Molecular Breeding

, Volume 25, Issue 1, pp 25–45

Extension of the core map of common bean with EST-SSR, RGA, AFLP, and putative functional markers

Authors

  • Luiz Ricardo Hanai
    • Escola Superior de Agricultura “Luiz de Queiroz”Universidade de São Paulo
  • Luciane Santini
    • Escola Superior de Agricultura “Luiz de Queiroz”Universidade de São Paulo
  • Luis Eduardo Aranha Camargo
    • Escola Superior de Agricultura “Luiz de Queiroz”Universidade de São Paulo
  • Maria Helena Pelegrinelli Fungaro
    • Centro de Ciências BiológicasUniversidade Estadual de Londrina
  • Paul Gepts
    • Department of Plant SciencesUniversity of California
  • Siu Mui Tsai
    • Centro de Energia Nuclear na AgriculturaUniversidade de São Paulo
    • Escola Superior de Agricultura “Luiz de Queiroz”Universidade de São Paulo
Open AccessArticle

DOI: 10.1007/s11032-009-9306-7

Cite this article as:
Hanai, L.R., Santini, L., Camargo, L.E.A. et al. Mol Breeding (2010) 25: 25. doi:10.1007/s11032-009-9306-7

Abstract

Microsatellites and gene-derived markers are still underrepresented in the core molecular linkage map of common bean compared to other types of markers. In order to increase the density of the core map, a set of new markers were developed and mapped onto the RIL population derived from the ‘BAT93’ × ‘Jalo EEP558’ cross. The EST-SSR markers were first characterized using a set of 24 bean inbred lines. On average, the polymorphism information content was 0.40 and the mean number of alleles per locus was 2.7. In addition, AFLP and RGA markers based on the NBS-profiling method were developed and a subset of the mapped RGA was sequenced. With the integration of 282 new markers into the common bean core map, we were able to place markers with putative known function in some existing gaps including regions with QTL for resistance to anthracnose and rust. The distribution of the markers over 11 linkage groups is discussed and a newer version of the common bean core linkage map is proposed.

Keywords

Phaseolus vulgarisCore linkage mapEST-SSRAFLPNBS-profiling methodResistance gene analogs

Introduction

Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption in the developing world (Broughton et al. 2003). Production is especially important in Eastern and Southern Africa and Latin America where, in particular, rice and beans are an inseparable pair of staple foods for millions of people, representing a major source of dietary protein. Therefore, an increased effort has been devoted to improving bean varieties and expanding the area under bean cultivation. However, the productivity of most bean varieties grown in developing countries is still low.

Molecular markers have been used to assist common bean breeding programs in various ways (Jarne and Lagoda 1996), including studies on the origin and diversity of current cultivars (Gepts 1998), the domestication of P. vulgaris (Koinange et al. 1996), and the genetic control of resistance to important diseases (Miklas et al. 2003; Miklas et al. 2006a; Nodari et al. 1993b; Yu et al. 1998). The first molecular linkage maps of common bean were developed by means of restriction fragment length polymorphism (RFLP) markers (Adam-Blondon et al. 1994; Nodari et al. 1993a; Vallejos et al. 1992). Subsequently, common markers were used to integrate these maps by establishing the correspondence of their linkage groups (Freyre et al. 1998). For instance, a population of RILs derived from a cross between ‘BAT93’ and ‘Jalo EEP558’ was used as a core mapping population to construct an integrated linkage map. Although RFLP markers have been important to establish a genome-wide framework for anchoring and cross-referencing plant linkage maps, their widespread use in common bean was restricted by the lack of probes and the low-throughput nature of RFLP markers. Different types of markers, mainly random amplified polymorphic DNA (RAPD) were then used to increase the density of the common bean molecular linkage map (Freyre et al. 1998). More recently, single sequence repeats (SSR), also called microsatellites, have been developed and used to increase the density of existing maps, especially the core ‘BAT93’ × ‘Jalo EEP558’ linkage map (Blair et al. 2003; Grisi et al. 2007; Yu et al. 2000).

Currently, high-throughput markers, such as AFLP, are preferred for map saturation purposes. Putative functional markers are still underrepresented in the common bean molecular linkage map compared to other types of markers (López et al. 2003; Miklas et al. 2006b; Mutlu et al. 2006; Rivkin et al. 1999). Among these are resistance gene analogs (RGA), which are associated with a number of known R-genes (Brugmans et al. 2008; Ferrier-Cana et al. 2003; Kanazin et al. 1996; Mutlu et al. 2006) and quantitative resistance loci (Flandez-Galvez et al. 2003; Mutlu et al. 2006; Timmerman-Vaughan et al. 2002). In addition, microsatellites represent a limited proportion of the markers on the bean core map (Blair et al. 2003; Grisi et al. 2007; Yu et al. 2000), in spite of their many desirable attributes, including their presence in both non-genic and genic regions of plant genomes (reviewed by Li et al. 2004; Oliveira et al. 2006). A large number of unmapped microsatellite markers have been reported in the literature (Benchimol et al. 2007; Buso et al. 2006; Caixeta et al. 2005; Campos et al. 2007; Cardoso et al. 2008; Gaitán-Solís et al. 2002; Guerra-Sanz 2004; Hanai et al. 2007; Métais et al. 2002; Murray et al. 2002; Yaish and Pérez de la Vega 2003). In addition, the density of the common bean core map is still low for purposes of marker-assisted selection and map-based cloning.

The objectives of the present work were to test new SSR markers developed from common bean expressed sequence tags (EST) in a set of P. vulgaris genotypes, assess their capacity to render SSR polymorphisms and to map them and other markers such as RGA and AFLP onto the common bean core map.

Materials and methods

Plant material and DNA extraction

A set of 23 common bean inbred lines and one accession of P. acutifolius were used to evaluate allelic variation at EST-SSR loci. Among P. vulgaris accessions, 17 genotypes belonged to the Mesoamerican gene pool (‘Apetito Blanco’, ‘Baetão’, ‘Barbunya’, ‘BAT93’, ‘Brasil2’, ‘Carioca Comum’, ‘Flor de Mayo’, ‘Garbancillo’, ‘Great Northern’, ‘IAC-UNA’, ‘Jamapa’, ‘Mulatinho’, ‘Porrillo’, ‘Puebla152’, ‘Rio Tibagi’, ‘Sanilac’ and ‘Tu’), and six to the Andean gene pool (‘Antioquia 8’, ‘CAL 143’, ‘Jabola’, ‘Jalo EEP558’, ‘Pompadour’ and ‘Red Kidney’). For map construction the inter-gene pool ‘BAT93’ × ‘Jalo EEP558” population (Freyre et al. 1998; Nodari et al. 1993a) consisting of 74 F8 RILs was used.

Total genomic DNA was extracted from young leaf tissue using the CTAB extraction method as described by Doyle and Doyle (1987). DNA concentrations were estimated by electrophoresis on ethidium bromide-stained agarose gels using appropriate molecular weight standards. From this quantification, aliquots at 10 and 50 ng/μl were prepared for EST-SSR amplifications and enzymatic digestions, respectively.

