Molecular Breeding

, Volume 22, Issue 4, pp 555–563

Identification, characterisation and mapping of simple sequence repeat (SSR) markers from raspberry root and bud ESTs

Authors

  • M. Woodhead
    • Scottish Crop Research Institute
  • S. McCallum
    • Scottish Crop Research Institute
  • K. Smith
    • Scottish Crop Research Institute
  • L. Cardle
    • Scottish Crop Research Institute
  • L. Mazzitelli
    • Scottish Crop Research Institute
    • Scottish Crop Research Institute
Article

DOI: 10.1007/s11032-008-9198-y

Cite this article as:
Woodhead, M., McCallum, S., Smith, K. et al. Mol Breeding (2008) 22: 555. doi:10.1007/s11032-008-9198-y

Abstract

Raspberry breeding is a long, slow process in this highly heterozygous out-breeder. Selections for complex traits like fruit quality are broad-based and few simple methodologies and resources are available for glasshouse and field screening for key pest and disease resistances. Additionally, the timescale for selection of favourable agronomic traits requires data from different seasons and environmental locations before any breeder selection can proceed to finished cultivar. Genetic linkage mapping offers the possibility of a more knowledge-based approach to breeding through linking favourable traits to markers and candidate genes on genetic linkage maps. To further increase the usefulness of existing maps, a set of 25 polymorphic SSRs derived from expressed sequences (EST-SSRs) have been developed in red raspberry (Rubus idaeus). Two different types of expressed sequences were targeted. One type was derived from a root cDNA library as a first step in assessing sequences which may be involved in root vigour and root rot disease resistance and the second type were ESTs from a gene discovery project examining bud dormancy release and seasonality. The SSRs detect between 2 and 4 alleles per locus and were assigned to linkage groups on the existing ‘Glen Moy’ × ‘Latham’ map following genotyping of 188 progeny and examined for association with previously mapped QTL. The loci were also tested on a diverse range of Rubus species to determine transferability and usefulness for germplasm diversity studies and the introgression of favourable alleles.

Keywords

Expressed sequence tagsRubus idaeusSimple sequence repeatsRaspberryEST-SSRsQTL

Abbreviations

AFLP

Amplified fragment length polymorphism

cDNA

Complementary DNA library

EST

Expressed sequence tag

RAPD

Randomly amplified polymorphic DNA

QTL

Quantitative trait locus

SSR

Simple sequence repeat

Introduction

Raspberries belong to the diverse genus Rubus, the commercially important raspberries being the European red raspberry, R. idaeus L. subsp. idaeus, the North American red raspberry R. idaeus subsp. strigosus Michx and the black raspberry (R. occidentalis L.). Raspberries are grown in many parts of the world and are an important high-value horticultural industry in many European countries providing employment directly in agriculture, and indirectly in food processing and confectionary. There is currently heightened interest focused on raspberry as major sources of antioxidants, such as anthocyanins, catechins, flavonols, flavones and ascorbic acid, compounds that may protect against a wide variety of human diseases, particularly cardiovascular disease and epithelial (but not hormone-related) cancers (Deighton et al. 2000; Moyer et al. 2002; Stewart et al. 2007). Raspberry breeding is a long slow process in this highly heterozygous out-breeder. Phenotypic selection has limitations especially when interest is focused on more complex physiological traits. In raspberry selection for traits such as fruit quality are very broad-based and few resources or methodologies exist for glasshouse and field screening for pest and disease resistance. Additionally, the timescale for selection of favourable agronomic traits such as root or plant vigour and the timing and duration of fruiting season, require data from different seasons and environments before any breeder selection can proceed. Progress in any breeding programme is based on the amount of genetic variability available and the effectiveness of the selection and evaluation of the trait in question. A more accurate way of assessing genetic variability and trait selection would be at the genetic level. Markers can be used to assess allele diversity across a range of germplasm, or markers can be examined for linkage to the trait or QTL underlying more complex traits. A prerequisite for genotypic selection is the establishment of associations between the traits of interest and genetic markers and requires markers and linkage maps to allow this to proceed effectively.

