184700+ 36

185101 -

# 182598 -38

E34M55-181+ 39# 184328+ 43

CX023634-SSR - 47Conf-9-SSR+ 52

OPAE-01-1190 - 54E34M48-83 - 55

E35M50-284 -E36M51-480 -E36M57-114+

56

Mald4.01 - 57OPAE-01-1210+

Conf-10-STS+Conf-13-SSR -

58

Conf-11-SSR+OPAE-08-1000+ 59

E33M52-96+E32M52-242+

OPD-01-0600+E35M50-281-2+

61

MC224a+CH01h02+ - 64

MC038a+ 65462205+ -

MC117+66

Mald2.01B+ - 68Mald2.01A+ - 70185333+ 71

MC115b+ 76

PF9

442368 +0

184050 # +2

9D20 +6

554103 + -8

526197 +13

519109 +14

CH01f03 +/-19442542 +21

441884 +22

553238 +

460707 -23

184328 # +35

182598 # -38

443058 +42

CH01h02 +/-49

CN444542a +55

185333 +60

012-9

MC244b - 0

pADH32a - 7MC228a - 9

519383+ 17OPAF-07-0890+ 18

186012+ 19OPE-12-1600+ 20

461634 -MC024a -

22

MC049+ -CH02b07+ -

E36M51-195+23

OPAG-04-1000+ 24460957+ 25

OPAD-14-1020 - 26Conf-15 - 27

LY29a+ - 28461747+ - 30

442891+ 31E35M50-239 - 35E34M59-410 -

EST-1 -E34M59-314+

MC109a -

36

E33M51-169 -Hi03e04y -

OPAB-13-2200 -OPAE-19-0250 -

37

518575 - 38

186714 - 39

462175 - 41

# 183247+ -CH02c11+ -

44

MC227a+ - 53CH03d11+ - 57

E35M52-224+MC030a+MC025b+

62

443095+ 64E35M48-159+

OPA-09-0200+ 68

# 183529 - 72MC127d -MC028a+ - 76

OPA-11-1050 -MC060+ -

USASSR11+ -77

CH02b03b+ - 80MS02A01+ - 85

# 183090+OPC-08-0790 -

91

MS06g03+ - 96186434 - 97

pAP4b - 98

PF10

183555 # +0

552809 + -6

184025 # + -7

460957 -9

554953 -11

553408 + -17

1H17 + -21

442891 + -37

186714 + -38

462175 -44

442053 -45

461749 + -46

183714 # + -49CH02c11 +/-51442552 -

183247 # -53

CH03d11 +/-58186426 -59

184838 -60

CH04g09y -71

9M8 + -90

1L20-! + -97

182835 # +

183090 # +103

5H14 +

184374 # -105

6G15 +106

2I8 +107MS06g03 +/-1088C7 +112

12L9 +

8F3 +113

012-10

185131 - -4

184618 - -1Conf-16-SSR+ 0

CH04h02z+ -CH04h02y+ -

Conf-17--SSR -2

E35M53-150+ 5E34M59-139+ 6

OPA-09-0600+MC004 - 12

461385 - 13E35M53-187 - 15E34M55-410+

OPAD-02-0500 -

# 183677+17

MC045+ 18CH02d12+ - 21MC036b - 26

CH04a12+ - 31E35M51-301+ 33

MC051+ 35UBC203-0400+ 39

E33M52-115 -E33M51-133+

460857+41

185136 - 47

525720+ 48

461081 - 49

186843+ 50UBC213-1200 - 51

E34M55-292 -E33M52-322 - 52

E31M52-114 - 54441813 - 55

MH116+ - 57OPAE-19-1800 - 60

E34M55-91+

184555+61

518989+7BC7b -

62

526057 -

525861 -63

526003 - 64

441669 -

525825 -66

OPAC-11-0600 - 67# 183719+ - 71E34M48-190 -

185124 -73

443193 - 75

442863 - 76

PF11

CH04a12 +/-0

CH02d08 +/-14

6P21 +28

518573 + -42

461081 -51

184554 + -53

10D23 +59

CH04g07 +63

CH03d02 +83

186331 + -89

442695 -95

526557 -99

518909 -100

555037 -105

CH04d10 +/-110

185320 + -115CH04h02e +/-116443030 -117

