Construction of a dense genetic linkage map for apple rootstocks using SSRs developed from Malus ESTs and Pyrus genomic sequences

ORIGINAL PAPER

Construction of a dense genetic linkage map for applerootstocks using SSRs developed from Malus ESTs and Pyrusgenomic sequences

J.-M. Celton & D. S. Tustin & D. Chagné & S. E. Gardiner

Received: 17 October 2007 /Revised: 7 April 2008 /Accepted: 27 May 2008 / Published online: 2 August 2008# Springer-Verlag 2008

Abstract Marker-assisted selection (MAS) offers quickand reliable prediction of the phenotypes of seedlings inlarge populations and thus opens new approaches forselection to breeders of apple (Malus x domestica Borkh.).The development of framework maps enables the discoveryof genetic markers linked to desired traits. Although geneticmaps have been reported for apple scion cultivars, none haspreviously been constructed for apple rootstocks. We reportthe construction of framework genetic maps in a crossbetween ‘M.9’ (‘Malling 9’) and ‘R.5’ (‘Robusta 5’) applerootstocks. The maps comprise 224 simple sequence repeat(SSR) markers, 18 sequence-characterised amplifiedregions, 14 single nucleotide polymorphisms and 42random amplified polymorphic DNAs. A new set of 47polymorphic SSRs was developed from apple EST sequen-ces and used for construction of this rootstock map. All 17linkage groups have been identified and aligned to existingapple genetic maps. The maps span 1,175.7 cM (‘M.9’) and1,086.7 cM (‘R.5’). To improve the efficiency of mappingmarkers to this framework map, we developed a binmapping set. Applications of these new genetic mapsinclude the elucidation of the genetic basis of the dwarfingeffect of the apple rootstock ‘M.9’ and the analysis of

disease and insect resistance traits such as fire blight(Erwinia amylovora), apple scab (Venturia inaequalis) andwoolly apple aphid (Eriosoma lanigerum). Markers fortraits mapped in this population will be of direct use toapple breeders for MAS and for identification of causativegenes by map-based cloning.

Keywords Apple . Genetic map . SSR .Molecular markers .

EST

Introduction

The cultivated apple (Malus x domestica Borkh.) is fourthin the global fruit market with more than 62.4 millionmetric tonnes produced every year (FAO 2005) and can beconsidered as one of the most economically importanttemperate fruit crops. To maintain this position, the demandfor new apple rootstock cultivars that confer desirable traitssuch as specific architectural and physiological charactersfor ease of orchard management, superior fruit quality anddisease and pest resistances needs to be addressed.However, direct selection for the majority of these traitscannot be carried out before several years of growth aftergrafting, which results in a long generation time. If priorknowledge of linkage relationships between marker lociand these characteristics were available, undesirable indi-viduals could be eliminated from progeny populations byusing marker-assisted selection (MAS). High-qualitygenetic linkage maps that enable the study of wholegenome structure and the localisation of genes of interestand permit the detection and analysis of quantitative traitloci (QTLs; Tanksley et al. 1989) are an essential tool forbreeders who want to use MAS. Although several high-density linkage maps have been constructed for apple

Tree Genetics & Genomes (2009) 5:93–107DOI 10.1007/s11295-008-0171-z

Communicated by O. Savolainen

J.-M. Celton :D. Chagné : S. E. Gardiner (*)Horticulture and Food Research Institute of New Zealand Ltd,Palmerston North Research Center,Private Bag 11030,Palmerston North 4442, New Zealande-mail: [email protected]

D. S. TustinHorticulture and Food Research Institute of New Zealand Ltd,Hawkes Bay Research Center,Private Bag 1401,Havelock North 4157, New Zealand

(Maliepaard et al. 1998; Liebhard et al. 2003; Calenge et al.2005; Silfverberg-Dilworth et al. 2006; Kenis andKeulemans 2005), these have all been developed fromscion cultivars or selections. Despite the crucial influenceapple rootstocks have on tree architecture and physiology,fruit quality and disease resistance, no genetic map hasbeen developed for them until now.

One feature of published apple maps is the presence ofsimple sequence repeat (SSR) markers. In apple as in otherplants, SSRs are abundant and generally uniformly distrib-uted in the genome (Morgante et al. 2002). SSRs are verypolymorphic due to the high mutation rate affecting thenumber of repeats (Hemmat et al. 2003), and they are co-dominant. More than 300 SSR markers have already beendeveloped and mapped in apple (Guilford et al. 1997;Gianfranceschi et al. 1998; Liebhard et al. 2002; Silfverberg-Dilworth et al. 2006) as well as in other species of theRosaceae family, such as pear (Pyrus communis; Yamamotoet al. 2002a, b, c; Yamamoto 2007; Oddou-Muratorio et al.2001; Fernández-Fernández et al. 2006), peach (Prunuspersica; Dirlewanger et al. 2002; Sosinski et al. 2000;Testolin et al. 2000), cherry (Sosinski et al. 2000) andraspberry (Graham et al. 2004).

Because they are based on sequence-specific polymerasechain reaction (PCR) amplification, SSRs are transferablebetween genetic maps within the same species and can beused as orthologous markers between species. For instance,apple SSRs were successfully used as DNA markers in pear(Yamamoto et al. 2001; van Dyk et al. 2005). However,very few SSRs developed from pear have been mapped inapple (Silfverberg-Dilworth et al. 2006), and as thesespecies are closely related, pear SSRs represent a consid-erable potential source of markers that have not beenexploited for apple genetic studies.

In the past few years, several sequencing projects haveproduced more than 250,000 expressed sequence tags(ESTs) for apple (Newcomb et al. 2006; Naik et al. 2006).SSRs associated with these sequences constitute a largeresource of markers that have remained largely unexploited.Moreover, as EST-based SSRs are located in conservedcoding regions, they are often more transferable betweenspecies (Decroocq et al. 2003) than SSRs from genomicsequences.

The investment needed to construct a genetic map can beconsiderable, as it requires the analysis of hundreds ofmarkers over a relatively large number of plants and addingnew markers increases this development cost. In order toincorporate new markers onto an existing genetic map, withreduced genotyping costs but still keeping a high accuracy,a strategy named bin mapping, or selective mapping, wasdeveloped (Vision et al. 2000). This method is based on theselection of a specific set of highly informative seedlingschosen for the number and position of crossover sites. The

development of bin mapping requires the preliminaryconstruction of a framework map (Vision et al. 2000).Once this has been obtained, bin mapping can be used toadd new markers, such as has been done in peach (Howadet al. 2005), wheat (Johnson et al. 2007) and melon(Monforte et al. 2007). Despite the advantages of efficiencyand cost saving that this method conveys, it has notpreviously been reported in apple.

The purpose of our study was to generate genetic mapsfor the two apple rootstocks ‘Malling 9’ (‘M.9’) and‘Robusta 5’ (‘R.5’). ‘M.9’ rootstock, also known as ‘Jaunede Metz’, is the most commonly used rootstock throughoutthe world because of its exceptional physiological charac-teristics, such as its capacity to dwarf the scion (Websterand Wertheim 2003). The second parent, ‘Robusta 5’, is avigorous rootstock that is resistant to several pests anddiseases, such as woolly apple aphid (Eriosoma lanigerumHausm.; Bus et al. 2008) and fire blight [Erwiniaamylovora (Burrill)] (Aldwinckle and Beer 1979). Parentalmaps were constructed using published SSR markers fromapple and pear as well as newly developed SSR markersderived from apple ESTs. By comparing these maps withother apple and with pear maps, homologous linkagegroups were identified. Finally, a bin mapping set wasdeveloped to improve the efficiency of mapping newmarkers on the initial framework map.