Several genetic linkage maps have been constructed in raspberry using RAPD, AFLP and SSR markers (Graham et al. 2004; 2006; Sargent et al. 2007; Pattison et al. 2007). However, dominant RAPD and AFLP markers are less transferable between genetic maps than highly polymorphic, co-dominant SSR markers. Furthermore, when SSRs are derived from expressed sequence tags rather than anonymous DNA, they become gene-specific, making them very useful for the construction and comparison of genetic maps and QTL analysis. EST-SSRs have been described for a number of cultivated Rosaceae species including strawberry (Bassil et al. 2006; Keniry et al. 2006; Lewers et al. 2005) and raspberry (Graham et al. 2006). Although some EST-SSRs may be transferable across the Rosaceae (Stafne et al. 2005), a large number of markers are required for crop improvement through marker assisted selection (MAS) and need to be identified from the species of interest. Often databases of ESTs derived from gene discovery projects can be mined for SSRs (Jung et al. 2005) but sometimes the construction and sequencing of specific cDNA libraries may be required.

This work aimed to identify EST-SSRs from two sources; a root cDNA library and a bud library as a starting point for mapping ESTs which may have effects on root and plant vigour, disease resistance and the timing of bud break leading to the manipulation of fruiting season. Association of ESTs with map locations of QTL for key traits in the raspberry breeding programme were determined.

Materials and methods

Plant material and DNA isolation

DNA was extracted from young raspberry leaves from two cultivars, ‘Glen Moy’ (R. idaeus) and ‘Latham’ (R. strigosus) and 188 progeny derived from a cross between these two parents using a CTAB/chloroform method as described in Graham et al. (2004). DNA samples were also prepared from leaves from a further eight Rubus accessions in order to assess the cross-transferability of the loci developed across a wide range of germplasm. Material was chosen across the main raspberry and blackberry species, a hybrid berry used in breeding and an ornamental species of no pomological value as shown in Table 1.
Table 1

Rubus species used for primer transferability

Accession name

Species

Common name

Subgenera

‘Glen Moy’

R. idaeus

European red raspberry

Idaeobatus

‘Latham’

R. strigosus

North American red raspberry

Idaeobatus

R. macraei

R. macraei

Tropical raspberry

Idaeobatus

R. coreanus

R. coreanus

Raspberry

Idaeobatus

R. leucodermis

R. leucodermis

Black raspberry

Idaeobatus

‘Tayberry’

R. idaeus × R. fructicosus

Hybridberry

Rubus × Ideobatus hybrid

R. fructicosus

R. fructicosus

Blackberry

Rubus

R. grabowski

R. grabowski

Blackberry

Rubus

R. mesogaeus

R. mesogaeus

Himalayan black raspberry

Rubus

R. geoides

R. geoides

Ornamental

Comaropsis

SSR identification

Root cDNA library construction

For RNA extraction, ‘Latham’ (R. strigosus) raspberry plants were grown in pots containing a high sand to soil ratio with liquid feed for 4 weeks. Plants were carefully harvested to prevent root damage, washed in sterile H2O to remove all sand/soil and the roots harvested and immediately frozen in liquid nitrogen. Total RNA was extracted and used to construct a cDNA library in the pSport 1 vector (Invitrogen Corporation, Carlsbad, CA) following the method detailed by Woodhead et al. (2003). Single transformed colonies were identified, picked into 19 × 384-well plates and used for plasmid preparation and sequencing. Sequencing (10 μl reactions) was performed using the BigDye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA), with M13 forward and reverse primers (5′-GTAAAACGACGGCCAG and 5′ CAGGAAACAGCTATGAC respectively) using 25 sequencing cycles of 96°C for 10 s, 50°C for 5 s and 60°C for 4 min on a GeneAmp 9700 PCR System thermocycler (Applied Biosystems). Sequences were analysed using a 3730 DNA Analyzer (Applied Biosystems). DNA sequences were quality scored using the Phred software (http://www.phrap.com) and then searched against the non-redundant nucleotide databases at NCBI (http://www.ncbi.nlm.nih.gov) using the BLAST algorithm (Altschul et al. 1990). SSRs were identified using Sputnik as described by Woodhead et al. (2003).

EST-SSR mining from the meristematic bud library

In raspberry, 380 ESTs from meristematic bud tissue (cv. Glen Ample (R. idaeus)) that are differentially expressed during dormancy phase transition (Mazzitelli et al. 2007) were sequenced using the universal M13 forward and reverse primers and the BigDye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems) as described above. Sequences were analysed on a 3730 DNA Analyzer (Applied Biosystems) and sequence data were analysed and mined for SSRs as described above.