185357 -118

9B21 + -124

012-11

186490+ - 0MC016+ - 1

518917+ - 4MC032b+ -

443179+ -6

MC225+ -

443372+ -7

OPA-06-1200+ 8443303 - 11

MC125a+ - 13E34M55-202 -

CN493139+OPC-08-0700 -

CH04g04+ -

15

443032+E31M52-290 -

16

442826+NZ28F4+ -

17

OPAB-12-2100 - 19MC070+ - 20

E35M48-196+ 22184451+ 23

MC127b+ 30OPA-10-1100_B+ 38

E35M50-113 - 43CH01f02+ - 46

443308+ 49OPAM-19-1020+ 53OPAD-12-0800 - 54

443077+ - 56

185669+ - 62E34M48-175 - 64# 183720+

Hi07f01+ -65

460973+ 66OPA-01-0700+ 67# 183485+ -

MC105b+ -69

461822+ - 70

185621+ - 71

525670+ 75

PF12

186490 -0

CH05d04 +/-5

10M16 + -13

Ch04g04 +/-19

461499 +33

10J9 +

10B21 +34

CH01g12 +/-40

3L18 + -45CH04d02 + -

3N14 +49

9H3 +50

525882 + -

6H17 +51

519342 + -59

183985 # -

183186 # +60

183701 + -61

183986 # +72

183720 # +73Hi07f01 +/-75

184963 + -81

183485 # +82

461822 +

525797 +86

184694 + -

185896 + -87

012-12

# 182625+ 0CH05h05+

E33M51-355+ 2

184627+ 4

553807+ 12E34M48-286+ 14E34M59-255+

LY05-Hi+MC001a+

16

E36M57-117+ 17MC039+ -MC130+ -GD147+ -

21

441485+ - 27

DIA_5+ 34NH009b+ - 35

OPAC-15-2050+OPAC-15-2000+ 36

Mald1.01+ 43MH128 - 44

Hi03e04z+ - 46E35M47-240-3+ 47

185125 - 49

MC221b - 56MC041a+

E34M55-380+ 60

OPAC-11-0460 - 62CH03h03+ - 63CH03a08+ - 65CH05f04+ -Hi04g05+ 67

CH01b12y+ -OPT-06-1200 - 68

E35M51-75+ 69

PF13

441502 + -0

184627 -10

554693 -11

CH05h05z + -15

461022 +24

182529 # +27

CH02g01 +31

NH009b +46

5P13 +56

183891 # +63

441485 -

6O5 +66

CH05f04 +81

012-13

441808 -

442037 -MC023b -

0

E31M52-410 - 1MC225b -

461548+E36M51-360 -

2

MC032a - 3MC125b - 8

E32M52-85 - 9518676+ 15

184790+ 16OPD-01-1200+E34M48-181+ 21

CH01e01+ -PGD-1 - 24

E34M59-239 -

519152 -E34M48-182 -E35M53-177 -E35M53-314 -

461773 -

# 182874 -CH01g05+ -

25

OPAD-18-0680 - 26E36M57-253 - 30# 183655+ - 31

MS01a05 - 35442170 - 36

185549 - 37OPJ-06-1300 - 41

CH05d03+ - 44E33M51-300 - 47

OPT-02-0400 - 48184742 -

# 184110 -51

553959 -

552945 -

553118 -E35M50-69 -

52

185879 - 53CH03g06+ -

7B9a+ 54

E33M52-193+ 55E35M47-149-8+E35M47-151-7+ 59

PF14

441808 + -0

442037 + -1

1M11 +16

185082 +22

7P5 +26

441509 + -31

554678 + -32

185319 +33

443195 +62

526150 +73

552945 -87

012-14

E35M51-286 - 0

Hi03g06 - 11

# 182590 -

443085+18

LY37a+ - 19AAT-4 - 22

NZ02b01+ - 23LY26+ - 24

CH05a02+ - 25# 182459+

184477+ -27

E32M52-165+ 31526179 -

184899 -34

E31M52-110+ 37pB610b+ 38

CH01d08+ - 42184544+ - 43

Conf-24-seq+ 52554081+ 56

E35M51-230+ 61E31M52-214+ 62

462056 -

525795 -66

E32M52-114+ 70MdACS1+ - 71

OPAC-08-0630+CH02d11+ - 73

442008+ -