Materials and methods

Plant material and DNA extraction

Ninety-four F1 individuals obtained from an interspecificcross between the dwarfing rootstock ‘M.9’ (Malus xdomestica) and the vigorous rootstock ‘R.5’ (Malus xrobusta) were used in this study. These 94 individuals wereselected from a progeny of 146 individuals developed in1999 at the Hawke’s Bay Research Centre of the Horticul-tural and Food Research Institute of New Zealand(HortResearch). Seedlings were grown on their own rootsfor their first year then used as rootstocks to evaluate theirdwarfing capacity. Plants from this cross were grown asstoolbeds. Leaf material was harvested from these stoolbedsand DNA was isolated according to Gardiner et al. (1999).

SSR markers developed in apple

A total of 185 published SSR markers were tested forsegregation across a set of six progeny plants and bothparents. These included 76 ‘CH’ SSRs (Liebhard et al.2002), 75 ‘Hi’ SSRs developed by the HiDRAS consortium(Silfverberg-Dilworth et al. 2006), 17 ‘GD’ SSRs withknown or unknown map position (Hemmat et al. 2003),

94 Tree Genetics & Genomes (2009) 5:93–107

four ‘MS’ SSRs (Liebhard et al. 2002), seven ‘NZ’ SSRs(Guilford et al. 1997), five ‘NZms’ SSRs (Chagné et al.2007; Bus et al. 2008) and the ‘Col’ SSR (Hemmat et al.1997). Twenty-seven SSRs developed from genomiclibraries at HortResearch (‘NZmsPal’, Erik Rikkerink) werealso tested for segregation. Primer sequences for ‘Pal’ SSRsmapped in this study are given in Table 1. All segregatingmarkers were then screened over a set of DNA from 94individuals. The SSR amplifications were performed asdescribed by Gianfranceschi et al. (1998) in a Hybaid MBSSatellite 0.5G Thermal Cycler (Thermo Electron, Waltham,MA, USA).

SSRs developed from apple ESTs

SSR motifs were detected in the HortResearch apple ESTdatabase using an automated bioinformatics tool as de-scribed by Newcomb et al. (2006). The selection for primerdesign was made on the basis of the type and length of therepeated motif in the sequence. Tri- and tetranucleotidewere favoured over dinucleotide repeats, and the length ofthe SSR motif was more than 12 bp. Primer pairs weredesigned for 130 SSRs using Primer3 (Rozen and Skaletsky2000). The theoretical melting temperature of the PCRprimers was approximately 60°C, and the amplification

Table 1 Names and primer sequences of NZmsPal SSR markers mapped in this study

Forward primer sequence Reverse primer sequence

NZmsPal8 GGCACAAGCACAAGGAAACA GTTTGAGCCAGTCCATTTTTCCCTATNZmsPal13 TCGATGAACAAGGCCCAAAG GTTTAGGGGGACGGAAGGAACAAGNZmsPal36 CCTCAACAAATATAAGACTCTCTC GTTTCTCCACTCTGTCCGTACATTNZmsPal45 AAAACCCAACACCACAGC GCTTCTTTGGATTCTGGATGNZmsPal51 GATTTTCTGATAATCCTGCC GTTTAAACAACTCCAGCTCTGCNZmsPal92 GTTTCTGGTTTCACTGGCATT GTTGCCACATTTTCACCATANZmsPal213rd CAACCTTTCTCTCATTCACTC GTTTCCTTTTATGTACCGGCTTNZmsPal443ird AAAAGCTCTCTCACTCCC GTTTATCTGCAAATCTGAGACC

Table 2 Name and primer sequences of the SCAR and SNP markers mapped in the ‘M.9’×‘R.5’ genetic map

Forward primer sequence Reverse primer sequence Reference

SCARsNZscOPL19 ACCTGCACTACAATCTTCACTAATC GACTCGTTTCCACTGAGGATATTTG Bus et al. 2002NZscOPC05 CCCAGTCACTAACATAATTGGCACA CCCAGTCACTGGCAAGAGAAATTAC Bus et al. 2008NZscOPC20 TCTCTAACTCAATAACTCCCAAGAC ACTTCGCCACCATTATCACTCCTGA Bus et al. 2008NZscAZ16AC15 GGCGAACTGGATGGCCAAAG ACGCTCCACCAAACCACACT Gardiner et al. 2003NZscAY17AB16 CACCAAGAATGCCAGGTGCAG TCGGGGTCGTRAAAATGTGATAT Gardiner et al. 2003AT20SCAR ATCAGCCCCACATGAATCTCATACC ACATCAGCCCTCAAAGATGAGAAGT Markussen et al. 1995CH01K08_SCAR GAACACTGGGCAAAGGAAAC TAAAAGCCACGTTCTCTCGC Gygax et al. 2004AD13SCAR GGTTCCTCTGTAAAGCTAG GGTTCCTCTGCCCAACAA Boudichevskaia et al. 2004NZscAE16 CTGGAGGTAGTGGTGGTGGATA AAGGGCAAGATAGAGAGGTCATTT Rusholme Pilcher et al. 2008NZscAI02 AGCCGTTCAGACCAGGAAAG AGCCGTTCAGTAGAATCACAG Rusholme Pilcher et al. 2008NZscEB108994 TGCTTCCTTCGTCTATTGGA TCACTTTCACTTGTTTCATACGC Rusholme Pilcher et al. 2008NZscCO901385 TGTTGGCATCGTATATTCCTCA CGACATTTCATATCCCTCAAGTAGCNZscEB114476 TTCAGACATACACCGAAACAAA ACCGAAAGTAGAAGGGCAGANZscSI GTTCACGGTTTGTGGCCTTC Rev 1-GACCTCAACCAATTCAGTC

Rev 2- GACCTCAACCAATTCAGTSNPsNZsnEG631316 GTTGGGTGAGCTAGAGATATTC GATACTGCTGGGAACGTCAGGA Chagné et al. 2007NZsnEB135547 CACCCGAACCCCAACGGCCA CTCTCCAGCTCCGCCACTG Chagné et al. 2007NZsnEB147206 CAAGGGCTAACGGAAAAACA TCTCCCCTAAATCCTCATGCNZsnEB39353 GGAAAGTGGCTCAAATGGTC CGTTCAAAACACCCTGGCTANZsnEB15133 TGTCAAGGAGGGAGACTACGA AACCAAGAGGCACAAGGAAANZsnCN943818 CGGGAAGAGGAAATGTGATT TGAACAGCTCATCGTCGGTANZsnEB120945 ATGTTTCTCCAGAGGCTTCA TCAATTTCACAAAGGGCAAANZsnDQ644205 TGATGCCATGAAGGAGTTTG GCCATAATTTACCGGCTTTCNZsnCN580831 GTCTTCCGGAAACAAAGCAA TCATGCTCGTGGGATTGTTANZsnCN946839 TCACCAAGTACGCTGGCC AGTCAGTTGCAACGGGAAATNZsnDR033889 CGAAGAATTTTCACTTTTTCTGAT GACTTCTCAGTGAGGCGTGA

Tree Genetics & Genomes (2009) 5:93–107 95

product length was kept between 100 and 400 bp. PCRamplifications were performed as described by Gianfrance-schi et al. (1998) with cycling modifications: an initialdenaturation step at 94°C for 2 min and 30 s was followedby four cycles of 94°C for 30 s, 60°C for 1 min, 72°C for 1min where the annealing temperatures was reduced by 1°Cper cycle, and then followed by 30 cycles of 94°C for 30 s,55°C for 1 min, 72°C for 1 min and a final 5-min 72°Cextension.