SSR primer design and testing

Primers were designed to SSRs using Primer3 (Rozen and Skaletsky 1998) and were tested on ‘Latham’, ‘Glen Moy’ and ten selected progeny. Each 20 μl PCR reaction contained 20 ng DNA, 0.5 μM each primer, 200 μM dNTPs, 1 × Taq buffer and 0.5 U Taq polymerse (Roche). Amplicon conditions were: 5 min at 95°C; 35 cycles of 60 s at 94°C, 60 s at 55°C, and 60 s at 72°C, followed by 8 min at 72°C on a GeneAmp 9700 PCR System (Applied Biosystems) thermocycler. Products were analysed on 2% (w/v) agarose to assess polymorphism. ESTs from the meristematic bud dormancy cDNA libraries (Mazzitelli et al. 2007) were similarly screened for polymorphic SSRs, using a touchdown PCR performed on a GeneAmp 9700 PCR System (Applied Biosystems) as follows: 5 min at 94°C; 7 cycles of 30 s at 94°C, 30 s at 65°C, and 30 s at 72°C decreasing to 58°C at 1°C per cycle, followed by 25 cycles of 30 s at 94°C, 30 s at 58°C and 30 s at 72°C, followed by 7 min at 72°C (Woodhead et al. 2003).

Genetic mapping

For polymorphic loci, one primer was fluorescently end-labelled with FAM or HEX and used to genotype 188 individuals of the ‘Glen Moy’ × ‘Latham’ mapping population (Graham et al. 2004) using a 3730 DNA Analyzer (Applied Biosystems) with ROX350 (Applied Biosystems) used as an internal size standard. Allele sizes were determined using GENEMAPPER (Applied Biosystems). JoinMap V 2.0 (Stam and Van Ooijen 1995) was used to construct the linkage map for population type CP (Cross pollinator). Linkage groups were separated at a LOD score of 7.0 and map distances were calculated using the Kosambi mapping function as described previously (Graham et al. 2004, 2006).

Results and discussion

SSR identification

EST-SSR markers are currently poorly represented on the raspberry genetic linkage maps (Graham et al. 2004, 2006; Sargent et al. 2007; Pattison et al. 2007). To date only 8 EST-SSRs have been mapped in raspberry (Graham et al. 2006). However, a number of QTLs for major traits including disease resistance and fruit quality in raspberry have been mapped across seasons and environments (Graham et al. 2006; Rusu et al. 2006, Tierney and McCallum, data not shown, Zait and Mozzim, personal communication) and candidate gene sequences and ESTs that are associated with the QTLs are being sought.

A total of 4608 ‘Latham’ root cDNA clones were sequenced giving 1438 singletons and 503 contiguous sequences; 335 SSRs (≥12 bp) were identified from these 1941 sequences. Primers were designed to 50 randomly selected SSRs, 21 loci were polymorphic and could be mapped in this population.

Analysis of the 380 dormancy phase transition-related ESTs gave 30 sequences containing SSRs ≥12 bp. From these 30 sequences five were suitable for primer design and four of these SSRs were polymorphic and could be mapped in this population.

Summary details of the 25 Rubus EST-SSR markers are given in Table 2. Homologies for 21 of the ESTs were found in the sequence databases; four show no homology to other sequences. Of the 21 that share homology to sequences in the databases, 14 (66%) showed greatest similarity to other Rosaceae sequences and the best matches are indicated (Table 2). Of the 17 root-derived ESTs (designated ERubLR) only one sequence shows homology to a root-related EST (ERubLR_SQ05_3_E02). The majority of the remaining sequences were similar to fruit-derived (7) and petal-derived (3) ESTs and others were similar to ESTs or protein sequences from pollen, leaf, seed or vegetative material or were unknown (Table 2). This suggests that most of the genes identified here may have general roles in plant growth and development, rather than being only related to root function. The four meristematic bud ESTs also showed homology to sequences from different tissues including petals, fruit and leaves (Table 2).
Table 2

Characteristics of the EST-SSRs identified in Rubus idaeus

Locus and Genbank accession number

Repeat motif

Forward (F) and reverse (R) primer sequences (5′–3′)

Allele sizes (bp) in ‘Latham’ × ‘Glen Moy’