Development and amplification of EST-SSR markers

As reported previously (Hanai et al. 2007), a total of 3,126 bean EST sequences were obtained from the bean EST project homepage (http://lgm.esalq.usp.br/BEST/). EST-containing SSR exhibiting at least five repeat units of di-, tri-, and tetranucleotide motifs were analyzed and 156 primer pairs were designed. PCR reactions were performed in a final volume of 16 μl in 96-well plates using a Gen Amp® PCR System 9700 thermocycler (Applied Biosystems). Approximately 20 ng of template DNA were mixed in a solution containing 0.2 μM of both forward and reverse primers, 0.2 mM of each dNTP, 1.5 mM MgCl2, 10 mM Tris–HCl (pH 8.3), 50 mM KCl and 0.4 units Taq DNA polymerase (Promega). Four PCR program profiles were used to amplify EST-SSR loci. All four profiles started with a preliminary denaturation step at 94°C for 2 min followed by two stages. In both stages, denaturing and elongation conditions were held constant at 94°C for 30 s and 72°C for 60 s, respectively. The duration of primer annealing was 45 s, but the temperature varied in stage 1, decreasing 1°C per cycle during 12 cycles (65–53°C), 0.5°C per cycle during 10 cycles (55–50°C) or 1°C per cycle during 10 cycles (55–45°C) in programs 1, 2 and 3, respectively. In program 4, the initial annealing temperature was 45°C and increased 1°C per cycle during 10 cycles (45–55°C). Stage 2 comprised 25 cycles of amplification. In all programs, the annealing temperature of stage 2 was the one reached at the end of the first PCR stage. Final elongation was performed at 72°C for 7 min.

Development and sequencing of RGA markers

RGA markers were amplified based on the NBS-profiling methodology (van der Linden et al. 2004). This methodology is based on the digestion of DNA, ligation with adapters, and a PCR reaction where one primer targets the adapter while the other, which is degenerate, targets the conserved nucleotide binding site (NBS) domain of plant disease resistance genes. This amplification results in several fragments per reaction due to the abundance of resistance gene-like sequences in plant genomes.

About 200 ng of genomic DNA from the parental line ‘BAT93’ and ‘Jalo EEP558’ were digested with RsaI (New England BioLabs). Digestions were performed in a final volume of 20 μl using 6 U of the enzyme according to the manufacturer’s recommendations, during 4 h at 37°C. Reactions were terminated by heat inactivation (20 min at 65°C). An adapter previously prepared from an equimolar mixture of LA (long arm) oligonucleotide (5′-ACTCGATTCTCAACCCGAAAGTATAGATCCCA-3′) and SA (short arm) oligonucleotide (5′-TGGGATCTATACTT*-3′) was ligated to the restriction fragment ends. The 3′ end of the SA oligonucleotide was blocked for Taq DNA polymerase extension by the addition of an amino group (*). Ligation was performed by adding 20 μl of a mixture containing 1.25 μM adapter, 1× ligation buffer (New England BioLabs), 80 units T4 DNA ligase (400 units/μl; New England BioLabs) to 20 μl of digested DNA. The reaction was incubated at 16°C overnight and terminated by heat inactivation (65°C for 10 min). As template DNA 3 μl of ligation products were used for the amplification of selected fragments anchored to the NBS-domain. For this, an AP (adapter primer) complementary to the adaptor (5′-ACTCGATTCTCAACCCGAAAG-3′) and one of four NBS-primer were used in distinct reactions (Table 1). The amplification was performed in a final volume of 20 μl containing 0.25 μM of both primers, 0.2 mM of each dNTP, 1.5 mM MgCl2, 10 mM Tris–HCl (pH 8.3), 50 mM KCl and 1.0 unit Taq DNA polymerase (Promega). The amplification was carried out in a Gen Amp® PCR System 9700 thermocycler (Applied Biosystems). A two-stage PCR was used after an initial denaturing step at 94°C for 5 min. The first stage consisted of 8 cycles at 94°C for 45 s, at 58°C (−1°C per cycle) for 1 min, and at 72°C for 1 min, whereas the second stage consisted of 25 cycles at 94°C for 45 s, 50°C for 1 min and 72°C for 1 min. A final extension of 7 min at 72°C was conducted. The amplification of fragments anchored to NBS-domain was assured by designing an adapter that does not have an AP-primer annealing site in the SA oligonucleotide. This annealing site is constructed after elongation of the NBS-primer, when the end of LA oligonucleotide is used as template for AP-primer annealing (for details see van der Linden et al. 2004).
Table 1

Designation and sequence of primers used to generate RGA markers based on the NBS-profiling method

Primer designationa

Sequence 5′–3′

Protein domain/motif

AP

ACTCGATTCTCAACCCGAAAG

Adapterb

NBSa-F

GGAATGGGKGGACTYGGYAARAC

NBS/kinase

Kdc-F

ATGGGAAGGAAGTATTCCAA

NBS/kinase

Kdc-R

ARGTTCCACAGGACATCACC

NBS/kinase

RGP-F

GGNATGGGYGGBRTHGGYAARAC

NBS/hydrophobic

aF for forward and R for reverse

bPrimer specific to the adapter sequence used in combination with RGA specific primers

RGA markers of interest were excised from polyacrylamide gels and reamplified following the same PCR conditions initially used. Fragments were resolved on agarose gels, purified (PCR purification kit, Qiagen), and cloned into pGEM®-T Easy vector (Promega) for sequencing. Inserts were sequenced in the forward and reverse directions. The sequencing reaction was performed as described by Sanger et al. (1977) using DYEnamic™ ET dye Terminator Cycle Sequencing Kit (Amersham Pharmacia Biotech, Inc.) on MegaBACE 1000 (Amersham Biosciences). Sequences were assembled using the Phred/Phrap/Consed package using a phred score ≥20 as the threshold for base quality. Nucleotide sequences were compared to sequences deposited in the Genbank database (http://ncbi.nlm.nih.gov/BLAST) using the BLAST tool (Altschul et al. 1990).

Generation of AFLP markers

AFLP markers were amplified based on the protocol described by Vos et al. (1995) with modifications. Restriction and ligation enzymes required for AFLP analysis were obtained from the New England Biolabs Company. Briefly, 200 ng of genomic DNA from each of the parents and the 74 F8 RILs were double digested with EcoRI and MseI or PstI and MseI enzymes (5 U of each) in a 25 μl reaction mixture (10 mM Tris–acetate, pH 7.5; 10 mM Mg-acetate, 50 mM K-acetate) during 4 h at 37°C. All resulting fragments were ligated to adapter sequences by adding an equal volume of a ligation solution i.e. 30 mM of Tris–HCl (pH 7.5), 10 mM of MgCl2, 10 mM of DTT, 1.0 mM of ATP, 0.25 μM of EcoRI or PstI adapter, 2.5 μM of MseI adapter, and 80 units of T4 DNA ligase (400 units/μl). These reactions were incubated at 16°C overnight and terminated by heat inactivation (65°C for 10 min). The adapter-ligated DNA (3 μl) was used for the pre-selective amplification using AFLP primers based on the sequence of the EcoRI or PstI and MseI adapters, with one selective nucleotide at the 3′ end. The pre-selective reaction was amplified using the following conditions: 94°C for 2 min; 26 cycles of 94°C for 60 s, 56°C for 60 s, 72°C for 60 s; and a final elongation at 72°C for 5 min. Five microliters of a 10-fold diluted pre-selected PCR product were used as DNA template for the selective amplification using AFLP primers with three additional selective nucleotides at the 3′ end. The following cycling parameters were used for selective amplification: 94°C for 2 min; 12 cycles of 94°C for 30 s, 65°C for 30 s, 72°C for 60 s; 23 cycles of 94°C for 30 s, 65°C for 30 s, 72°C for 60 s; and a final elongation at 72°C for 5 min.