SSR markers from pear

A total of 117 SSRmarkers developed from pear (Yamamotoet al. 2002a, b, c; Yamamoto 2007; Oddou-Muratorio et al.2001; Fernández-Fernández et al. 2006) were tested forsegregation. PCR amplifications were performed as de-scribed above, but with an annealing temperature of 55°Cfor the first of the four touchdown cycles.

SSR analysis

All SSR markers screened over the ‘M.9’×‘R.5’ populationwere genotyped using a capillary electrophoresis system:the CePro 9600 TM (Combisep, Ames, IA, USA). Thiselectrophoresis system has an estimated sensitivity of twobases (although no study has been conducted to confirmthis sensitivity), and no sizing method was implemented tomeasure the size of the SSR alleles. PCR products weredesalted in 96-well microplate devices UNIFILTER®350 μl (Whatman®, Clifton, USA) using Sephadex™G-75 Superfine (Amersham, Uppsala, Sweden) beforeelectrophoresis. Multiplexing was performed when theamplification products differed in size.

SCARs, SNPs and RAPDs

A total of 82 sequence-characterised amplified region(SCAR) and 21 single nucleotide polymorphism (SNP)markers were tested for segregation. Primer sequences forSCAR and SNP markers mapped in this study are presentedin Table 2. PCR reactions for SCARs and SNPs werecarried out in a total volume of 16.5 μl containing: 1.5 ngDNA, 18 mM Tris–HCl pH 8.4, 46 mM KCl, 0.1 μM ofeach dNTP, 1.3 mM MgCl2, 0.08 μM each of forward andreverse primers and 0.44 U Platinum® Taq DNA polymer-ase (Invitrogen). Amplifications were performed in aHybaid MBS 0.5G PCR thermal cycler under the followingconditions: an initial denaturation at 94°C for 2 min 45 sfollowed by 40 cycles of 94°C for 55 s, the temperaturespecified for each marker for 55 s, 72°C for 1 min 39 s anda final 10-min 72°C extension was included. Forty of the 42polymorphic random amplified polymorphic DNA (RAPD;Operon Technologies) markers had previously been

screened over the ‘M.9’×‘R.5’ population in the course ofusing bulked segregant analysis to identify markers linkedto dwarfing of a grafted scion (Rusholme Pilcher et al.2008; Celton, unpublished). The RAPD marker S65 is fromConner et al. (1997). RAPD reactions were carried out asfor SCARs and SNPs except that 1% of formamide wasadded to the PCR mix, and the annealing temperature was37°C. All amplification products were separated on 0.9%agarose gels in 1× TAE buffer and stained with a solutionof ethidium bromide.

Map construction

Linkage analysis was performed using JoinMap version 3.0(Van Ooijen and Voorrips 2001) with a LOD score of 4 forgrouping. Genetic maps were constructed independently foreach parent using informative markers and based on a firstset of 93 individuals. In a few cases, a marker wasdiscarded during the mapping stage where its presencecaused inconsistencies in the map. Such markers wereidentified after integration of all markers of a linkage groupand confirmed by visual identification of double recombi-nants. Parental maps were aligned using fully informativemarkers, and the linkage group numbering was assignedbased on SSR markers in common with published maps(Maliepaard et al. 1998).

Table 3 SSR polymorphism in the ‘M.9’×’R.5’ population

SSR origin Markerstested

Markersmapped

Genomic (apple) CHa 76 56 (74%)Hib 65 37 (57%)GDc 17 12 (70%)NZd 7 2 (28%)MSa 4 1 (25%)Col SSRe 1 0NZmsPalf 27 8 (30%)Total 197 116 (59%)

EST-based(apple)

New EST-SSR 130 47 (36%)NZmsg 5 5 (100%)HiDRAS EST SSR 10 7 (70%)Total 145 59 (41%)

Transferred Pearh 117 49 (42%)Total 459 224 (49%)

a Liebhard et al. (2002)b Silfverberg-Dilworth et al. (2006)c Hemmat et al. (2003)d Guilford et al. (1997)e Hemmat et al. (1997)f E. Rikkerinkg Bus et al. (2008), Chagné et al. (2007)h Yamamoto et al. (2002a, b, c, 2007), Oddou-Muratorio et al. (2001),Fernández-Fernández et al. 2006


Tab

le4

Nam

es,prim

ers,SSRmotif,origin

oftheEST,

type

ofmarkerandmap

positio

nof

thenew

setof

SSRmarkers

developed

GeneB

anknb

Forwardprim

ersequ

ence

Reverse

prim

ersequ

ence

Motifin

ESTdatabase

Originof

EST

Typ

eof

marker

Map

positio

n(linkage

grou

p)

‘Mallin

g9’

‘Rob

usta

5’

NZmsCN87

9773

CCCTCTGTTA

CTTTGACTCTTCTC

TGGTTTGGGTTGAAAATGGT

(AG) 11

‘Roy

alGala’

sloc

a1

1NZmsEB14

7493

aACACCCCCTCCCCAAACTT

GCACCCCTCTGATGTTGTG

(CCCT) 3

+(CT) 11

‘Roy

alGala’

mlocb

1NZmsEB14

9808

CGAGCCATGCTGATGATTC

TGTCCATCGATCCTCCAATG

(TC) 7(TATG) 8

‘Roy

alGala’

mloc

2NZmsEB15

3909

GTGGAGGGCACACACTCATA

AACAAAGAGGGAGGGAAGGA

(GAG) 4

+(TCA) 4

‘M.9’

sloc

2NZmsEB10

6592

CTCCCACTA

CTA

GCCAAACG

TTGGGATTTGAAGGACAGG

(TCC) 8

‘Roy

alGala’

sloc

2NZmsEB1194

05GCATGTCAAACCACTTGTCC

ATTCTCTCGCGGCAGTT

(CGT) 6

‘Roy

alGala’

sloc

2NZmsEB10

7305

AACTTCCAAACCCCATCTCC

AGAGCAACCTCACCATCTTCA

(TC) 7

+(TC) 9

‘Roy

alGala’

sloc

2NZmsEB17

7464

CTCCCACCCATCCCTCTA

AG

GCTCCTCTTCCCCTCCTCAT

(CT) 8

+(CT) 12

‘Roy

alGala’

sloc

3NZmsCN94

3818

CGGGAAGAGGAAATGTGATT

TGAACAGCTCATCGTCGGTA

(ATG) 4

‘Roy

alGala’

sloc

3NZmsDR99

9337

ACAGATTGGGATCTCGTGCT

CTTA

GCCTGTGTTGCACATTG

(GAA) 5(G

AT) 6

‘Red

Delicious’

sloc

4NZmsEB14

2980

CCAGTTGGTTA

TACAAATCGCAAAG

CCTGATCCTCAAAATTA

CAGCA

(AAAG) 3

‘Roy

alGala’

sloc

4NZmsEB15

5242

CCCCATCATCAAATCAGAAAC

GGAGGTGGTGTTGTCATTCTC

(TC) 9

‘Braeburn’

sloc

5NZmsEB13

4379

GATGGGATTA

TTA

CATGCATA

AGG

AGTGCGGCACGTA

GTGTTTT

(TTTA

) 6‘Roy

alGala’

sloc

55

NZmsEB13

2749

CTTTCCAGAGGAGGGCAGTT

GGTA

CACACTCTTTCCTCTTA

CATT

(AAAT) 8

‘Roy

alGala’

sloc

55

NZmsEB13

7770

TTGCTGGATCTGAAAACTA

GAGG

TCCATTTGCTCTCTCTTCCAA

(CT) 13+(CTT) 6

‘Roy

alGala’

sloc

5NZmsCN89

8349

GAGTTGGCAGAAAGAAACCA

CTGGGTGAAGACGAGATGCT

(TC) 19+(TTC) 6

‘M.9’

