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  • Research article
  • Open Access
  • Large-scale microsatellite development in grasspea (Lathyrus sativus L.), an orphan legume of the arid areas

    • 1,
    • 1,
    • 2,
    • 3,
    • 3,
    • 4,
    • 5,
    • 1,
    • 1,
    • 6,
    • 6,
    • 1 and
    • 1Email author
    Contributed equally
    BMC Plant Biology201414:65

    https://doi.org/10.1186/1471-2229-14-65

    • Received: 19 July 2013
    • Accepted: 12 March 2014
    • Published:

    Abstract

    Background

    Grasspea (Lathyrus sativus L., 2n = 14), a member of the family Leguminosae, holds great agronomic potential as grain and forage legume crop in the arid areas for its superb resilience to abiotic stresses such as drought, flood and salinity. The crop could not make much progress through conventional breeding in the past, and there are hardly any detailed molecular biology studies due to paucity of reliable molecular markers representative of the entire genome.

    Results

    Using the 454 FLX Titanium pyrosequencing technique, 651,827 simple sequence repeat (SSR) loci were identified and 50,144 nonredundant primer pairs were successfully designed, of which 288 were randomly selected for validation among 23 L. sativus and one L. cicera accessions of diverse provenance. 74 were polymorphic, 70 monomorphic, and 144 with no PCR product. The number of observed alleles ranged from two to five, the observed heterozygosity from 0 to 0.9545, and Shannon’s information index ranged from 0.1013 to 1.0980, respectively. The dendrogram constructed by using unweighted pair group method with arithmetic mean (UPGMA) based on Nei's genetic distance, showed obvious distinctions and understandable relationships among the 24 accessions.

    Conclusions

    The large number of SSR primer pairs developed in this study would make a significant contribution to genomics enabled improvement of grasspea.

    Keywords

    • Lathyrus sativus L
    • Microsatellite
    • 454 FLX Titanium pyrosequencing
    • Marker development

    Background

    Grasspea (Lathyrus sativus L.) is an excellent candidate crop to provide protein and starch for human diets and animal feeds in the arid areas [1]. It is one of the hardiest crops for adaptation to climate change because of its ability to survive drought, flood and salinity [2]. It also plays a vital role in many low input farming systems [3]. However, undesirable features such as prostrate plant habit, indeterminate growth, pod shattering, later maturity and presence of neurotoxin, β-N-oxalyl-L-α,β-diaminopropionic acid (β-ODAP), limit its cultivation under various agro-ecological conditions [46].

    To date, less than 205 microsatellite (SSR) markers have been published for grasspea, and only 61 of them were characterized for size polymorphism [79]. Lioi et al., [7] searched for the presence of SSRs with the European Molecular Biology Laboratory (EMBL) nucleotide sequence database. Ten out of 20 SSR primers were successfully amplified, and only six of them exhibited size polymorphism. In addition, Ponnaiah et al., [8] searched for EST-SSRs in the National Center for Biotechnology Information (NCBI) database. Seven of the 19 Lathyrus EST-SSRs and four of the 24 Medicago EST-SSRs revealed polymorphism when screening L. sativus accessions [8]. Sun et al., [9] analyzed a total of 8,880 Lathyrus genus ESTs from the NCBI database (up to March 2011), identified 300 EST–SSR and designed primers to characterize for size polymorphism among 24 grasspea accessions. Among them 44 SSR markers were polymorphic, 117 markers monomorphic and 139 markers with no bands [9]. Lioi sequenced 400 randomly selected clones and get 119 retrieving SSR containing sequences. 7 primer pairs produced clearly distinguishable DNA banding patterns in 10 randomly selected SSRs, The transferability of SSR markers was high among three related species of Lathyrus, namely Lathyrus cicera, Lathyrus ochrus and Lathyrus tingitanus, and the legume crop, Pisum sativum [10].

    Next generation sequencing (NGS) technologies has become popular on its success of sequencing DNA at unprecedented speed thereby enabling impressive scientific achievements and novel biological applications [11, 12]. Next generation RNA sequencing (RNA-Seq) is rapidly replacing microarrays as the technology of choice for whole-transcriptome studies [13]. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods [14]. However, few studies solely focused on high-throughput novel microsatellite markers discovery of orphan crops via next generation sequencing [1519].

    Recently, we applied next generation sequencing to obtain high-quality putative SSR loci and flanking primer sequences inexpensively and efficiently. The novel SSR sequences were characterized and validated through successful amplification of randomly selected primer pairs across a selection of 23 grasspea accessions and one accession of its direct ancestor red pea (Lathyrus cicera) as an outgroup.

    Methods

    Plant material

    Eight grasspea (L. sativus) accessions consisted of two Chinese, two Asian, one African and three European accessions were used for the 454 sequencing.