185550+ -

185550+ -

74

OPA-16-1800+

441762+ -75

442482+ -CH03b10+ -

76

E35M51-245+ 82E31M52-164+ 84

441511+ -

526908+ -85

526299+ - 86

# 182445 - 90Conf-19--SSR+ 92

CH02c09+ 95# 183710+ 99E36M51-101+

460791+ -

441510+

461923+ -

100

460798+ - 101

461175 - 108

553104 - 109

PF15

461263 + -0

NZ02b01 +/-65B20 +

1O3 +7

184280 # +9

184477 + -10

184574 + -31

CH01d08 + -34183149 # + -36

184899 + -39

519690 + -41

184708 + -42

526669 + -45

462056 + -62

526576 + -71

526173 + -78

552762 + -81

182599 # + -82

526885 + -84

461423 + -88

182445 # -97

526167 +99

11B12 + -103Hi23g12 -106183710 # + -107

9D2 +108

012-15

CH02a03+ - 0442923+ -

441883+ -2

Ma+ - 3CH05e04+ - 12MC001b+ 13

MC044+ -LY05b - 18

MC050+ -MC242+ - 21

E34M48-198+ 25MC078+ - 26

Hi04e04+ - 28526724+ - 29

442132+ - 30Mald1.09+CH05a04+ - 36

Mald1.02+ 37Mald1.06+CH05a04+Mald1.03+

38

185214+ 39E35M51-67+ 41462075+ 43

462051+ 44MC191+

OPJ-01-0950+MC221a+

45

OPAF-13-0900+OPAF-07-0640+

MC041b+46

CH03a08y+P137-1250 -

pAP260b+

# 184079+

47

E32M52-113+E32M52-330+

CH04f10+ -

# 183165 -MC057b+

E35M47-156-6+

441862+4G11 -

50

HB03AT+ -E36M59-177+

LY27a+ -51

# 183930 -OPAG-15-0680+

52

# 183421 - 63

PF16

CH05h05y +0461640 + -1Ch02a03 +28K19 + -

7A6 +5

443159 +6

461310 +

525633 +

185494 +

184045 # +

442923 + -

442679 + -

441883 + -

185094 +

7

186214 +

183169 # +8

3D6 + -16Hi04e04 +/-30

CH05a04 +/-54442727 + -

184122 # + -56

552929 + -65

184362 +66

553235 + -69

442544 + -

441862 + -71

HB03AT -72Hi02c07p + -

184722 + -73

12P22 + -76

4J15 + -78

CH04f10 +/-93

012-16

Fig. 2 continued

652 Mol Breeding (2012) 29:645–660

123

was hybridised to the same DArT array used for

Prima 9 Fiesta. Additionally, several previously

mapped SSR markers were included to confirm the

DArT marker alignment. A similar number of

polymorphic DArT markers was obtained (774 in

2000–2012 vs. 776 in Prima 9 Fiesta), in addition to

a similar call rate (97.3%) and a similar redundancy

level, leading to a comparable number of unique

single locus markers (260 vs. 247).

The two mapping populations were shown to have

70 common polymorphic DArT markers that consis-

tently aligned homologous linkage groups with regard

to their identity and orientation for all 17 linkage

groups of apple (Fig. 2). Several cases of minor

differences in marker order were observed, depicted

as the crossing lines in Fig. 2. The overall consistency

in the identity and orientation of the linkage groups and

the marker order show that the DArT markers support

the alignment of the mapping populations.