Putative location of SSR

Homology, accession number and identity

E-value

Linkage group

ERubLR_SQ07_3_C07

EX567279

(ACC)4

F

R

ATGGCTTGTAGGTTTCACTC

CATTTGCTCAAACGATTATG

242,248 × 242

Possibly CDS

Unknown Oryza sativa protein (NP001059068.1) 20/28 (71%)

7e-05

1

RubPara_SQ008_D04

EX567296

(AT)9

F

R

TTGAGAACCATGCCTACATATCTT

GCTGGAAATGGATTGAATGG

242,249 × 242

3′-UTR

Malus × domestica leaf cDNA (DR994811) 347/413 (84%)

6e-77

1

ERubLR_SQ07_4_E09

EX567281

(CTAG)4

F

R

CACTAGGTCGATCAAGAAGC

CTGCCATAGAAACAAACGAC

170,180 × 170

3′-UTR

Glycine max seed coat cationic peroxidase 2 (AAC83463.1) 48/56 (85%)

6e-21

2

ERubLR_SQ01_F09

EX567285

(GCA)5–(CAAAA)2

F

R

GGCATACCCAAGACGTTCTC

GTCTTTGGTGGTGCTTGAGG

208,214 × 208

CDS/3′-UTR

Prunus armeniaca fruit EST (CV050893.1) 105/117 (89%)

2e-29

2

RubPara_SQ007_O09

EX567295

(CATA)4 (CTAG)3

F

R

CATGGAAAACCATGCATCATA

GCTTTGTCCAAAAGTGCTGT

296,305 × 296

5′-UTR

Fragaria × ananassa whole plant secretory peroxidase-like cDNA (CO817499) 294/332 (88%)

4e-90

2

ERubLR_SQ07_4_D05

EX567280

(AGC)7

F

R

CTTCTTTCCAACCGATTTC

ACGAATTGATTTCATCAACC

233,244 × 233,236

Unknown

No hits

 

3

ERubLR_SQ07_1_E10

EX567277

(GAA)6

F

R

GAGGAGAAGATTGTGAATCG

ACACACCTCCCAGACATAAC

240,248 × 242,248

CDS

Rosa hybrid cv. petal EST (CF349335.1) 320/365 (87%)

1e-126

3

ERubLR_SQ01_P18

EX567291

(TG)7–(TAGC)3

F

R

CCACTTTATTTGATTTATTCCATCC

ACGGACAAAAGTGGGTATGC

198,202 × 202

CDS

CDS

Prunus armeniaca fruit EST (CB823353) 41/44 (93%)

1e-07

3

ERubLR_SQ01_B06

EX567284

(AGCG)4

F

R

CCTCTACACCACCCCATCAG

CGTCATCGTCATCTCTCTCG

190,198 × 198

CDS

Rosa chinensis petal EST (BI977827.1) 177/207 (85%)

7e-41

4

ERubLR_SQ19_3_G09

EX567283

(GCTC)4

F

R

GTTCGTCATCGTCATCTCTC

AGAAAACCAAACCCCTCTAC

205,215 × 215

Unknown

Rosa chinensis petal EST (BI977263) 395/498 (80%)

1e-119

4

ERubLR_SQ07_2_H02

EX567278

(CTAG)4

F

R

TGGCAATCAACCACTCTGTG

CAAACTGACAAACGCTCTTCC

234 × 234,236

3′-UTR

Vitis berry isoflavone reductase-like protein (CAI56335) 45/49 (91%)

1e-19

4

RubEndo_SQ004_N23

EX567294

(TA)14

F

R

CACTGCAAGGTGTCGTTTGT

ATAGCTCCGGCAATCCATC

217,233 × 238

3′-UTR

Rosa chinensis petal GAST-like cDNA (BI978016) 179/202 (88%)

3e-54

4

ERubLR_SQ19_1_A05

EX567282

(GAA)11

F

R

GTTTGCTTCCTTTCGTAGTC

TATACTAATGGCCACCTTGG

204,215 × 207,210

Unknown

Unknown V. vinifera protein (CAO63589.1) 44/106 (41%)

3e-12

5

ERubLR_SQ06_2_E01

EX567276

(AT)6

F

R

GCAGGAGTTGGACGAGTAG

TTTCCAGATCAAACAAGACC

194,198 × 194

3′-UTR

Vitis pollen specific protein (ABC86745.1) 61/100 (100%)