Genotyping

All markers were resolved in 6% w/v denaturing polyacrylamide gels (19:1; acrylamide:bis-acrylamide) using the electrophoresis apparatus Sequi-Gen® GT (Bio-Rad). Samples (3 μl) of amplified products were denatured with 1× loading buffer (0.2% each bromophenol blue and xylene cyanol, 10 mM EDTA, pH 8.0, and 95% formamide) at 95°C for 5 min before they were loaded onto the gels. The EST-SSR markers were electrophoresed for 2 h 30 min at 70 W, and AFLP and RGA markers for 4 h 30 min at 80 W. The loci were visualized by silver staining according to Creste et al. (2001). AFLP loci were coded using the name of the primer pair followed by the fragment size (bp). RGA loci were coded using the initials of the enzyme and NBS primer names followed by the fragment size (bp). The codes for EST-SSR markers are shown in Table 2.
Table 2

PvM (Phaseolus vulgaris Microsatellites) loci derived from bean expressed sequence tags (EST)

Marker code (Bean unigene)

Repeats motifa

Sequence of forward and reverse primers (5′–3′)

Predicted/observed allele (bp)b

PCR programc

Na/PICd

Linkage group

Amplification in Phaseolus acutifolius

PvM010 (PVEPSE3030I07)

ACT5

GAAGGGCAATGGCTGAAG

TCCCGTGGAAACACTTGG

256/256

1

Nd

1

 

PvM023 (PVEPSE2004G02)

AG5

CCTGTTCCCTCTGTGTGAGA

AATCAACCCCATCAAACCAA

219/700

2

Mono

 

N

PvM031 (PVEPSE3030F06)

ATC5

GAGAAGCCAGGAACTTA

GCATCCCTTTTGTGTC

159/159

3

Nd

  

PvM043 (PVEPSE2026A06)

AG10

CGAGCAAAGACATCGGTTT

CATTGTAAGCCAGGGAAGG

112/112

4

Mono

 

N

PvM047 (PVEPSE2022E03)

CA5

AGCACTATGATTTTTGAAT

CCTGGGTTGAAGGAAT

205/700

3

Nd

  

PvM050 (PVEPSE2025C02)

TC5

GCGTGGGGTCTTTTCTCTCT

AACGCATGGAAGTGCAAGTT

206/206

4

Mono

 

N

PvM051 (PVEPSE2019C07)

CA5

CCAACCACCCTTCTTCTCTCT

ATCCGTGCCAACCATCTTT

199/199

4

2/0.22

 

Y

PvM052 (PVEPSE2018H03)

CA7

TCCTCTGCAAACAAAACCCTA

TTCGCCAAATTCGACAATCT

204/500

4

3/0.62

5

Y

PvM053 (PVEPSE2016A02)

TC6

TGGGGGAATTGAGTGAACAT

TCTTTCTTGCGCTTTTCTCTTC

200/200

3

4/0.51

9

Y

PvM054 (PVEPSE2015G11)

TC5

GCATCGTTGTTTCCTTCACA

GATTGGAGAGCGGATTGGTA

193/193

3

2/0.09

 

Y

PvM055 (PVEPSE2014C04)

AT6

TGGTCTTCCTGGAGATGAAAG

GCACAAAGTGCCCAAATG

209/209

1

Mono

 

N

PvM056 (PVEPSE2013B09)

TA6

AGCTGGCAGAAACTTGGAAA

TTGAAACCCAGGTCTATTCTCTTC

214/214

3

4/0.62

1

Y

PvM057 (PVEPSE2030D11)

CT5

TCCTCAAATGCTTGGTTTCA

CCGGTTCTCACCAGATTGTT

199/199

1

Mono

 

N

PvM058 (PVEPSE2031B01)

TC5

ATTGGGACGGGGATTG

ACTTTTCCTTCTCTTCTCCTCT

151/151

3

3/0.38

 

Y

PvM059 (PVEPSE2031C12)

CT5

TGAGGCACACTTCGACTACAA

ATGGCAAGAACGTGAAAAGG

158/158

2

2/0.38

8

Y

PvM060 (PVEPSE2032B08)

AC5

TTCACATTCTTCACTCACA

ATCCCTTGGACGATGAC

161/161

3

2/0.08

 

Y

PvM061 (PVEPSE2033A05)

AC6

GAAAAAGCTATGGGCCACAC

CGGTAGAGAATCCAGCGAGA

231/231

2

2/0.39

9

N

PvM062 (PVEPSE2033F05)

TC5

GCACCACTTTCTCAGATTTGG

CTGTCATGGCGATGGTGTTA

172/172

3

3/0.48

5

Y

PvM064 (PVEPSE2035G05)

GA6

AGTACCCTACACGTATCACTG

GCCACTAGCCCATCTTCT

163/163

1

Nd

  

PvM065 (PVEPSE2129G03)

TA5

GAGCGCACAAATGCAATAAT

GGGAGGATAACGACAATAGG

241/241

1

2/0.09

 

Y

PvM066 (PVEPSE3001H04)

AT5

CCTCAGCAAGCTCCGTAAAC

CATGCAACCTGAAACACTCC

196/196

1

2/0.51

6

Y

PvM067 (PVEPSE3002D09)

GT5

CTGGTGCAGCAAGGTTTTTC

TGCGCCAGAATTTACAATACAC

216/216

1

2/0.09

 

Y

PvM068 (PVEPSE3007B09)

AT6

CCATTACGTGTCCAAGGTCTC

CAAAAAGGAATCGGACTCTAGG

269/269

3

3/0.51

 

Y

PvM069 (PVEPSE3008F01)

TC7

CAATAAAAACCGCAGAGAATCC

GCGTAAGCAGGTGGGTAAGT

217/217

1

2/0.09

 

N

PvM070 (PVEPSE3010C09)

AT6

GAAGGGTCATTGTGGAC

TCTTTTGTCACTCCTAATCC

161/161

1

Nd

11

 

PvM072 (TC144)

TC9

GAAACACAATGGCTCAAGCA

CAAACCAGCAGCAACAAGAG

200/200

3

Mono

 

Y

PvM073 (TC154)

AAG6

CTTCACCGATCTGACAGCAG

TTCTCCAGGAACCCCTTCTTT

194/600

4

3/0.44

9

Y

PvM074 (TC241)

GCG5

TGAACACCCTTTCGTCAACTC

CCTTCTCCTCCCCTGATTTT

200/450

4

2/0.08

 

Y

PvM075 (PVEPLE1001E04)

GAT5

ATTGGAAGGGGGATGAACCT

TAGGAGAGTGCCCAGTGCTT

222/222

4

3/0.44

9

Y

PvM078 (PVEPSE2003D01)

TCT6

CATTACTCCCTTCCCTTCCA

ACTTCACTGGCACTCACAGG

174/174

1

Nd

3

 

PvM079 (PVEPSE2003F03)

GAA5

TCCGAAACTAACAGAACAAGGA

TTATGGACAGTGGACGAACG

191/191

1

2/0.5

 

Y

PvM080 (PVEPSE2004B12)