    A set of 23 grasspea (L. sativus) accessions and one red pea (L. cicera) accession were used in SSR marker testing and genetic diversity analysis. These genetic resources contained six accessions from China, seven each from Asia (including one L. cicera accession) and Europe, and four from Africa.

    The seed samples were obtained from the National Genebank of China at Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China. Details information is given in Additional file 1: Table S1.

    DNA isolation, library preparation and 454 sequencing

    The sprouts from each of the eight genotypes were collected and total genomic DNA was isolated using the CTAB method from the seven-day old seedlings grown under dark condition at 18°C. A selective hybridization with streptavidin coated bead method was used to construct SSR-enriched genomic libraries. The following eight probes were used: p(AC)10, p(GA)10, p(AAC)8, p(AAG)8, p(AAT)8, p(ATGT)6, p(GATA)6 and p(AAAT)6. Libraries quality control was conducted by randomly selecting and sequencing 186 clones. The DNA fragments were inserted into pGEM-T EASY vector, and insert fragments were validated by Sanger sequencing. If the libraries had high ratio of insert fragments and most fragments length were from 500 to 800, they were considered as high quality.

    The eight SSR-enriched DNA libraries were equally pooled for pyrosequencing using the 454 Genome Sequencer FLX Titanium System at Beijing Autolab Biotechnology Co. Ltd (China). Finally, the 454 System collected the data and generated standard flow gram file (.sff) which contained raw data for all the reads. Then, grasspea.sff file was submitted to the sequence read archive (SRA) at the National Center for Biotechnology Information (NCBI) with the accession number SRX272771.

    Reads characterization

    All high quality reads were processed to remove adaptor-ligated regions using the Vectorstrip program in EMBOSS software package [20]. Moreover, in-house developed program such as: SeqTools.pl, ACGT.pl, ave_length.pl, and max.pl programs were used to analyze the total number of nucleotide A, T, C, G in all reads, the average length of all read sequences, and the maximum length read in our study.

    SSRs searching

    Before SSRs searching, “clean reads” were filtered redundant at 98% sequence identity, using CD-HIT program (http://weizhong-lab.ucsd.edu/cd-hit/). A high-throughput SSR search was performed using MISA (Microsatellite identification) tool (http://pgrc.ipk-gatersleben.de/misa/). The parameters were as following: minimum SSR motif length of 10 bp and repeat length of mono-10, di-6, tri-5, tetra-5, penta-5, and hexa-5. The maximum size of interruption allowed between two different SSR in a compound sequence was 100 bp.

    SSR characterization

    The MISA file was used to analyse the number of sequences containing SSRs, the number of SSRs detected, the number of SSRs starting within 200 bp of read sequences, the dominant types of SSR motifs within mono-, di-, tri-, tetra-, penta- and hexa- repeats, and the ratio of single, perfect compound and interrupted compound SSRs. These characterizations were obtained by statistical analysis from the MISA files [21] by a small Perl program and plotted by R language [22], and OpenOffice.org Calc.

    Primer pairs designing

    Primer pairs were designed by Primer 3.0 interface modules containing p3_in.pl Primer 3.0 [23] and p3_out.pl files (http://pgrc.ipk-gatersleben.de/misa/primer3.html). These Perl scripts were used to normalize the format in order to design primers flanking the microsatellite locus. Amplification product sizes ranged from 100 to 300 bp. Then, the in-house developed script primer_random_pick.pl was used to gain the non-redundant primers.

    Polymerase chain reactions (PCR) amplification

    For each of primer pair, PCRs were performed twice, each time with a different Taq enzyme and reaction buffer. All the primer pairs were amplified in the first round experiment with 20 μl reaction volumes containing 0.5 U of TaKaRa Taq polymerase (Code No.: R001A, TaKaRa, Dalian, China), 2 μl of 10 × PCR Buffer (Mg2+ plus), 0.2 μl of dNTP (2.5 mM each), 0.4 μM primer, and 50 ng of genomic DNA. Then the no bands or weak bands primers were used in the second round PCR reaction using TAKaRa LA Taq polymerase with GC buffer (Code No.: RR02AG, TaKaRa, Dalian, China) according to the manufacturer’s instructions. SSRs were amplified on Heijingang Thermal Cycler (Eastwin, Beijing, China). Under the following conditions: 5 min initial denaturation at 95°C; 35 cycles of 30 s at 95°C, 30 s at the optimized annealing temperature (Table 1), 45 s of elongation at 72°C, and a final extension at 72°C for 10 min. PCR products were tested for polymorphism using 6% denaturing polyacrylamide gels and visualized by silver nitrate staining.
    Table 1

    Characteristics of 74 polymorphic microsatellite loci developed in grasspea (FP = forward primer, RP = reverse primer, Ta = annealing temperature)