DNA sequencing of DArT markers

and redundancy estimation

In the mapping process, DArT markers were classified

as redundant when they showed identical scores among

the progeny, leading to clustering at one genetic

position. Such clustering may be caused by high DNA

sequence similarity or tight genetic linkage of the

markers. To obtain an estimate of sequence-based

redundancy, we sequenced 384 clones from the PstI/

AluI DArT array. We performed a local pairwise

‘‘blast’’ of all of these sequences and then clus-

tered them into bins of highly similar sequences

(e \ 1.0E-50), using a Perl script developed in-house

(DArT PL unpublished). As Fig. 3 shows, the number

of clones per bin varied from one (278 bins) to four (one

bin only). There were 324 sequence bins identified;

therefore, the percent of redundant clones in the initial

sampling of the 384 clones was 15.6% when based on

the sequences. Since these 384 sequenced clones

represent only 2.6% of the 14,592 clones used for

printing on the slides, the real redundancy was higher.

Fitting the observed data from Fig. 3 to a Poisson

distribution, we deduced that sequence similarity led to

approximately 50% redundancy within the total set of

clones.

Comparison of these DNA-sequences to sequences

in NCBI GenBank databases showed that close to 90%

of BlastN and TblastX searches returned highly signif-

icant similarities to EST sequences (Online Resource

2). This indicates that the PstI/AluI DArT clones were

derived mainly from genes or gene-like sequences.

Alternative complexity reduction method

The high proportion of redundant markers hampers

the statistical and genetic analyses of the data.

Therefore, we wondered whether marker redundancy

could be decreased by a less stringent complexity

Fig. 3 Frequency distribution of 384 DNA-sequenced DArT

markers from the standard PstI/AluI method. If DNA

sequences of one or more clones were highly homologous to

each other, then these clones were clustered into a common

bin. The 384 markers provided 324 bins

CH04c06y+ - 0E33M52-333 -

CH04c10+ - 1

442865+ 2FDH-1 - 5

461519 - 6

553948 -

443198+ -8

519569 - 9

184490+ - 10E35M48-245 - 11

4F11 - 13# 182634+ 16

CH01h01+ - 21MDMADS_1+ 24

MC098+ 26461612+

E35M52-305+32

MC228c - 33

GE212858-SSR+ 48MC121+ - 49

MC012a -

460877+52

E36M51-133+ 53E33M51-265 - 59E31M52-238+ 64

441670 - 69E35M51-385+

MC224b+ - 70

185405 -MC052b+

72

S+ -E35M47-137-9+ 73

E35M52-117+E35M48-105+ 74

Conf-23-seq+OPAD-12-0580 - 75

AAT+ - 76CH05d08 - 77MC115a+ - 80

# 183185+ 82

PF17

184490 +0

461367 + -4

184664 + -

182816 # + -

461023 + -

526235 + -

5

184746 + -

186513 -6

553948 -7

525628 + -8

183635 # + -

184756 + -

186441 + -

183853 # + -

9

182634 # + -

526188 -12

CH01h01 +/-18525524 + -

184808 + -21

460877 +37

8C17 +44

183534 # +60

5N4 +62

461202 +

461443 +63

182778 # +65

10L5 +66

525667 +68

012-17

Fig. 2 continued

Mol Breeding (2012) 29:645–660 653

123

reduction method and whether such an alternative

approach could also be useful in increasing genome

coverage. The standard complexity reduction method

was based on PstI/AluI digestion. The alternative

method that we examined here was based on PstI/

EcoRI/MboI digestion, which resulted in a larger

number of fragments, so the chance that a clone was

sampled multiple times diminished. The alternative

array was used for the genotyping of 244 progenies of

population 2000–2012, all of which had also been

genotyped with the standard method. The maternal

map of the heterozygous parent 1980-015-025 was

constructed using DArT markers from both complex-

ity reduction methods. Table 2 shows the number of

spotted clones per complexity reduction method, the

number of polymorphic maternal markers obtained,

the number of maternal markers that could be mapped

and the number of ‘unique’ markers. Figure 2 shows

the resulting maps. Table 2 and Fig. 2 led to the

following conclusions:

1. The degree of redundancy was lower for the

alternative method;

2. The two methods gave a similar genome coverage;

3. There are no clear indications that the two

methods differ in the genomic regions for which

they raise polymorphic markers;

4. Performance of both methods increased genome

coverage compared to application of one method

only.

Discussion

Comparison of DArT with other marker

technologies

After being initially developed for rice, DArT

markers have been developed for many additional

plant species (Jaccoud et al. 2001; Xie et al. 2006).