CAC5

ACTATCCCCAACAACCACCA

TCATAGCCTCCACCAGAAGG

204/204

4

Mono

 

Y

PvM081 (PVEPSE2004F01)

ATG5

TCCCAGTGAAATCTGCTACAT

CCAACAATAAAATGGCACAAA

176/176

4

2/0.08

 

Y

PvM082 (PVEPSE2004G10)

TTA5

TTTCATCTTCAAAACTCTCATCAA

ATGGCAGACCGAACTCTCTA

183/183

4

2/0.16

 

Y

PvM083 (PVEPSE2005C02)

TTC5

AGAAATGAGTGAGCGTGTCG

ACGGCTGATAGAGCGGGTA

152/152

1

Mono

 

Y

PvM084 (PVEPSE3013B07)

TG5

AGAAGGTGAAGTATGATTTA

TACATTGATTTTGGGTCA

244/244

1

Mono

 

N

PvM085 (PVEPSE3015B05)

TA6

ATTCACGGTTAGGATAGAT

TGGCTGTCTTGTGTTTCT

111/111

1

Mono

 

N

PvM086 (PVEPSE3018D04)

AT5

ACCGGGAGAAAAGGAAGAAC

GCCAAAAAGTAAGAAGCAGCA

210/250

1

2/0.09

 

Y

PvM087 (PVEPSE3021G12)

TA5

CATCACGACAGTTTTCC

CATTACATTACACCTATTCA

278/278

1

Nd

3

 

PvM088 (PVEPSE3022A06)

AG5

AGGTGCAAAAGCAAGAATGC

TCCCCAGCAGTATGATGACA

208/208

1

Nd

2

Y

PvM089 (PVEPSE3023B04)

TC5

CGAAGTAGCACGCAGAGAGA

GCAAGACGGGAGTGATGG

185/290

1

2/0.08

 

Y

PvM090 (PVEPSE3023H10)

TC6

CCCTTCACCGCTCCATACT

CGGAAACAGTGGCTGGTCTA

250/250

1

2/0.08

 

Y

PvM092 (PVEPSE3027F14)

TA6

CGTGGGCTACACTGGAAGAC

CATCTGCAAATGCTTGCTGT

240/240

1

3/0.35

 

Y

PvM093 (PVEPSE3029J06)

GA5

TTATATGCGGAGCAAAGGATG

GACCGACAAAGCCTTCATTC

216/216

1

2/0.38

2

Y

PvM094 (PVEPSE3030F08)

CT6

AGTCACCGGATGCTCTGAAG

GGGGTTTAGGGAAAGCAAAA

185/185

1

Mono

 

Y

PvM095 (TC17)

AC9

GGGCGAGTTCATCTTCACAA

AGGATCAACAGCCTCCAGTG

243/400

1

4/0.69

3

Y

PvM096 (TC18)

CT5

GCCAGTTTGTTGCTTGGAAT

GAAGAATGGTTGCTCCCTCA

190/190

1

Mono

 

Y

PvM097 (TC19)

TA5

CAAGAGTGAAGGGGCAGTTT

CGGCCAACCACTACTTTTAG

155/155

1

3/0.66

1

N

PvM098 (TC70)

TC5

CTCCCTCCTTCACACTCTTTG

GGGGTAGTCCTTTGGAACG

114/114

1

3/0.46

11

Y

PvM099 (TC70)

TC5

CTCTTTGTGTGGCTCCCTGT

GGTGGCATCTTTTTCTACCTCA

203/2000

1

Mono

 

Y

PvM100 (TC147)

AT7

GCCAATAACATCACCTCAT

GGGTAGTCAGTTTCTAAGCA

290/290

1

4/0.36

2

Y

PvM101 (TC158)

TC6

TCACATACAAGCACATCAACCA

CCAGCAACTCCAGACACAGT

176/660

1

Mono

 

Y

PvM102 (TC161)

CA5

CGGAAATAGAAACTCAAACTT

AATGGAGAGAGAGCAAGG

259/259

1

Mono

 

Y

PvM103 (TC168)

AG8

CGAGAAAGAGAGAGAAGAGTTT

GTGTTGGTGTGATGCTGAG

145/145

1

3/0.58

8

Y

PvM104 (TC187)

AC5

CCAATCGAAAGACCCAAATC

GATCGCAGAGCCTTCAAATC

191/191

1

2/0.08

 

Y

PvM105 (TC188)

AT5

CCGTATGAACATCAACCATT

CACAAGAGGATTTCCAACTCT

232/500

1

2/0.29

 

N

PvM106 (TC195)

AT5

GCTGGTGTGGAGATGATACT

TGTTGATGTTGAAAGGAGTG

219/219

1

Mono

 

Y

PvM107 (TC198)

AT5

GGAGCCCCTCACCAATAGAC

CGCCCTGGATCGTTAGATAG

347/347

1

Mono

 

Y

PvM108 (TC202)

CT5

CATCTTGAGTTTATCCCTGCTC

AATTCCAAGGCCATTGACAC

238/238

1

Nd

  

PvM110 (TC325)

CT5

CGCACACGCTCTCTCTCT

CTTCTGCTGCTCCTCAATCTT

202/

2

Nd

  

PvM111 (TC427)

TA5

TGGCTGGTAACAACAACTTCA

TACGACATGGACCAAAACGA

200/200

1

Mono

 

N

PvM112 (TC471)

AG5

GGTTCCTGCCCCAGAATC

TTGCTGCTTCCGTTTCAGTA

251/251

1

Mono

 

Y

PvM113 (TC514)

CT5

CTGGTGGAGTTGTGGCTGTA

GGATTCTGCTCAAAGGGAGA

180/180

1

Mono

 

Y

PvM114 (TC529)

CT5

TCTTCTTCTTCCAAGCCTTCC

TATGGCAGCAAACGGGTAT

201/1000

1

Mono

 

Y

PvM115 (PVEPLE1003G09)

CT25

AAATGTAAAGTGCTCCAT

CTGAGAGAAAGAAAGAGACA

143/143

2

13/0.91

2

Y

PvM116 (PVEPSE2002D05)

GA5

TATTGCCCAAAGATGCTTCC

ATACCCAAAATGCACCCACT

179/179

1

Mono

 

Y

PvM117 (PVEPSE2004H03)

TC7

CACACATCTCACCTTGTCTCTCTC

GCGGCATTCAACACTGCT

165/700

1

Mono

 

Y

PvM118 (PVEPSE2006F05)

TC8

GCGAACACATTCACACAACA

AATCCCGACCAAGTCTCCTT

215/215

1

5/0.54

8

Y

PvM119 (PVEPSE2006H01)

TC9

AGAAGAAGAAGTAGAACAGAATC

GCTGGAGTTGGGGTCAGT

226/1100

1

Nd

  

PvM120 (PVEPSE2009C06)

TC6

CCCCATCCTCACTCACAAAC

TCATTCTTCTGGTGCTGCTTT

211/211

1

2/0.39

1

Y

PvM123 (PVEPSE2013B07)

CT9

CCCACTACCACTCCTTTG

AGCGTCTGAACCCATTG

194/194

2

4/0.47

1

Y

PvM124 (PVEPSE2013E06)

TA5

TCCCCTACTGATGTGTTC

AAATGTCTGGTTTTGC

193/193

2

2/0.39

3

N

PvM125 (PVEPSE2014B09)