sloc

5NZmsCN86

2923

ATTTTCAAGTA

CCCCCAACC

CTTCTCCCTA

CAGCACAAGC

(ATC) 7

‘Roy

alGala’

sloc

5NZmsMDAJ168

1CCTGAGGTTA

TTGACCCAAAA

CACTCAGTTGGAAAACCCTACA

(CT) 25

GeneBank

sloc

66

NZmsEB13

2582

AGGCCACATCATA

CCTCCAC

CACCTTTGTTGTCGTTGTCG

(CAA) 6

‘Roy

alGala’

sloc

6NZmsCO75

4252

CTGCCCTCAAGGAGAATGTC

ACAGGTGCAGCAAAGGCTAT

(AG) 9

GeneBank

sloc

6NZmsEE66

3789

GGGGGACATA

AACCTTA

CCC

TAGTGGGGGCGTAGAAATTG

(AAC) 4

‘Roy

alGala’

sloc

7NZmsEB13

7749

ATCTCCTGCTGTGCTGGTCT

TCACCAAACACCAATCAACAA

(GA) 8

‘Roy

alGala’

sloc

7NZmsCN94

3067

AAATGGGGCACGCTA

TTA

TG

TGTGCCATTCAAGAGCTCAA

(TTC) 14

‘Roy

alGala’

sloc

7NZmsEB17

7006

AACCAATTCACCCGCCATA

CCTCTGCTGTGGCATGATT

(CCA) 4

‘Roy

alGala’

sloc

8NZmsCV88

0267

TGACCAAAAGAAAAGCAGGAG

AAATTGGCTGGAGGAGCTG

(CTT) 4

‘Roy

alGala’

sloc

88

NZmsCN90

0668

AGGCGTCAGCTGCTA

CTTTC

CTTTCCCACTTTCCTCACCA

(AG) 15

‘Sciros’

sloc

8NZmsEB1162

09AAAATCCCAATTCCAAAACC

TTGGAGCAGTGAAAGATTGG

(AGA) 10

‘Roy

alGala’

sloc

9NZmsCN94

3946

GGCGTGTTA

GGGATTCAAAC

TGGATCTCACCACAAAATGC

(ATTA

) 6‘Roy

alGala’

sloc

9NZmsCN89

2357

AGGTGAAGGTGGCTCAAAGA

AATTGTA

CGGCTCGGAACAG

(GA) 13

‘Roy

alGala’

mloc

9–11

NZmsCN89

9300

ACGAGCGCTCTCTCATCAC

TACGGGATTTTGTTGGTGCT

(TC) 15+(G

CA) 5

‘M.9’

sloc

10NZmsDR03

3893

CACTTA

GGGTGTA

TGGGTGTGA

TCATTTTGGGCAGGCACT

(AGT) 6

‘Roy

alGala’

sloc

11NZmsCN89

5337

GGCACCAACACATCCAAAC

CAGGAAGAGAACCACCGTACA

(CA) 6

‘Roy

alGala’

sloc

11NZmsEB15

3947

GGGAGAGTTA

GGGGAAAAGG

ACTGAGGCCTGCAACATA

CC

(ACC) 4

‘M.9’

sloc

11NZmsAB05

2994

TGCTA

TTA

GCTCCTCCTGAATTG

TTGTTGTTGCAGTGAAGGAA

(CT) 17

GeneBank

sloc

1212

NZmsEB1117

93TTGAGGGCTGCTTTCCAG

GGAGACATA

CAAGATTTCCAATGAG

(TC) 16

‘Roy

alGala’

sloc

1313

NZmsEB13

5714

CAAAGCCAGAACAGAGAGACAG

TGTTGGGATTGGAGTGATGA

(AGAC) 3

‘Roy

alGala’

mloc

13NZmsEB14

6613

AGAGTTCCGTTCCCCTCTCT

GTGGATTCGGAAATGCACTC

(TTCC) 8

‘Roy

alGala’

sloc

1414

NZmsCN91

4822

GACGATGATCAGGCCATTCT

TGTTCATGTCGGTGCTCAAT

(ACA) 6

+(A

GG) 4

‘Braeburn’

sloc

14


Nomenclature of markers

The names of published SSR markers were not modified.SSR markers developed from ESTs were prefixed with‘NZms’ followed by their GenBank accession code. Markersobtained from the same primer pair, but amplifying severalindependent loci, were qualified with an ‘a’ or ‘b’ suffix. TheSCAR and SNP markers developed in HortResearch areprefixed with ‘NZsc’ and ‘NZsn’, respectively, followed bytheir GenBank accession code. The RAPD marker namestarts with ‘NZra’ and then the Operon primer code followedby the indication of the fragment size in base pairs.

Development of a bin mapping set

The goal for the selection of the bin mapping set was theminimisation of the number of DNA samples to begenotyped while obtaining a maximum number of binscovering the whole genome. We only considered the plantsand co-dominant markers showing at least 80% of the datapoints in order to reduce the number of missing data points.Marker data used for the construction of the genetic mapswas sorted by linkage groups and ordered according to theirmap position. The linkage phase for each marker wasdetermined using JoinMap v3.0. The alleles of the markersin repulsion phase were recoded so that all markers withinthe same linkage group were in coupling phase. Followingthat, individuals were sorted according to the number ofcrossovers over the whole genome. After comparison of thelocation of the crossovers between the remaining individ-uals for both parental maps, a subset of individuals wasselected. This bin set was then tested to evaluate theefficiency of the method. For this, a two-step procedure wasemployed: first, a set of markers was genotyped over thebin mapping set, and second, the same markers weregenotyped over the remaining individuals used for the mapconstruction and analysed using JoinMap v3.0. Thegenotype for each marker over the 93 individuals wascompared to the genotype of the bin mapping set by visualinspection. The rough location of the markers as found bythe bin mapping method was compared to the map locationcalculated by JoinMap v3.0. The set of markers used forthis test consisted of 31 SSRs, including 21 developed fromPyrus, five previously published apple SSRs, and fivenewly developed EST–SSRs.

Fig. 1 Genetic map of ‘Malling 9’ (‘M.9’) and ‘Robusta 5’ (‘R.5’).Numbering of the linkage groups is according to Maliepaard et al.(1998). Newly developed SSRs from the EST database are prefixed byNZms and are indicated in green and underlined. SNP, SCAR andRAPD markers developed at HortResearch are prefixed, respectively,by NZsn, NZsc and NZra. Pyrus SSRs are indicated in red

bTab

le4

(con

tinued)

GeneB

anknb

Forwardprim

ersequ

ence

Reverse

prim

ersequ

ence

Motifin

ESTdatabase

Originof

EST

Type

ofmarker

Map

positio

n(linkage

grou

p)

‘Mallin

g9’

‘Rob

usta

5’