These include barley (Wenzl et al. 2004), wheat

(Akbari et al. 2006; White et al. 2008), cassava (Xia

et al. 2005), Arabidopsis (Wittenberg et al. 2005),

pigeon pea (Yang et al. (2006), oat (Tinker et al.

2009), sorghum (Mace et al. 2008) and many others

(collated at www.diversityarrays.com/publications.

html). The present study demonstrates the perfor-

mance of DArT technology for low-cost, high-

throughput genotyping in apple (Malus).

Several lines of evidence support the utility of DArT

for apple genomics studies. First, the call rate and

reproducibility appear to be high. Non-DArT marker

data required repeated examinations for identification

of erroneous data, consuming many months of labour.

DArT markers, however, did not require this laborious

scrutinising; DArT genotyping was fully automated

and more accurate than other marker systems. The non-

DArT markers were gel-based systems (i.e. RFLP,

RAPD, AFLP, SSR), and were scored manually.

Second, the DArT markers integrated smoothly into

the existing Prima 9 Fiesta map. Only one marker

could not be placed (0.4%). This percentage is very low

compared to that found in other marker systems, such

as RFLP, RAPD, AFLP and SSRs. Also, DArT

markers were robust among different mapping popu-

lations, allowing for map alignment.

The standard DArT array gave similar numbers of

non-redundant markers in the two mapping popula-

tions, indicating that it is robust over populations.

Moreover, the majority of these markers were

population-specific, indicating that the extensive pool

of clones that are not polymorphic in one population

are a vast reservoir of possible new markers in other

populations. Thus, the DArT array is applicable over

a wide range of mapping populations. The number of

unique markers is therefore expected to increase

further in more extensive studies.

Table 2 Number of DArT clones and resulting markers from two complexity reduction methods for the maternal map of population

2000–2012

Complexity

reduction

method

Number of

spotted clones

Number (and percentagea)

of segregating markers

Number of

mapped

markers

Number (and percentageb)

of redundant markers

Number (and percentagea)

of mapped markers after

removal of the redundant ones

Standard 14,592 547 (3.7%) 542 282 (52%) 260 (1.8%)

Alternative 6,144 105 (1.7%) 104 24 (23%) 80 (1.3%)

a as % of the number of spotted clonesb as % of the number of mapped markers

654 Mol Breeding (2012) 29:645–660

123

DArT lends its general applicability for wide

germplasm coverage to the hybridisation of PCR

fragments that are hundreds of basepairs long.

Polymorphisms are based on the presence or absence

of restriction sites and are insensitive to SNPs and

short indels in the hundreds of basepairs between the

restriction sites (Wittenberg et al. 2005). This is

reflected by the sequence data. Map-redundant DArT

markers were often based on clones that differed in

size and sequence but nevertheless showed identical

segregation patterns in mapping. For instance, the

three markers 183247, 183997 and 184057 showed

identical segregation patterns and therefore mapped

to the same position (LG10, Prima 9 Fiesta, LG4,

44 cM; Fig. 2, only 183247 is shown). The three

DArT fragments varied in size (479, 469 and 502 bp,

respectively) and exhibited some sequence polymor-

phism, as occurs for different alleles of a single gene.

Their map-redundancy was confirmed at the sequence

level, as ‘‘blasting’’ matched them to the same gene

(Online Resource 2). This insensitivity to SNPs and

short indels in the probe makes DArT robust for

applications on genetically diverse germplasm, in

contrast to the sensitivity of SNP arrays to similar

polymorphisms. The proportion of informative mark-

ers from SNP arrays drops quickly when applied to

germplasm that is genetically distinct from acces-

sions that were used in the design of the SNP array.

DArT appears to be less prone to this limitation.

DArT and SNP platforms are both suitable for

high-throughput genotyping, benefiting from auto-

mated scoring and data quality checks. The first

small-scale SNP arrays for Malus were developed

recently for Golden Delicious (Micheletti et al.

2011). Recently, initiatives have been undertaken

for worldwide collaboration on the development of

large-scale, multiple accession-based arrays. We

expect that DArT will also play a longer term role

because of its own specific advantages, including

wide applicability, as discussed above, and low cost

even when small numbers of accessions have to be

genotyped.