AC5

CAAACTCAACACCCTCTCA

GGAAACAGCAGCACCAC

198/198

1

Mono

 

N

PvM126 (PVEPSE2014F08)

TC7

AAATCCTCTTCCACCTTTG

AACACGCACACACAGACA

132/132

1

3/0.49

3

N

PvM127 (PVEPSE2015H07)

TC5

AACTTTCTTTGACCCTCTC

GCTTTGTCTTGTTCTTCCA

155/155

2

6/0.72

10

Y

PvM128 (PVEPSE2016C01)

GA11

GTTTCTGCGGTGAGAGTG

AGCCTTCGTCGTTCTTCT

130/130

1

3/0.43

9

N

PvM129 (PVEPSE2017D09)

GA5

GGTAGGACAACAAGGTAACG

AAAACAACGCAGGAAATG

167/167

2

Mono

 

N

PvM130 (PVEPSE2018H02)

TA5

TGGACAACAACACTACACA

AAGACATTCACATAATAAGG

265/265

2

2/0.18

 

N

PvM132 (PVEPSE2018H10)

AG5

GCCGAAGCAGATAAAAGG

TGTTCTCGTCTCCAATGC

191/191

2

4/0.51

3

Y

PvM133 (PVEPSE2019C09)

AT5

GAAGTCTCTTGGGTTTCAGA

CCCTATTTTTCACTCTCACC

193/193

2

Mono

 

N

PvM134 (PVEPSE2020C04)

CA5

TCATACTACCTTGTTCTTACATTCA

CACGCTGTTCCACCTG

182/182

2

Mono

 

Y

PvM135 (PVEPSE2005C06)

TTG5

TCTCTCTGTTTCTTTTCTGGGTTT

CGTTGTCTTTTTCTCCGCTTT

151/225

1

Mono

 

N

PvM136 (PVEPSE2006E08)

TGG5

GCAACTATGCTGGGAAAGGA

GGGCATTCTTCAGATTCTCG

217/217

1

2/0.08

 

Y

PvM137 (PVEPSE2007B06)

TTC6

TTCTCCTGTCCCTCCTTGTG

GCCTTCCCACCAGGTTTAG

197/197

1

2/0.16

 

Y

PvM139 (PVEPSE2011H08)

AGC5

AGAGGACGATGGATTGGT

TCAGAACAAGGGTTTTCG

288/288

2

Mono

 

N

PvM141 (PVEPSE2013G03)

CCA5

CTTCGTCATCTCCCACAA

CCATCATCTCCTTTGGAA

214/214

2

Mono

 

N

PvM142 (PVEPSE2014H11)

CAG5

CAGATAAATAGCCCTGTGC

GCATTCAAACGATGACTCTT

188/188

1

2/0.16

 

N

PvM143 (PVEPSE2016B08)

ATG5

TCTTCCACTCCTCCACCT

CCTAAGCACCCCAAAAAT

183/170

1

Mono

 

N

PvM145 (PVEPSE2019C10)

TCC5

TTTCAGTTCGGGATTGTTCC

ATTGGTGGAGGTGGGAGAG

203/203

1

3/0.16

5

Y

PvM146 (PVEPSE2020D07)

CGC5

ACCATTGACTCCGATGT

ACGATAAACCCAATCCACCA

187/400

1

Mono

 

Y

PvM147 (PVEPSE2020F11)

TCA5

ATTTGCTGTTTTCTGCTG

GAAGTTGAGGTGGGAGGT

151/151

1

Mono

 

N

PvM148 (PVEPSE2023B04)

CCA7

ACCTCAAAACCCACCACAAA

GAAGTGCTCCCAGATGAAGG

191/191

1

3/0.48

3

Y

PvM149 (PVEPSE2025B02)

ACG5

ATGACGAGGAACCAGACACC

GTCGCTTCAACGAGGATGTT

213/213

1

2/0.08

 

Y

PvM150 (PVEPSE2030D10)

TCT5

CTCCCAAGTTCCCCTTTTTC

ATGCGTCCAACCCTTATGTC

199/199

1

2/0.43

11

Y

PvM151 (PVEPSE2031D01)

TTA6

GGGCTGCAAAGGTGACATTA

ACCGAAAACCCATGCTACTC

204/215

1

3/0.29

 

Y

PvM152 (PVEPSE2032F06)

TTG6

ATTTTGGAGCGAAACAGCAT

GAGAACCTCGTCGTCGTCTT

200/200

1

4/0.36

 

Y

PvM153 (PVEPSE3002B08)

AGA5

ATGGGCGATCTGGACTATGT

TTGAAGACCAAGCCAAGAGAA

183/270

1

2/0.41

2

Y

PvM154 (PVEPSE3021F08)

TCA5

ATTCACCTCCTTCTGCTTCG

GCTCCTTCTCTCCAGTCTCG

216/490

1

Mono

 

Y

PvM155 (PVEPSE3029G07)

AAC5

AAGTATGGAAACTGGGGCTGT

GTGCGTGGAATAATGTGGTG

206/206

2

2/0.08

 

Y

PvM156 (PVEPSE2021C05)

TTC6

CACACTTCAACTCCAAAGG

CCAACCCTCGCAAAAT

219/1100

2

Nd

  

aFollowing the repeats motif, the number of repeat units is shown

bAt least one genotype amplified the observed allele

c Detailed in Material and methods

dNa number of alleles observed considering all of the bean genotypes (24), PIC polymorphic information content calculated as described in Hanai et al. (2007), Nd not determined as there was no amplification or weak amplification, Mono monomorphic locus in all of the studied bean genotypes

Map construction

The segregation of each AFLP and RGA locus was scored by the presence or absence of the fragment. EST-SSR as well as rare codominant AFLP loci were scored by identifying the parental fragments in the segregating population. Goodness-of-fit tests for 1:1 segregation ratio were performed for all makers segregating in the 74 F8 RILs.

For the construction of the map, we adopted the following approach using the software MAPMAKER v. 3.0 (Lander et al. 1987). Segregation data here obtained (EST-SSR, RGA and AFLP markers) were merged with available data of markers placed on the framework of the core map (Freyre et al. 1998). Initially, three RFLP markers equally distant were anchored to their respective linkage group using the ‘anchor’ command. The ‘assign’ command (LOD > 3) was used to assign all other markers to the linkage groups. In each linkage group, the order of 10 highly informative markers was defined using the ‘order’ command. Then, the other markers were added to the map using the ‘build’ command (LOD > 2.0). Loci that could not be ordered with the default log-likelihood threshold value were referred to as accessory markers and placed in the most likely interval. The Kosambi mapping function was used for the calculation of map distances (Kosambi 1944). Map drawings were generated using MapChart (Voorrips 2002). The nomenclature and orientation of linkage groups followed the recent changes adopted by the Genetics Committee of the Bean Improvement Committee (Pedrosa-Harand et al. 2008).

Results and discussion

Allelic variation at EST-SSR loci

Out of 156 primer pairs designed initially, 139 amplified 140 loci of which 40 were analyzed previously (Hanai et al. 2007). The remaining 100 loci were evaluated in the present study using a set of bean genotypes (Table 2). About 13 amplicons were larger than expected, probably due to the presence of introns between primer sites. Nevertheless, only 11 EST-SSR loci presented a non-optimal amplification pattern and were not analyzed. A total of 89 pairs of primers amplified fragments that were easy to score, 54 of which revealed polymorphisms among the 24 bean genotypes. The number of alleles per polymorphic locus varied from 2 to 13 with an average of 2.7. The polymorphic information content (PIC) of the 54 loci ranged between 0.08 and 0.89, with a mean PIC of 0.40.