NZmsEB13

4400

TTCATCTTCACCGTCCTCCT

CCCCTCTTCTTA

TTGCTTCG

(TGTT) 3

‘Roy

alGala’

mloc

1515

NZmsCN90

9188

CCCTTCTTCTTTCACCACCA

TGAGGAGTTGCTGGGTGTCT

(CCT) 6

‘Braeburn’

sloc

15NZmsEB1172

66CATCCATGATCATTCAAGACC

CGTGGCCCTCTA

TATTA

AAGC

(CA) 11

‘Roy

alGala’

sloc

15NZmsCN87

8021

TAATCATGAGCGGAGGAGGA

ATGATTGGAACAGCGAGAGG

(AGC) 7

‘Roy

alGala’

sloc

15NZmsCO90

5522

CAGGGCACTGACAAAGACAG

AATTGGAGATTTGCGGTGTC

(AG) 6

‘Roy

alGala’

sloc

1616

NZmsEB14

7967

CTTTCTCTCTCTTCGCTCCAA

AGTGCCTTCGGATTCAACAG

(TC) 7

‘Roy

alGala’

sloc

16NZmsEB15

7320

TGACGAACAACTCCAACAATG

AAGCAAGAACCACCCGAAG

(GCAA) 3

‘Roy

alGala’

sloc

17NZmsEE66

3955

CGGAGGCCGCTA

TAATTA

GG

CCTGGAAAGAAAGTAAAAGGACAC

(TA) 7(TGTA

) 3‘Roy

alGala’

mloc

17NZmsEB13

7525

TCTTTCGCTGGTGTCCTCTT

GTGCTGCTTGCTGTTGTTGT

(TC) 6

‘Roy

alGala’

sloc

1717

aSinglelocus

bMultiloci


NZmsEB147493a0.0NH010a_b2.8

Hi12c0225.9CHVf126.8

NZmsCN87977333.9

KA4b40.7

‘M.9’ LG1

Hi02c070.0NH010a_b1.7CH03g12_a3.8

NZraAD12(450)23.8CHVf124.8NZscEB12318527.3NZmsCN87977327.5NH010a_a33.1

‘R.5’ LG1

NB124b0.0

GD12610.3AD13SCAR10.4CN58149312.5NZsnEB14720613.9CN49313922.6NZmsPal9224.9Hi05g1228.9Hi24f0433.4NH010a_c37.7NH033b38.0

NZmsPal13nw50.9NZmsEB149808b56.0CH02b1057.4CH02a0458.4CH03d1058.7CH05e0360.6NZsnEB13935368.1NZscEB13853872.5NZmsEB15390973.3NZmsEB10730578.1NZscOPL1981.4CH01K08_SCAR84.8

‘M.9’ LG2

CN5814930.0NZsnEB1472064.3AD13SCAR9.4NZraMA2(650)18.7NZmsEB11940525.2NZmsPal9230.1NH212a38.4NH012a40.0NZmsPal13nw41.2NZmsEB10659241.6CH02b1045.8BGT23bCH03d10CH02a04

46.0

NZraAG07(900)46.1Hi08f0547.8CH05e0349.8CH01c0651.0Hi07d1251.3CH01K08_SCAR61.1NZraAR10(700)61.8

‘R.5’ LG2

CH03e030.0

CH03g0719.0NZsnEB15513323.2

Hi03d0655.3

Hi04c1060.2

GD1273.1

NZraAR02(700)85.4NH030a87.6NB109a90.3

CH03g12_b106.0

‘M.9’ LG3

NZmsCV8812510.0CH03e030.2

CH03g0714.4

Hi03d0618.9Hi07d0824.8NZraAJ03(1050)25.9NZmsEB17746428.6NZmsCN94381833.0NB109a34.6

NZsnCN94381843.4

CH03g12_b73.9

‘R.5’ LG3

NH209a0.0NH011b1.0CH02h11a_b4.7CH01d035.0GD6b9.2

NB141b20.3

Hi23d1129.6

‘M.9’ LG4GD1620.0

CH02h11a_b13.5CH01d0314.6GD6b15.7NZraAV11(1800)18.7Hi07b02b19.7CH02h11a_a24.0NZmsDR99933726.1

Hi01e10b35.9

Hi08e0445.2NZmsEB14298045.7

‘R.5’ LG4

NZraAV11(850)0.0Hi01c04a11.9Hi04a0812.0NB115b14.3NZraAM18(700)15.8CH03a0919.6NZraAP07(450)22.7NZscAE1623.3NZscAI0225.1CH05e0627.5CH04g0929.2NZmsEB13437933.2NH041aa35.2NZmsEB13274936.3NZraAE02(1200)39.8NZmsEB13777042.3NZscEB10899444.3CH05f0648.9NZraAR10(1200)50.7NZraAQ06(1000)55.1NZraAJ14(1300)56.8NZraAF07(500)58.8NZraAQ06(850)60.1NZraAR15(900)61.9CH04e0373.5

‘M.9’ LG5

NZmsEB1552420.0Hi01c04b7.0Hi01c04a9.1Hi09b0410.9Hi04a0811.8NB115b14.3

CH03a0922.3

CH05e0630.9CH04g0936.1NZmsEB13437937.7NZmsEB13274942.3

NZmsEB13777052.2NZraAD02(400)54.0GD103GD13654.4

NZmsCN89834954.9CN44559955.8CH05f0657.9CH04e0364.6NZmsCN86292369.2

‘R.5’ LG5

NZ23g040.0

CH03d1210.9

NZsnEB12094517.6

‘M.9’ LG6

NZraAT03(550)0.0

NH027a9.5Hi08g0310.4NZmsPal3610.8NZmsMDAJ168110.9CH03d0712.2NZ23g0417.7NZmsPal443ird19.5CH03d1224.3

NZmsCV65899039.1

Hi07b0659.4NZmsCO75425261.8

‘R.5’ LG6

CN4447940.0

Hi03a1017.1

NZmsEE66378932.1CH04e0534.6

NZmsEB13774955.0

Hi05b0966.1

‘M.9’ LG7

EMPc1170.0

CN44479410.5

NZmsCN94306721.4

EMPc11138.3

Hi05b0951.0

‘R.5’ LG7

CH01c060.0

NB114a19.4NZscOPC2021.4NZmsEB17700622.3

NZmsCV88026730.9NZraAF13(1600)35.3

NZraAE12(1200)46.8NZscEB11447649.1NZmsPal213rd50.2CH02g0950.3NZmsCN90066860.8NZraAK06(1250)60.9NZmsEB10675361.1NH005b66.5EMPc11968.0Hi22g0670.4

NH201a84.2

‘M.9’ LG8

NH036b0.0

NB114a5.9

NZmsCV88026726.8NZraAK06(1700)35.1NH005b37.1NZmsEB10675337.2NZscOP0537.6NZraAR02(400)40.9NH213a43.6

Hi22g0652.8NH201a56.8

‘R.5’ LG8NB125a0.0

NZmsCN9439469.8

GD14216.3NH029a19.0NB104a23.6

CH01f03b34.7NZmsEB11620936.4NZraAV19(1600)36.9NZscCO90138538.5BCA14438.7NB130b41.7Hi05e0742.4NZmsCN892357a53.1Hi04a0556.5

‘M.9’ LG9

NZraAB07(1250)0.0GD1422.2NH029a4.2NB125a6.3

CH05c0722.4

Hi05e0732.8NB130b33.7NB134a37.9

GD15844.9

S6559.5

‘R.5’ LG9


CH02b070.0

AF571347.8CH02a089.4NZmsPal4511.1NH039a16.7CH02c1121.9NZraAQ06(1000)23.5

Hi01b0132.0

Hi08h1252.5Hi22a07NZmsCN899300a56.3

GD10056.6CH02b03b57.3

MS01a0369.7

‘M.9’ LG10

NH020a0.0

NH041ab18.8CH02b0720.3AF5713423.4NZraAP17(900)25.3NZraAP17(450)26.2CH02c1130.5

CH02b03b62.0

GD10067.3

MS01a0377.7

NZsnEG63131684.4

‘R.5’ LG10

NZmsAB1620400.0

CH04g0418.3CH05d1123.2CH05g0725.6NZsnEB135547(250)27.3NH207a28.5

CH01g1237.7CH04d02b40.6GD6a42.5

CH04d02a51.0

AT20SCAR61.1NZraA17(750)61.8

GD12776.9

‘M.9’ LG12

CH05d040.0

NZmsAB1620409.4

NZ28f0420.0NH207a20.7

NB104a30.3CH01d0931.8CH01g1232.7GD6a33.4Hi01e10a40.7CH01f0243.7CH04d02a46.7

NZmsCN899300b53.4

AT20SCAR60.8

GD12776.6

‘R.5’ LG12

CH05h050.0Hi04g053.6NZmsEB1386817.8

NZsnCN58083119.8

NH009b28.1

Hi03e0436.5NB133a_b40.7

CH05c0451.2CH03a0852.3

‘M.9’ LG13

Hi04g050.0

NZmsEB1386818.1NZraAY12(900)11.2

NZmsEB13571433.6NH009b38.3Hi03e0441.4NB133a_b44.8CH03a0847.5CH05c0449.2NZraAF13(400)52.2