Impact of pedigree structure

Although the standard DArT array gave similar

numbers of non-redundant markers for both mapping

populations (247 for Prima 9 Fiesta vs. 260 for

2000–2012), differences were observed in the distri-

bution of these markers among the parents. Whereas

the proportion of maternal, paternal and bi-parental

markers were similar in Prima 9 Fiesta (35, 32 and

33%, respectively), unbalanced proportions were

observed in 2000–2012, with relative under-repre-

sentation of paternal markers and over-representation

of bi-parental markers (35, 20 and 45%). These

differences in representation reflect differences in the

pedigree structures of these populations (Fig. 1). The

father of population 2000–2012 arose from a cross

between two sibs, resulting in an expected level of

homozygosity of approximately 25%. This parent

would yield no segregating markers in these homo-

zygous regions. In addition, the parents of population

2000–2012 have common ancestors, Golden Deli-

cious and Ingrid Marie, reducing levels of allelic

diversity. This increases the number of bi-parental

markers that segregate for both the father and the

mother. Prima and Fiesta lack such recent common

ancestors. The distribution of segregating DArT

markers among the parents thus reflects the pedigree

structures, further supporting the suitability of DArT

for genetic studies.

Redundancy

Markers that perfectly co-segregate do not provide

additional genetic information, but slow down the

mapping process and lead to the statistical over-

weighting of that specific position.Redundant mark-

ers were therefore removed. This reduced the number

of polymorphic markers used in the mapping process

by about half. Markers that segregated in both

populations needed to be preferentially retained to

facilitate linkage map alignment.

Clustering of DArT markers can be caused by: (1)

an absence of recombination between the markers

due to tight genetic linkage; (2) sequence identity; or

(3) high sequence similarity derived from different

alleles from different apple accessions. The effective

population size of Prima 9 Fiesta was 121, which

can only partially explain the current high degree of

redundancy in the DArT markers as a result of a lack

of recombination between markers. Consequently,

sequence identity and high sequence similarity were

likely to be significant sources of redundancy. This is

consistent with our estimation from Fig. 3 that

Mol Breeding (2012) 29:645–660 655

123

sequence identity indeed led to approximately 50%

redundancy. Based on the sequence information, we

conclude that the clustering of PstI–AluI markers is

mainly due to sequence similarity among the mark-

ers, in addition to genetic linkage.

In classifying markers as ‘‘redundant’’ using a

mapping process, more than just similar mapping

positions were taken into account. For a proper

classification, the parental origin and linkage phase

have to be identical too. For example, JoinMap

mapped the bi-parental DArT markers 183313 and

184063 within 0.1 cM from each other. Considering

the size of the Prima 9 Fiesta population (n = 121

for the DArT markers) and the type of marker

(bi-parental), both markers belonged to the same

genetic bin; there was no evidence that they mapped

to different positions. Their scores did not indicate

any recombination. Although this suggests that they

are identical, their linkage phase was different: they

were in repulsion phase, indicating that these markers

come from different genomic positions. Indeed, DNA

sequencing confirmed a substantial sequence differ-

ence of the two clones (Online Resource 2).

The positive side of redundancy is that the

underlying markers can be regarded as repeats when

present on the same slide and thus confirm validity of

marker scores. The co-segregation of markers with

highly similar sequences highlights the high reliabil-

ity of the DArT markers.

DArT markers mainly derived from gene rich

regions

Our analysis of the sequences shows that 90% of the

sequenced markers are highly homologous to mRNA

sequences that are deposited in EST databases

(Online Resource 2). This indicates that the set of

DArT markers is highly enriched for genic regions.

This phenomenon has been observed previously in

other species like barley (Wenzl et al. 2006), wheat

(Akbari et al. 2006) and sorghum (Mace et al. 2008).

DArT markers are predominantly located in gene-rich

islands in the subtelomeric regions of chromosomes.

This is not surprising, as the PstI enzyme is

methylation-sensitive (Gruenbaum et al. 1981), and

targets hypomethylated, low-copy sequences, which

occur primarily in the gene-rich regions (Feng et al.