Our data agree with previous findings that reported an average of 2.9 (Yu et al. 1999) and 3.1 alleles per locus (Guerra-Sanz 2004) as both studies analyzed genic SSR in bean accessions. Generally, SSRs from anonymous sequences are regarded as more informative than SSRs of genic origin. For example, average values of six and seven alleles per locus were described by Gaitán-Solís et al. (2002) and Buso et al. (2006), respectively. The fact that expressed sequences are associated with biological processes and therefore are more conserved than anonymous ones could explain these differences; however, when the same set of bean genotypes were analyzed using SSR loci developed from genic and genomic sources, the results showed similar average values for PIC and number of alleles per locus between genic and genomic SSRs (Hanai et al. 2007).

A considerable number of polymorphic SSR loci is generally required for variety identification or even for pedigree analysis when polymorphisms are used for tracing parentage (Guerra-Sanz 2004). The locus PvM115 containing a CT motif repeated 25 times showed both higher PIC (0.89) and number of alleles (13) in the 24 genotypes analyzed (Fig. 1). In our previous study, 12 alleles were detected at the PvM21 locus (Hanai et al. 2007). Thus, these two EST-SSR loci are very informative and may be useful in both types of analyses.
https://static-content.springer.com/image/art%3A10.1007%2Fs11032-009-9306-7/MediaObjects/11032_2009_9306_Fig1_HTML.gif
Fig. 1

Electrophoretic pattern at PvM115 locus (EST-SSR) in 24 Phaseolus genotypes detected in 6% silver-stained polyacrylamide gel. 10-bp DNA ladder (Invitrogen) are in first and last lane

An updated common bean core map

We screened ‘BAT93’ and ‘Jalo EEP558’ for polymorphisms using 156 EST-SSR primer pairs of the PvM series, 16 combinations of restriction enzymes (RsaI, HindIII, AluI and DraI) and NBS primers (Table 1) through the NBS-profiling methodology and 28 combinations of AFLP selective primers. A total of 140 EST-SSR primer pairs amplified scorable loci, of which 50 were polymorphic. Regarding the NBS-profiling method, the restriction enzyme RsaI was chosen because it generated better amplification profiles and more polymorphic RGA loci (data not shown). The four NBS primers in combination with RsaI produced 194 loci, of which 32 were polymorphic (Fig. 2). In addition, the AFLP selective primer combinations (12 from EcoRI/MseI and 16 from PstI/MseI digestions) amplified 1,252 loci, 29% of them being polymorphic. From these, 15 combinations producing 203 polymorphic loci were selected for genotyping the mapping population (Table 3).
https://static-content.springer.com/image/art%3A10.1007%2Fs11032-009-9306-7/MediaObjects/11032_2009_9306_Fig2_HTML.gif
Fig. 2

Amplification pattern of RGA markers in 6% silver-stained polyacrylamide gel. The DNA was digested with RsaI and amplified using the primers AP and NBSa-F. The parental lines are represented in duplicate (‘BAT 93’, lanes 1 and 2, and ‘Jalo EEP558’, lanes 3 and 4); lanes 6 through 35 correspond to F8 RILs. Arrows indicate polymorphic loci. Lane 5 shows the 25-pb DNA ladder (Invitrogen)

Table 3

Number of polymorphic loci per combination of AFLP primers

Primer combination

Selective nucleotides

Number of polymorphic loci

P31M64

P + AAA, M + GCT

18

P32M63

P + AAC, M + GCA

19

P37M64

P + ACG, M + GCT

5

P39M65

P + AGA, M + GGA

8

P39M63

P + AGA, M + GCA

11

P38M65

P + ACT, M + GGA

4

P32M64

P + AAC, M + GCT

6

E31M48

E + AAA, M + CAC

20

E39M49

E + AGA, M + CAG

10

E40M56

E + AGC, M + CGC

23

E37M60

E + ACG, M + CTC

23

E31M60

E + AAA, M + CTC

18

E40M49

E + AGC, M + CAG

8

E31M49

E + AAA, M + CAG

18

E39M48

E + AGA, M + CAC

12

Total

203

EEcoRI complementary primer, PPstI complementary primer, MMseI complementary primer

The merging of the data of the 285 loci developed in this study (50 EST-SSR, 32 RGA and 203 AFLP) with the data of 143 markers previously mapped into the core common bean linkage map (Freyre et al. 1998) resulted in a map comprised of 413 DNA markers (Table 4) distributed in 11 linkage groups (LG). About 15 markers remained unlinked. The length of the new linkage map was estimated at 1,259 cM, corresponding to an average of one marker per 3.0 cM. The number of markers per LG ranged from 32 (10) to 50 (8) while the LG lengths varied from 75 (5) to 147 cM (2).
Table 4

Distribution of different types of marker over the linkage groups (LG) of the novel common bean core map, and their lengths in centimorgans (cM)

LG

No. of markers previously mappeda

No. of novel markers

Total

Length (cM)

EST-SSR

RGA

AFLP

1

14

6

3

21

44

129.0

2

15

6

4

14

39

146.7

3

12

7

2

21

42

143.0

4

8

1

3

23

35

99.6

5

15

5

1

18

39

75.2

6

15

2

0

16

33

97.1

7

14

2

4

14

34

105.4

8

11

7

4

28

50

146.1

9

7

7

1

11

26

123.1

10

9

4

5

14

32

108.4

11

11

3

5

20

39

85.2

Total

131

50

32

200

413

1258.8

a Markers previously assigned to the framework of the common bean integrated map (Freyre et al. 1998). EST-SSR expressed sequence tag derived single sequence repeats, RGA resistance gene analog markers based on NBS-profiling method

The levels of efficiency of both QTL mapping and selection based on DNA markers is enhanced when regularly spaced markers are available throughout the linkage groups (Lander and Botstein 1989). If the number of markers allocated to map positions is high, existing gaps are more likely to be saturated. With the integration of 282 new markers (50 EST-SSR, 32 RGA and 200 AFLP) into the common bean core map, we were able to place new markers in some existing gaps. In LG 3, for instance, five AFLP, one RGA, and one EST-SSR markers were positioned between markers Bng12 and D1151 and in LG 6 three AFLP and one EST-SSR markers were positioned between markers ROF7a and D1086. Similarly, additional markers were placed in two linkage groups within regions where QTL for resistance to anthracnose were mapped before (Miklas et al. 2006b): the QTL interval (40–75 cM) in LG 1 was saturated with seven AFLP and two EST-SSR markers whereas the QTL interval in LG 2 (65–95 cM) was saturated with 14 new markers, including 4 RGA (Fig. 3).
https://static-content.springer.com/image/art%3A10.1007%2Fs11032-009-9306-7/MediaObjects/11032_2009_9306_Fig3a_HTML.gifhttps://static-content.springer.com/image/art%3A10.1007%2Fs11032-009-9306-7/MediaObjects/11032_2009_9306_Fig3b_HTML.gif
Fig. 3