2e-10

5

ERubLR_SQ05_3_E02

EX567273

(GGT)4

F

R

GTCACACAAGGCTACCAAG

ATTGAACTGGTCAACAATGC

205,207 × 205,207

Unknown

No hits

 

5

ERubLR_SQ01_I20

EX567288

(TA)9

F

R

TCTTTTGCGGTGGCTACAAG

CAACCCGAAGTCTACAACAGC

217,221 × 221

CDS

Poncirus trifoliata root EST (CX640069) 81/95 (85%)

1e-10

5

RubPara_SQ005_K23

EX567297

(AG)6

F

R

AGGTGAGGTGGGAGATGATG

ATCCTCGGTTCCTCCAAAAT

202,203 × 202

Unknown

Fragaria × ananassa red fruit cDNA (CO380688) 56/60 (93%)

5e-12

5

ERubLR_SQ01_M20

EX567289

(ATA)5

F

R

TTACGAACACCCATTAATTTAAGTC

AATCCTGAGACCGACGAGTG

234,242 × 234,242

CDS

Malus × domestica fruit EST (CV084067) 145/167 (86%)

9e-34

5

ERubLR_SQ02_B19

EX567293

(GC)7

F

R

CTCCGCAGACATTCCTTCTC

GCTTCAGGAAGCTCGATCAC

218,220 × 218

Unknown

Fragaria vesca seedling EST (DY674776) 56/62 (88%)

4e-11

7

ERubLR_SQ01_G16

EX567286

(TC)8

F

R

GCACCCTAATCTCCATGACC

CCGCTGTAGTTCCTGTAGGC

198,200 × 200

Unknown

No hits

 

7

ERubLR_SQ05_3_H01

EX567274

(TA)5

F

R

CTATTGCAAGGATACCAAGC

GTTGCAACATGACAATTCC

182,187 × 187

3′-UTR

Malus × domestica fruit xyloglucan endotransglycosylase––(AAN07898.1) 47/75 (62%)

6e-21

7

ERubLR_SQ01_I08

EX567287

(GC)7

F

R

GCTTCAGGAAGCTCGATCAC

TCACCTAAGCACCTAATTAAGGAAG

198,200 × 198

Unknown

No hits

 

7

ERubLR_SQ01_N03

EX567290

(AT)5

F

R

GATTCAAATCCAGTAGACCAGTACC

CATTGAGACCCACCTCTTGG

230,232 × 230

3′-UTR

Malus × domestica fruit Mal d 1-like gene (AAS00047) 82/114 (71%)

2e-42

7

ERubLR_SQ02_B23

EX567292

(AG)5

F

R

CGTACTGGGTTTTCTTCCTTG

GCTACTCCAGCAGCAAGCAG

217 × 267

Unknown

Medicago truncatula DNA (CU424435) 31/37 (83%)

1.6

NM

ERubLR_SQ05_4_E09

EX567275

(GGA)6–(GGC)5

F

R

TCAGCTCCCAACCTATTTAC

CTCCTCGCCTCTATCGTTAC

162 × 159

CDS

Prunus persica fruit EST (DY650612) 308/345 (89%)

1e-105

NM

NM: not mapped, parents both homozygous

The SSRs amplified reliably, gave clear electropherogram profiles that were easily scored and detected between 2 and 4 alleles in this mapping population. The putative locations of the SSRs within the sequences was determined, with the majority (10/25) unknown, 8/25 present in the 3′-untranslated regions, 6/25 in the coding sequence and only one in the 5′-untranslated region (Table 2). As more database sequences become available it may be possible to identify the unknowns more easily.

Genetic mapping

Of the 25 ESTs, two loci were homozygous for each parent and could not be mapped in this population but the remaining 23 markers were mapped to their respective linkage groups (Table 2) using Joinmap. The markers span six of the seven Rubus linkage groups (Fig. 1) but no root-related EST-SSRs were placed in Linkage Group 6, known to be one of two linkage groups associated with root growth and morphology (data not shown). Associations of these new EST-SSR markers with QTL for phenotypic traits of interest (Ahmad 2004; Graham et al. 2006; Graham and Jennings 2008; Rusu et al. 2006; Tierney, personal communication; Zait, personal communication; Mozzim, personal communication) were examined. Fourteen of the new EST-SSR markers have been assigned to linkage groups and linked to markers previously associated with QTL for developmental traits such as bud break, fruit development as well as fruit quality traits and disease resistance characteristics (Fig. 1).
https://static-content.springer.com/image/art%3A10.1007%2Fs11032-008-9198-y/MediaObjects/11032_2008_9198_Fig1_HTML.gif
Fig. 1