2010).

Comparison of complexity reduction methods

The standard DArT array developed here provided

moderate coverage of the apple genome (Fig. 2),

allowing for a quick start in QTL mapping experi-

ments. Coverage, however, was not uniform across

the entire genome. Enhancing the array with more

clones could increase genome coverage, but using the

standard complexity reduction method to do so would

not be efficient, due to sequence redundancy. There-

fore, we tested an alternative complexity reduction

method in order to develop more DArT markers and

improve the genome coverage.

Whereas the standard method only amplified PstI–

PstI fragments, the alternative method amplified

PstI–EcoRI fragments as well as PstI–PstI fragments,

yielding higher complexity with the alternative

method than with the standard method. We simulated

the number of fragments that would be amplified

using the published whole genome sequences of

Arabidopsis thaliana, and found that the alternative

would result in approximately 4.5 times more ampli-

cons in Arabidopsis than the standard method (Mark

Fiers, unpublished). The higher complexity of the

alternative method and the printing of fewer of these

amplicons resulted in less redundancy for population

2000–2012 (23%), compared to the standard method

(52%).

Despite the lower redundancy, the percentage of

clones leading to unique single locus markers was

low for the alternative method (1.3%) compared to

the standard method (1.8%; Table 2). The most likely

explanation is an unfavourable signal-to-noise ratio

due to the higher degree of complexity. The analysis

of raw image data, looking at the noise level, supports

this explanation (data not presented). Another possi-

ble explanation is a reduction in polymorphism due to

variation in methylation. Whereas the standard pro-

cedure only amplifies PstI–PstI segments, the alter-

native method also amplifies PstI–EcoRI segments.

The EcoRI enzyme is methylation-insensitive, and

thus possible polymorphism in methylation is not

used. Wittenberg et al. (2005) ascribed up to 8% of

the polymorphisms of the alternative method to

differences in methylation in Arabidopsis thaliana.

Importantly, a single standard DArT assay was

clearly capable of providing reasonable genome

coverage, as exemplified by the 17 linkage groups

of the Prima 9 Fiesta map, with non-redundant

656 Mol Breeding (2012) 29:645–660

123

markers distributed across all of the chromosomes,

albeit unevenly (Fig. 2).

Linked research

The genetic maps shown here are the basis for several

QTL studies that are currently underway, examining

metabolomics (Khan et al., submitted), disease resis-

tance, fruit quality traits and low allergenicity (Van

de Weg et al., in prep.). Additionally, the standard

DArT assay is being applied worldwide to a number

of mapping populations and to the construction of

consensus genetic maps (Van Dyk et al., in prep.). All

the markers in this study are being sequenced and

will be aligned with the apple genome sequence

(Velasco et al. 2010). This will allow for the

integration of the genetic positions of phenotypic

traits with the whole-genome sequence of apple,

thereby aiding in the search for underlying genes.

Acknowledgments This study was carried out with financial

support from the Ministry of Agriculture, Nature and Food

Quality, The Netherlands. Unpublished data from the European

projects DARE and ISAFRUIT were used, which were

supported financially by the Commission of the European

Communities under the Thematic Priority FAIR5 of the 4th

Framework Programme of RTD (Contract no. FP4-FAIR-CT-

1997-3898), and 5–Food Quality and Safety of the 6th

Framework Programme of RTD (Contract no. FP6-FOOD–

CT-2006-016279), respectively. Also, unpublished data from a

Voluntary Contribution project between the Australian

National Apple Breeding Program, and Horticulture Australia

Ltd, Australia (AP06009) were used. We are grateful to Mark

Fiers (Plant and Food Research, New Zealand), for simulating

the number of DArT restriction fragments in Arabidopsis, for

different combinations of restriction enzymes. We

acknowledge also James J. Luby and James M. Bradeen

(University of Minnesota) for their contribution in selection of

Malus genotypes for construction of libraries for the diversity

arrays.

Open Access This article is distributed under the terms of the

Creative Commons Attribution Noncommercial License which

permits any noncommercial use, distribution, and reproduction

in any medium, provided the original author(s) and source are

credited.

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