‘R.5’ LG13

NZmsEB1466130.0

NH004a8.3

CH05e0525.6

NZmsPal44332.7

CH03a0239.0

NZmsPal5151.0

‘M.9’ LG14

CH05g070.0

NZmsCN9148225.7NZmsEB1466139.3

NH004a14.3NZraAW11(1200)16.6

NH035a31.0CH03a0233.9

NZmsPal5146.0

U7894852.1

NZmsCO86707058.0Hi03a0361.3NZsnCN90842065.2

‘R.5’ LG14

Hi02g060.0

NZmsEB13440017.6NZ02b0119.1

NH204a42.8

CH01d0860.6

NZmsEB11726680.6

NZmsCN90918886.9

NZsnEB135547(550)92.2NZraAD05(750)94.7

NB111a100.6

NZraAW11(650)115.3

CH03b10126.5

‘M.9’ LG15

Hi02g060.0

NZsnDR0338895.6

NZmsEB13440023.9

NZmsDT00192834.2

NH204a40.0

NZraAJ13(1200)56.1

NZraI14(550)62.2NZmsEB11726664.6NZscAY17AB1666.1

Hi07d1175.3

NB111a81.1

CH03b1093.5

‘R.5’ LG15

Hi22f060.0

NH007b11.4

CH05a0442.2

NZmsEB14796751.5

GD15458.7CH04f1062.8

‘M.9’ LG16

NH044b0.0CH02a035.4NH026a10.9Hi02h0811.8Hi22f0612.8CH05c0616.9NZmsCO90552218.1Hi15a1319.8

NH007b28.5

Hi01a0840.7Hi08f1242.2

CH04f1053.2

Hi04e0462.0NB133a_a65.4

‘R.5’ LG16

NZmsEB1573200.0Hi01d062.9

NZmsEE66395513.4AT00017414.3

CH04c0621.9

GD9635.5

NH013a_a45.1

Hi02f1252.6

NZscSI71.8

NZmsEB13752592.1

‘M.9’ LG17

GD960.0

NZmsEB1457648.4

GD15330.5CH02g0434.5

NH008b43.8

NZmsEB13752564.9

‘R.5’ LG17

Hi07d110.0

NZraAG02(500)13.0

NZraI14(200)22.5NZraAU15(900)25.7NZraAQ13(300)29.2NZmsCN892357b30.5CH02d0831.5CH04a1235.5NZraAZ13(400)39.2Hi02c0643.4

NB135a49.9

NZmsPal856.1

NZmsEB12806571.7

CH04d0779.4

NB105a86.4

‘M.9’ LG11

NZscAZ16AC150.0

NZmsDR03389319.2NZsnDQ64420520.1NZmsCN892357b29.0CH02d1230.6NZraAZ13(1150)31.5Hi02c0634.9NH013a_b36.2NZraAU14(2000)37.9Hi04g1138.5NH045a42.5NB135a44.8CH04g0750.6NB121a52.4NZmsCN89533756.8NZmsEB15394763.2NZmsEB12806564.5NB118a69.7CH04d0771.7

‘R.5’ LG11

Fig. 1 (continued)


Results

Apple SSR polymorphism

Out of 342 SSRs developed from apple, 175 (52%) werepolymorphic in the ‘M.9’×‘R.5’ population (Table 3). Ofthe 197 markers designed from genomic sequences, 116(60%) were polymorphic, including 56 ‘CH’, 37 ‘Hi’, 12‘GD’, two ‘NZ’, one ‘MS’, and eight NZmsPal. Of the 130new SSR markers developed from the apple EST database(Table 3), 119 (91%) amplified a PCR product, and ofthese, 47 (39.5%) were polymorphic. In addition to that, 12previously published EST–SSRs segregated in the‘M.9’×‘R.5’ population.

Fourteen of the new polymorphic EST-SSRs are dinu-cleotide repeats, 14 trinucleotide, eight tetranucleotide, and11 are compound SSRs (Table 4). Overall, compound SSRswere the most polymorphic (50%), followed by tetra- anddinucleotide SSRs (44% and 43%, respectively), while only19% of the trinucleotide SSRs segregated in the population.

Transferability of SSR markers from pear

All 117 pear SSR markers amplified a PCR product whentested on apple, and 49 (42%) were polymorphic (Table 3).Four (8%) pear SSR markers amplified more than one locusin apple.

SCARs, SNPs and RAPDs

In total, 18 SCAR, 14 SNP and 42 RAPD markers werepolymorphic in the ‘M.9’×‘R.5’ progeny.

Genetic map construction

Two parental maps (Fig. 1) were constructed using a totalof 316 loci (amplified from 296 primer pairs) genotypedover 93 individuals. One individual was removed from thedataset because the SSR data suggested that it was notproduced from a ‘M.9’×‘R.5’ crossing. Each linkage mapconsisted of 17 linkage groups (LG; see Table 5 for details)that correspond to the number of chromosomes in the applehaploid genome. The maps span a total of 1,175.7 and1,086.7 cM for ‘M.9’ and ‘R.5’, respectively. The parentalmaps could be aligned, as they had 82 markers in common,including 76 fully informative SSRs, three SCARs, oneSNP and two RAPDs. Based on the SSR markers incommon with other published apple maps, conservation ofthe marker distance and order was observed for both ‘M.9’and ‘R.5’, except for a few discrepancies: (1) a secondlocus was amplified for CH01c06 and was mapped on LG2(‘R.5’); (2) Hi07d08 was mapped on LG3 (‘R.5’) instead ofLG1 (Fiesta); (3) Hi01d06 (LG11 and LG16 in ‘Fiesta’ and

‘Discovery’, respectively) was mapped on LG17 (‘M.9’);(4) Hi07d11 (LG11 and LG16 in ‘Fiesta’ and ‘Discovery’)was mapped to LG15 (‘R.5’); (5) a second locus wasamplified by Hi01c04 and was mapped 2.1 cM away fromits first locus on LG5 (‘R.5’). When compared with thereference map ‘Fiesta’×‘Discovery’ (Silfverberg-Dilworthet al. 2006), the following discrepancies were also observedin marker order: (1) KA4b was mapped below CH-Vf1; (2)CH02b03 was mapped below Hi08h12; (3) Hi02g06 wasmapped above NZ02b01; and (4) AT000174 was mappedabove CH04c06.

Development and validation of a bin mapping set

The framework genetic maps of ‘M.9’ and ‘R.5’ weredivided into 113 and 106 bins (Table 5), with an averagebin length of 10.8 and 10.2 cM, respectively. A set of 14individuals, which will be hereafter termed the bin mappingset, was selected, each giving a single joint genotype. Thelongest bins identified were 39.5 and 32.5 cM for ‘M.9’LG17 and ‘R.5’ LG2, respectively (Table 5).