An updated common bean molecular linkage map based on the ‘BAT93’ × ‘Jalo EEP558’ RIL population. The revised orientation and nomenclature of linkage groups follows that of the Bean Improvement Cooperative (http://www.css.msu.edu/bic/Genetics.cfm). About 261 markers were ordered with LOD > 2.0 and their distances (cM) from top to bottom are indicated to the left of linkage groups (LG). About 152 markers were assigned to linkage groups but not ordered in multipoint analyses (LOD > 2.0) and were placed in the most likely interval (gray boxes) without changing the map distances. Loci with distorted segregation ratios are indicated by asterisks (*P < 0.05; **P < 0.01; ***P < 0.001 for markers skewed toward ‘BAT93’) or degree symbols (°P < 0.05; °°P < 0.01; °°°P < 0.001 for markers skewed toward ‘Jalo EEE558’)

Slight discrepancies were observed between the present map and the previous one (Freyre et al. 1998). Linkage groups 2, 6 and 11 became shorter while LG 1, 3, 8, 9 and 10 became longer. These discrepancies are probably due to the size of the mapping population and the kind of markers used. In order to develop a core linkage map and align the existing RFLP maps, Freyre et al. (1998) used a number of markers with more missing data and a smaller population. For instance, the LG 2 of the Freyre’s map had 175 cM while the corresponding groups in the Florida and Davis’ maps had 128 and 107 cM, respectively (Nodari et al. 1993a; Vallejos et al. 1992). In addition, the present map is about 30 cM longer than the one reported by Freyre et al. (1998), because new markers were positioned at the end of the groups, e.g., LG 10 had eight new loci mapped as terminal markers, expanding its size to more than 36 cM (Fig. 3).

Segregation features

Most of the markers (82.5%) showed a 1:1 segregation ratio of the parental alleles (P < 0.05), as expected in a RIL population. Among the newly positioned markers, 13 EST-SSR (26%), 7 RGA (22%) and 28 AFLP (14%) showed segregation distortion. Gametes in direct competition, meiotic drive, and genes controlling pollen lethality are factors that affect allele segregation during meiosis and can produce distorted ratios (Moyle and Graham 2006). Among the 28 AFLP loci with distorted segregation, similar numbers were found skewed towards ‘BAT93’ alleles (15) and ‘Jalo EEP558’ alleles (13). In contrast, segregation distortion affecting EST-SSR and RGA loci favored ‘BAT93’ alleles. Nine EST-SSR and five RGA loci showed an excess of ‘BAT93’ alleles, while four EST-SSR and two RGA loci showed an excess of ‘Jalo EEP558’ alleles. This could be explained by the higher adaptability of lines carrying ‘BAT93’ alleles. Since we used SSR markers that are within genes it is possible that their products were affected by natural selection leading to the observed bias in the segregation ratios. Following allelic frequencies of SSR loci in 24 generations, Rodrigues and dos Santos (2006) reported that all loci were affected by natural selection, which favored one of the parental common bean accessions (‘Carioca MG’) at 29 out of 30 loci.

Interestingly, markers showing distorted segregation were mainly located in six linkage groups. An excess of ‘Jalo EEP558’ alleles were positioned in two regions located on LG 1 and 6, while an excess of ‘BAT93’ alleles were mapped in four regions located in LG 2, 7, 8 and 9. The clustering of markers with segregation distortion possibly reflects the location of genes that were favored by either meiotic selection or inadvertent selection in BJ population.

Marker distribution

Table 4 shows the distribution of marker types in the common bean linkage groups together with group lengths (in cM). Non-anonymous EST-SSR and RGA markers were mapped to all linkage groups, excluding LG 6. About 50 EST-SSR markers were ordered with LOD > 2.0 into 40 distinct positions of the 11 linkage groups of the BJ map. Although EST-SSR were positioned on all LGs, their distribution was not uniform and varied from one in LG 4 to seven markers in LG 3, LG 8 and LG 9 (Table 4). Interestingly, LG 4 is the group in which most of the microsatellites studied by Yu and coauthors were mapped (Yu et al. 2000). This illustrates the complementariness of both studies regarding the saturation of the core map with SSR markers.

In general, we did not observe a direct relation between number of markers and length of the LGs. The shortest linkage group (75 cM) had as many markers (39) as the largest one (123 cM), which contained 26 markers (Table 4). This could be explained by the clustering pattern in some regions of the bean genome. Using absolute co-segregation of three or more markers as a criterion for defining a cluster we inferred clustering in seven LGs: 1, 2, 3, 4, 6, 8 and 11, with large clusters (>8 markers) in groups 4, 8 and 11 (Fig. 3). AFLP markers formed the majority of the clusters. The uneven distribution of AFLP markers derived from double digestion with EcoRI and MseI was previously reported in other legume species such as soybean (Young et al. 1999) and adzuki bean (Vigna angularis; Han et al. 2005) but also in the yellow passion fruit (Lopes et al. 2006). The preferential localization of AFLP loci in DNA regions of recombination suppression may be associated with the restriction enzymes used, which may favor the finding of these markers in centromeric regions, for example (Troggio et al. 2007), as they may require methylation to maintain their specialized functions. Here, we used the combinations PstI with MseI and EcoRI with MseI, as suggested by Young et al. (1999). These authors proposed that PstI, which is blocked by methylation would be more efficient than EcoRI in producing AFLP markers placed at random on linkage maps. In fact, out of 51 PstI/MseI-derived markers, only five were found completely linked, two being located in the cluster of LG 4 and three in the cluster of LG 8.

Mapping markers with putative known function

Several EST-SSR showing similarities with known and unknown proteins were mapped in several linkage groups. These include markers with highly significant e-values (<e−30) such as PvM61 (LG 9) from a sequence similar to members of the stress-related NAC transcription factor family (Fang et al. 2008); PvM18 (LG 5) from a sequence similar to the leucine-rich repeat (LRR) domain of plant disease resistance genes (Ryan et al. 2007); and PvM87 (LG 3) from an EST similar to subtilisin-like proteases, a class of enzymes involved in recognition of pathogens and activation of defense responses (van der Hoorn and Jones 2004). A complete list of the putative function of ESTs from which SSR markers were developed in this work is presented in Table 5.
Table 5

EST-SSR and RGA clones with similarity (e-value < e−5) to protein sequences deposited in GenBank

Marker code (Sequence name)

Linkage group

GenBank access number

Homology

E-value

Organism matched

EST-SSR

    PvM001 (TC34)

8

P25699

Ferritin

4e-67

Phaseolus vulgaris

    PvM002 (TC116)

10

ABE77731

Conserved hypothetical protein

4e-16

Medicago truncatula

    PvM007 (TC127)

5

ABA40448

Fructokinase 2-like protein

5e-71

Solanum tuberosum

    PvM010 (PVEPSE3030I07)

1

NP_194345

Cytokinin-responsive GATA factor 1

1e-9

Arabidopsis thaliana

    PvM012 (PVEPSE3030L20)

4

ABE81465

C2 domain-containing protein

5e-34

Medicago truncatula

    PvM013 (PVEPSE3030M09)

10

NP_565320

Proteína ribosomal 40S S17 (RPS17B)

3e-46

Arabidopsis thaliana

    PvM017 (PVEPSE2030E02)

8

CAA42617

Ribulose bisphosphate carboxylase

8e-41

Phaseolus vulgaris

    PvM018 (PVEPSE3003E05)