‘Latham’ × ‘Glen Moy’ linkage map with position of EST-SSRs and the QTL associated with them

Cross transferability

The EST-SSRs were transferable to some extent in 10 diverse Rubus species with five EST-SSRs amplifying only in R. idaeus and R. strigosus (Table 3). In two of these five loci the SSR was located in the 3′-untranslated region yet six other EST-SSR loci also contained repeat motifs in this region (Table 2) and cross-amplification was between 80 and 100% successful across the species tested (Table 3). The level of transferability of these markers may prove useful for future genetic diversity and population genetics studies in raspberry and related species, as well as in future raspberry breeding programmes.
Table 3

Transferability of the 25 EST-SSR loci in 10 Rubus species

Locus

Eubatus × Ideobatus hybrid

R. fructicosus

R. geoides

R. grabowski

R. idaeus

R. lacustre

R. macraei

R. mesogaeus

R. coreanus

R. strigosus

ERubLR_SQ07_3_C07

236/242

236/242/248

242

234/242

242

242

234/242

228

242,248

RubPara_SQ008_D04

237/242/249

240/242

242/249

242

242

237

237

237

237

242/249

ERubLR_SQ05_4_E09

159/162

162/166

159

162/166

159

162/166

159

166/168

162

162

ERubLR_SQ01_F09

210

213/216/222

208/214

222/225

208

200/208

210

208

208/214

RubPara_SQ007_O09

305

305

305

305

296

300

305

305

296/305

ERubLR_SQ07_4_D05

233/236

229/236

233/236

236

233/236

236/240

233/244

233/242

233/244

ERubLR_SQ07_1_E10

250

246/248

250

242/248

246/252

248/250

230/238

240/248

ERubLR_SQ01_P18

198

198

202

202

202

198

202

198

198/202

ERubLR_SQ01_B06

188/194/198

188/196

188/198

188/194/198

198

188/198

188/198

196/198

190/198

ERubLR_SQ19_3_G09

211/215/219

201/205/215

203/215

205/213

215

205/215

215

203/215

205/215

ERubLR_SQ07_2_H02

230/237

233/237

230/237

234/237

234/236

228/237

227/234

227

234

RubEndo_SQ004_N23

245

203/213

251/257

245

238

238

238

238

217/233

ERubLR_SQ19_1_A05

198/210

202/204/210

207/210

202/204

207/210

204

204

210/215

213

204/215

ERubLR_SQ06_2_E01

214

211/214

211/214

214

194

214

214

211/214

214

194/198

ERubLR_SQ05_3_E02

205/207

205/207

ERubLR_SQ01_I20

217/219

221

217/221

221

221

217

217/219

221

217/221

RubPara_SQ005_K23

221

221/226

200

221/226

202

212

202

212

202/203

ERubLR_SQ01_M20

234

242

234

234

234/242

234

234

234/242

ERubLR_SQ02_B19

218

218/220

ERubLR_SQ01_G16

198

191/198

204/212/219

200

198/204

198/206

198/200

ERubLR_SQ05_3_H01

187

182/187

ERubLR_SQ01_I08

196

196

198

196

198

196

204

198/200

ERubLR_SQ01_N03

230

230/232

ERubLR_SQ02__B23

267

217

ERubLR_SQ07_4_E09

160/162

162/166/168/170

160

166/168

170

162/166

160

166/168

170/180

Allele size; –, no amplification

The enrichment of genetic maps with EST-SSR loci that are associated with potentially functional genes may help to associate candidate genes with mapped traits and allow greater comparisons between genetic maps. As the Rubus QTL become more closely associated with functional sequences on maps it will be possible to utilise these and other candidate gene markers being developed to identify corresponding BACs and link the genetic and physical maps for Rubus. Additionally, the use of transferable EST-SSR loci may help identify alleles in novel germplasm for traits of interest for incorporation into breeding programmes.

Acknowledgements

This work was funded by RERAD, DEFRA and HDC through Horticulture Link. We thank C. Booth and M. Macauley for sequencing and genotyping assistance.

Copyright information

© Springer Science+Business Media B.V. 2008