A total of 31 polymorphic markers, both SSRs andSNPs, were screened over the bin mapping set and theparents. Results of the comparison between the genotype ofthe new markers and the genotype of the frameworkmarkers flanking the bins are presented in Table 6.Twenty-three new markers exhibited a genotype thatcorresponded to one bin. Seven markers had a genotypethat did not correspond to any of the bins; however, theirrough location could be established by comparing adjacentbins and analysing the possibility of recombination betweenthem. Finally, the SSR marker Hi07d11, whose score didnot exactly match any of the pre-established bins, waspredicted to map at the top end of LG11 that was notcovered by the genetic map. All 31 markers were thengenotyped over the remaining 79 individuals from thepopulation, and their actual position in the genome wascalculated using JoinMap v 3.0. All the markers mappedclose to the location predicted using bin mapping (Table 6),including Hi07d11 mapping at the top of LG11.

Discussion

Development of a new set of EST-based SSR markersfor apple

A set of 47 new apple EST–SSRs was developed andmapped (Table 4). These markers were obtained bysearching for SSR motifs in an EST database, a processthat is less labour-intensive compared with time-consumingSSR development techniques based on the construction ofenriched libraries. A previous study reported the develop-


ment of EST–SSRs in apple (Silfverberg-Dilworth et al.2006). Our study showed a lower dinucleotide SSR successrate than what they observed (36% compared to 61%). Thiscan be explained by (1) the lower sensitivity of the capillaryelectrophoresis system we used to separate our SSRs and(2) by the low selection criteria applied, as some of the di-and trinucleotide SSRs tested had as few as six repeatedunits. This low stringency selection was applied because anemphasis was put on gene function rather than the size of theSSR motif. Indeed, 24 of our new EST–SSRs are locatedwithin candidate genes coding for functions of interest, suchas resistance gene analogues (RGAs). For instance, five EST-SSRs developed from RGAs were mapped on LG2, which isknown to contain several disease resistance gene clusters(Bus et al. 2008). This shows that EST–SSRs are asignificant source of functional markers that can bedeveloped for candidate genes while still keeping theirquality as SSR markers (i.e. they are transferable betweendifferent genetic backgrounds and suitable for relativelyhigh throughput genotyping for MAS).

Overall, a higher polymorphism was observed for di-and tetranucleotide repeats compared to trinucleotiderepeats. Di- and tetranucleotide repeats are usually foundin higher frequency in 3′ and 5′ untranslated regions ofgenes, while trinucleotides are preferentially found intranslated regions (Morgante et al. 2002). This unevendistribution of SSR motifs may be a result of mutationpressure and positive selection for specific single aminoacid stretches. A mutation in a mono-, di- or tetranucleotideSSR in the open reading frames would result in a frameshiftthat could change the translated protein structure andfunction. It is interesting to note that in our study, thetrinucleotide types TTC/CTT/TCC displayed a lowerpolymorphism (12%) than the AAC/CCA type (57%).

The eight tetranucleotide SSRs developed during thisproject are the first of their class to be mapped in apple.

Four of them amplified more than two different alleles inthe progeny, indicating that they are highly polymorphic.Tetranucleotide SSRs could become markers of choice forfingerprinting studies in apple, as is already the case inhuman DNA (Guarino et al. 2006), because of the low‘stuttering’ and larger size difference between alleles thatmakes it easier to differentiate them. The future screeningof these newly developed SSRs over a set of cultivars orwild accessions will make it possible to estimate their truelevel of polymorphism, determine their allele size range andselect the most suitable markers for genetic diversity studiesand association genetics.

Development of a dense genetic map for the applerootstocks ‘M.9’ and ‘R.5’

We have constructed the first genetic maps for applerootstocks, including the most widely used rootstock in theworld (‘M.9’) and a rootstock possessing some resistances towidespread pest and diseases, ‘R.5’ (Bus et al. 2008;Aldwinckle and Beer 1979). The maps contain 316 lociand span 1,175.7 and 1,086.7 cM for ‘M.9’ and ‘R.5’,respectively, whose length is comparable to the mapdescribed for ‘Fiesta’×‘Discovery’ (Silfverberg-Dilworth etal. 2006). The mapping of SSR markers in common makes itpossible to align the maps with published maps. With theexception of LG1, LG4 and LG6 for ‘M.9’ and LG1 andLG8 for ‘R.5’ (Fig. 1), the coverage of the linkage groups iscomparable to the reference map of ‘Fiesta’×‘Discovery’.Very few SSR markers mapping to LG1 have been publishedso far. Here, we report the development of two new SSRs onLG1: NZmsEB147493 and NZmsCN879773. LG6 of ‘M.9’is the smallest group of all (17 cM). The coverage of LG4 of‘M.9’ and LG8 of ‘R.5’ is not complete, and an estimatedportion of 20 to 30 cM in length remains to be covered. Inorder to fill the gaps in our linkage map, SSR markers that

Table 5 Detailed analysis of the number and type of SSR markers, length, marker density and number of bins for each linkage group of the‘M.9’×‘R.5’ map

Marker type Linkage groups

M91 R51 M92 R52 M93 R53 M94 R54 M95 R55 M96 R56 M97 R57 M98 R58 M99

SSR Apple 4 4 11 12 6 8 4 10 10 18 2 10 6 3 8 3 7Pear 2 2 3 3 2 1 3 − 2 1 − 1 − 2 4 5 5

Total markers 6 8 20 21 10 11 7 11 25 20 3 12 6 5 17 11 14Length (cM) 40.7 33.1 84.8 61.8 106 73.9 29.6 45.7 72.5 69.2 17.6 61.8 66.1 51 84.2 56.8 56.5Marker density inmarkers/cM

0.15 0.24 0.24 0.34 0.09 0.16 0.24 0.24 0.34 0.29 0.17 0.19 0.09 0.1 0.2 0.19 0.25

Number of bins 3 4 10 6 7 5 4 4 14 8 2 6 5 5 6 7 6Average bin lengthin cM

13.5 8.3 8.5 10.3 15.1 14.8 7.4 11.4 5.2 8.6 8.8 10.3 13.2 10.2 14 8.1 9.4

Longest bin in cM 25.9 21.0 18.6 32.6 32.1 30.5 19.3 14.6 15.8 21.8 10.9 20.3 22.9 16.9 25.5 20.9 18.4


were monomorphic in this population, but mapped in otherpopulations at positions where gaps are observed, could besequenced to identify SNPs in the alleles of ‘M.9’ or ‘R.5’that would map at the desired location

The ‘M.9’ and ‘R.5’ maps are mainly composed of SSRmarkers with relatively few markers of other types. Onlythe map ‘Fiesta’×‘Discovery’ (Silfverberg-Dilworth et al.2006) contains more SSR markers (more than 300). We

Table 6 Comparison between the map location of SSR markers estimated using the bin mapping set (14 individuals) and JoinMap (93individuals)

Marker LG Closest marker (bin mapping) Location on map (93 individuals)