5

NP_188718

Leucine-rich repeat family protein

2e-29

Arabidopsis thaliana

    PvM022 (PVEPSE2004H10)

9

BAG09558

Chloroplast RNA binding protein

9e-28

Mesembryanthemum crystallinum

    PvM034 (PVEPSE3027C10)

9

BAA19769

SRC2 cold induced protein

1e-37

Glycine max

    PvM036 (PVEPSE3011F10)

7

NP_194937

Galactosyltransferase

8e-17

Arabidopsis thaliana

    PvM046 (PVEPSE2024B07)

2

Q94A43

BES1/BZR1 homolog protein 2

4e-21

Arabidopsis thaliana

    PvM052 (PVEPSE2018H03)

5

NP_196885.1

Glutaredoxin family protein

7e-05

Arabidopsis thaliana

    PvM059 (PVEPSE2031C12)

8

CAN61408

Hypothetical protein

1e-44

Vitis vinifera

    PvM061 (PVEPSE2033A05)

9

ACD39379

NAC domain protein

1e-50

Glycine max

    PvM066 (PVEPSE3001H04)

6

NP_001077728

Dormancy/auxin associated family protein

3e-12

Arabidopsis thaliana

    PvM073 (TC154)

9

AAB00554

Dehydrin

3e-21

Phaseolus vulgaris

    PvM075 (PVEPLE1001E04)

9

CAN73178

Hypothetical protein

7e-25

Vitis vinifera

    PvM078 (PVEPSE2003D01)

3

CAO64383

Unnamed protein product

2e-28

Vitis vinifera

    PvM087 (PVEPSE3021G12)

3

AAY54007.1

Subtilisin-like protease

3e-76

Arachis hypogaea

    PvM093 (PVEPSE3029J06)

2

Q40287

Anthocyanidin 3-O-glucosyltransferase 5

9e-18

Manihot esculenta

    PvM095 (TC17)

3

P49357

Serine hydroxymethyltransferase 1

2e-66

Flaveria pringlei

    PvM097 (TC19)

1

AAO91809

Drought induced protein

1e-38

G. latifolia

    PvM098 (TC70)

11

NP_200264

Hypothetical protein

5e-35

A. thaliana

    PvM103 (TC168)

8

AAN03469

Ubiquitin-conjugation enzyme

6e-71

G. max

    PvM118 (PVEPSE2006F05)

8

ABF70090.1

Putative protein kinase

3e-60

Musa balbisiana

    PvM120 (PVEPSE2009C06)

1

ABO78563

Glycine cleavage system P-protein

7e-06

M. truncatula

    PvM124 (PVEPSE2013E06)

3

AAM63014.1

Unknown

5e-27

A. thaliana

    PvM127 (PVEPSE2015H07)

10

CAN64365

Hypothetical protein

2e-07

V. vinifera

    PvM148 (PVEPSE2023B04)

3

AAW28572.1

Putative oxygen evolving enhancer protein 3, identical

1e-38

Solanum demissum

    PvM150 (PVEPSE2030D10)

11

NP_191557.1

tRNA-binding region domain-containing protein

3e-47

A. thaliana

    PvM153 (PVEPSE3002B08)

2

AAL50980

Bax inhibitor-like protein

5e-13

Brassica oleracea

RGA

    RNF330 (RNBSaF330)

11

ABE86051.1

Disease resistance protein

9e-25

Medicago truncatula

    RNF356 (RNBSaF356)

10

AAC49509

Disease resistance protein homolog

2e-16

Glycine max

    RNF475 (RNBSaF475)

11

AAC33296.1

NBS type putative resistance protein

3e-74

Phaseolus vulgaris

    RRF380 (RRGPF380)

10

AAF44094.1

Disease resistance-like protein

9e-45

Glycine max

    RRF410 (RRGPF410)

11

ABN42886.1

Resistance protein

1e-42

Phaseolus vulgaris

    RKF310 (RKDCF310)

4

ABD28710

Polynucleotidyl transferase, Ribonuclease H fold

2e-7

Medicago truncatula

    RKR240 (RKDCR240)

8

AAR13317

gag-pol polyprotein

2e-7

Phaseolus vulgaris

Mapping of RGA markers

About 32 RGA loci generated with the NBS-profiling method using four degenerated primers that target the NBS domain were mapped at 26 positions on 10 linkage groups (Fig. 3). The remaining six mapped at exactly the same loci (RKF275 and RNF230 on LG 1; RNF90, RNF115 and RNF180 on LG 2; RKF500 and RKF510 on LG 7; RKF318 and RKF320 on LG 8; and RNF330 and RNF475 on LG 11). This was expected, as many disease resistance genes occur in clusters as complex loci in many plant species, including common bean. The anthracnose resistance locus Co-4 is such an example as it contains five copies of the COK-4 gene (Melotto et al. 2004). Vallejos et al. (2006) showed that multiple copies of a gene member of the TIR–NBS–LRR family were present within the I locus, which confers resistance to Bean common mosaic virus.

At least five RGA markers mapped to regions containing resistance genes for anthracnose and rust diseases. In LG 1 the marker RNF120 co-located with Co-1, Co-x, Co-w and Ur-9 genes; in LG 7 the marker RKR385 was mapped near to Co-6 gene; and in LG 11 three markers (RNF330, RRF410 and RNF475) were positioned in the region containing the Co-2 gene against anthracnose and Ur-3, Ur-11 and Ur-Dorado genes against rust (Miklas et al. 2006a). The RGA markers were also positioned in the vicinity of QTLs located on the core map (Miklas et al. 2006a). For instance, markers RKF275 and RNF230 (LG 1) were mapped near to QTLs for resistance to common bacterial blight and white mold. In LG 2, the marker RRF230 was positioned in a region containing QTLs for resistance to common bacterial blight and anthracnose as well as RNF115, RNF180 and RNF90 co-located with a QTL for resistance to white mold. The RGA RNF240 mapped to a region that a QTL for resistance to Fusarium root rot was located in LG 3. The marker RKR230 (LG 5) was mapped together a QTL for resistance to white mold, and markers RKF500 and RKF510 (LG 7) co-positioned with a QTL conditioning common bacterial blight. The marker RRF550 (LG 10) was mapped near a QTL for resistance to angular leaf spot, and the markers RNF330, RRF410 and RNF475 (LG 11) were mapped near a QTL region for resistance to anthracnose (Miklas et al. 2006a).

About 16 RGA fragments were sequenced, and five sequences showed high similarity with plant resistance proteins (Table 5). The BLASTx analyses showed that RNF356 and RRF380 sequences are similar to resistance proteins from Glycine max. Similarly, sequences of RNF475 and RRF410 were highly similar to resistance proteins from P. vulgaris as well as the RNF330 sequence has similarity with a resistance protein from Medicago truncatula. Several tagging approaches in candidate genes have been used for analyzing resistance genes in crop species, including common bean (López et al. 2003; Miklas et al. 2006b; Rivkin et al. 1999). Here we demonstrate the feasibility of NBS-profiling methodology for generating RGA loci as well as a complementary tool for tagging RGA that were not yet mapped in the common bean genome.

Acknowledgments

Authors are in debt with the Brazilian institutions Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP: grants 2004/13547-9 and 2008/54732-4 and scholarships 2004/07614-5 and 2008/52269-5), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

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© The Author(s) 2009