NH030a 3 NB109 2.7 cM from NB109NB141b 4 CH01d03 15.3 cM from CH01d03NH041aa 5 CH04g09 6.0 cM from CH04g09EMPc119 8 NZraAK06(1250) 7.1 cM from NZraAK06(1250)EMPc111 7 NZmsCN943067 16.9 cM from NZmsCN943067EMPc117 7 NZmsCN943067 21.4 cM from NZmsCN943067NB115b 5 NZraAM18(700) 1.5 cM from NZraAM18(700)BGT23b 2 CH02a04 0 cM from CH02a04NB109a 3 NZraAR02(700) 4.9 cM from NZraAR02(700)NH027a 6 CH03d07 2.8 cM from CH03d07NB114a 8 NZmsCV880267 11.5 cM from NZmsCV880267NH005b 8 NZraAK06(1700) 2.0 cM from NZraAK06(1700)BCA144 9 CH01f03b 4.0 cM from CH01f03bNB134a 9 CH05c07 15.4 cM from CH05c07NB135a 11 CH04g07 4.4 cM from CH04g07NB121a 11 CH04g07 1.9 cM from CH04g07NH207a 12 CH01g12 9.2 cM from CH01g12NH009b 13 NZsnCN580831 8.3 cM from NZsnCN580831NH004a 14 NZmsEB146613 8.3 cM from NZmsEB146613NB111a 15 NZraAW11(650) 14.7 cM from NZraAW11(650)NH007b 16 CH05c06 11.6 cM from CH05c06Hi03a10 7 NZmsEE663789 15 cM from NZmsEE663789Hi05e07 9 NZraAV19(1600) 5.4 cM from NZraAV19(1600)Hi07d11 11 NZraAG02(500) 13.0 cM from NZraAG02(500)Hi08e04 4 NZmsEB142180 0.5 cM from NZmsEB142180U78948 14 CH03a02 18.2 cM from CH03a02NZmsCN935411 15 NH204a 6.5 cM from NH204aNZmsCN944871 15 NH204a 0.8 cM from NH204aNZmsEB137861 16 Hi22f06 1.0 cM from Hi22f06NZmsCN879773 1 CHVf1 7.0 cM from CHVf1NZmsEB117266 15 NZmsCN909188 6.3 cM from NZmsCN909188

Table 5 (continued)

Linkage groups

R59 M910 R510 M911 R511 M912 R512 M913 R513 M914 R514 M915 R515 M916 R516 M917 R517

4 12 6 8 10 9 11 6 6 5 8 7 6 5 10 9 64 1 2 2 5 1 2 2 2 1 2 2 2 1 4 1 1

10 14 11 11 21 13 14 9 10 6 12 12 12 6 14 10 659.5 69.7 84.4 86.4 71.7 76.9 76.6 52.3 52.2 51 65.2 127 93.5 62.8 65.4 92.1 64.90.17 0.2 0.13 0.13 0.29 0.17 0.18 0.17 0.19 0.12 0.18 0.09 0.13 0.1 0.21 0.11 0.09

7 6 6 9 10 8 8 5 5 5 6 10 9 5 3 7 78.5 11.6 14.1 9.6 7.2 9.6 9.5 10.4 10.4 10.2 10.8 12.7 10.4 12.5 21.8 13.2 9.3

14.6 24.6 31.5 17.5 19.2 18.3 23.2 15.8 22.4 17.3 19.2 25.2 18.3 30.8 28.5 39.5 22.1


have mapped 224 SSR markers in total on ‘M.9’ and ‘R.5’compared with 62 SSRs for ‘Discovery’× ‘TN10-8’(Calenge et al. 2004) and 20 SSRs for ‘Telamon’×‘Brae-burn’ (Kenis and Keulemans 2005). In addition, the‘M.9’×‘R.5’ map is one of the most functional mapsavailable, since it contains more than 50 SSR markers and12 SNPs derived from EST sequences.

The ‘M.9’×‘R.5’ genetic map has already permitted theidentification of a major gene conferring resistance towooly apple aphid (Er2) on ‘R.5’ LG17 (Bus et al. 2008)and the mapping of a major locus for dwarfing (Dw1) by‘M.9’ to LG05 (Rusholme Pilcher et al. 2008). The map hasalso enabled the mapping of a major QTL for resistance tofire blight on ‘R.5’ LG03 (Peil et al. 2008).

Duplication of SSR loci and confirmation of homoeologousregions in linkage groups

The mapping of a proportion of SSR markers to twodifferent linkage groups may indicate homoeologous pairsof chromosomes in the apple genome. Markers mapping toLG5 have already been found to amplify a second locus onLG10 (Maliepaard et al. 1998). This association of linkagegroups is confirmed by NH020a mapping on LG5 in pearand LG10 on ‘R.5’ (Table 7). The SSR marker CH03g12amplifies two loci mapping to the bottom of LG3 and to thetop of LG1 (Liebhard et al. 2002); the association between

Fig. 2 Map position of multi-locus SSR and RFLP markers revealduplication within the apple genome. Map positions are estimated forall the markers. The homoeologous chromosome segments areindicated by different filling patterns of bar segments. The format of

the lines linking the groups varies to allow for an easier reading of themap. Linkage groups are named and oriented according to Maliepaardet al. (1998)

Table 7 Pear SSRs mapping in different linkage groups in pear andapple

Apple map position(linkage group)

Pear map position(linkage group)

NB125a 9 17NB111a 15 11NH027a 6 15NH041a 5;10 7NH044b 16 13NH045a 11 10NH020a 10 5NH013a 17 1


LG3 and LG1 is also indicated by Hi07d08 that maps onLG1 of ‘Fiesta’ (Silfverberg-Dilworth et al. 2006) and LG3of ‘R.5’.

We combined this information on multilocus SSR andrestriction fragment length polymorphism (RFLP) markersto construct a map representing homoeologous parts of theapple genome (Fig. 2). This map is based entirely on non-functional markers and includes supposed homoeologousregions linked to each other by only one genetic marker(LG2 and LG8: CH01c06; LG1 and LG15: Hi21g05; LG9and LG12: NB104a). Thus, additional markers (non-functional as well as functional) will be necessary toconfirm the association between these suggested homoeol-ogous regions. Knowledge of the structure of the applegenome will bring a better understanding of its evolutionand assist in locating members of multigene families.

Comparative genome mapping between apple and pear

Out of the 117 pear SSRs tested, 49 were located on theapple genetic maps in this study, including 46 that had notbeen mapped in apple before. All the pear SSRs mapped inthis study were derived genomic SSRs. Mapping of thisrelatively large number of pear SSRs on an apple map is astep towards the detailed study of synteny between thesetwo species. Generally, our results agreed with those of areciprocal study (Yamamoto et al. 2004), as 86% of the pearmarkers were located in homologous linkage groupsbetween apple and pear. Some of the pear SSRs did notmap to corresponding linkage groups in apple (Table 7).These markers may reveal possible differences in theorganisation of the pear genome compared to apple.However, more markers need to be developed in theseregions to confirm this hypothesis.

The overall conservation of synteny between apple andpear genomes opens new possibilities for development ofmarkers for traits in common between apple and pear.

Development of a bin mapping set

We have developed the first bin mapping set for apple. Bydemonstrating that a set of 31 markers could be placed on the‘M.9’×‘R.5’ maps using 14 individuals instead of 93, weachieved our objective of minimising the effort involved inthe mapping of new markers by carefully selecting a fewinformative individuals. This represents an 85% reduction ofthe cost of genotyping and makes it possible to envisage theuse of alternative methods for genotyping. For instance, withsuch a small number of individuals, it is now possible to usedirect sequencing as a method for both marker developmentand genotyping. Bin mapping in the highly polymorphic‘M.9’×‘R.5’ population will facilitate access by the Rosa-ceae scientific community to this reference mapping popu-

lation, enabling the mapping of new markers or genesthrough the exchange of a limited number of DNA samples(14 individuals plus the two parents). New markers are nowscreened routinely over this bin set, contributing to acontinuous enrichment of our genetic map. The incorpora-tion of new markers can also potentially increase the numberof bins, resulting in an increase of the accuracy of mapping.The development of a bin mapping set for apple will beparticularly useful for candidate gene mapping, as functionalstudies based on microarray experiments or bioinformaticsanalysis often generate large numbers of candidate genes tobe tested for co-location with QTL intervals.

Acknowledgements The authors thank Toshiya Yamamoto forproviding Pyrus SSR primer sequences prior to deposition in thepublic database. This work was partially supported by the NewZealand Foundation for Research, Science and Technology, contractno. CO6X0205.

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Construction of a dense genetic linkage map for apple rootstocks using SSRs developed from Malus ESTs and Pyrus genomic sequences