    Primer

    Repeat motif

    Primer sequence (5′-3′)

    Real product size(bp)

    Ta/°C

    G1

    (A)10

    FP-AAGGAGCAGCAGCATTTGTT

    210-240

    52

    RP-TAATAATGGGGAGCCGATCA

    G4

    (AAAG)5

    FP- CCTTTCGGAGCAATCAAGAC

    110-120

    56

    RP- TGCCTAAGCATTGGCTTTCT

    G5

    (AAC)10

    FP- CACAACCAGTTGCATCAGTG

    200-220

    56

    RP- TGGCTCACATGATGGTTTGT

    G6

    (AAC)12

    FP- TGGAGGACGAGCAACAATAA

    230-250

    54

    RP- TGTTGTTGATGGAAACAAATGA

    G7

    (AAC)5

    FP- ACAGCAAGAAGCAGCAACAG

    230-245

    56

    RP- AGTTGGTTGTTGTGTCGTTGT

    G9

    (AAC)6

    FP- CAACCAGAGCAACCACAAGA

    240-260

    56

    RP- GGTTGCAAGAGGTTGCAGAT

    G13

    (AACCA)5

    FP-CAAACCAAACCAAACCAAACT

    180-195

    52

    RP- CGCGTTTTGGTTTTCGTACT

    G15

    (AAG)6

    FP- TCAAGCCCAAAGTGAGATGA

    145-155

    56

    RP- TTTTGTGTTGCTTGCTGACC

    G17

    (AAT)5

    FP- CAGGTCCGGCTTATCTCTCA

    180-200

    56

    RP- TTGGTTTCAACCCACTCCTC

    G18

    (AC)10

    FP- ACACGACACACACGACAGTG

    130-140

    52

    RP- CTGCGTGTCTGTGCCTATTG

    G27

    (AC)18

    FP- ATCTTACCGGGGATCCATTC

    190-210

    56

    RP- CTTCCCCATTCTCTGGTGTT

    G33

    (AC)6

    FP- ACCAAAGGATGCAGGGTCTA

    230-270

    54

    RP- TAGTCGTGGTGTCGTGGTGT

    G39

    (AC)6

    FP- CCAGACACACACGCAAACAT

    170-190

    54

    RP- GTGTGTGACGTTGCCGTTAG

    G49

    (AC)7

    FP-ACGCACACACGGAAGAAAG

    160-180

    56

    RP-GTGTGCGCATGTGTGTATGA

    G61

    (AC)8

    FP-CACACACCATTACGCACACA

    130-150

    54

    RP-TGGTGTCGTGGTCGTAGGTA

    G64

    (AC)8

    FP-GCACATTCGCACGTATTCAC

    160-180

    56

    RP-CGTTTCTGAGTGCGTTGTGT

    G67

    (AC)9

    FP-CACCCTCTTCACTGCCTAGC

    120-150

    52

    RP-TTGGGGGTTGTAGAAGGAAC

    G68

    (AC)9

    FP-GCACACAAGGGCACACTG

    170-180

    52

    RP-TGCGTCGTGTGTATGTGTTG

    G72

    (ACA)5

    FP-CAACGACAACAACGCAAAAC

    260-280

    52

    RP-TTCGCGGTTTGTCCATTTAG

    G73

    (ACA)5

    FP-CCAACTCTCAGCCACGAACT

    200-220

    54

    RP-TTGCTCCACCTACGCTTCTT

    G75

    (ACA)6

    FP-AACAACAGCAGCAACAACAAT

    200-215

    54

    RP-CGTGTTGTGTGTTCGTTCGTA

    G76

    (ACA)6

    FP-CACAACCAACGCCAATACAG

    230-250

    54

    RP-CCGTAGTACCGCGCTTATTC

    G77

    (AAC)11

    FP-ACAAGACAACATCACCGAGAC

    300-330

    52

    RP-TGTTGTTTGGTTGTTCGTGTA

    G80

    (AAC)5

    FP-AAACACAACAGACGATTAAACACA

    185-200

    52

    RP-TCTTGCTATGTAGTGTTGTGTGATG

    G81

    (ACG)5

    FP-CGCACACACTCACACACAAC

    180-200

    52

    RP-GGTCCTGTCGTCGTAGTCCT

    G83

    (ACG)7

    FP-GGGCACACATTCTCACACAC

    190-200

    54

    RP-TGTCGTCGTGTCGTAGTCGT

    G87

    (AG)15

    FP-CCCTTACCGAGTGCAGAAAA

    230-250

    54

    RP-CACCACGACTTGCTCACCTA

    G101

    (CA)11c(CA)7

    FP-TGGCAGGTAACTGGTGAGTG

    180-190

    52

    RP-GGTGTTTCCCCACCTCTCTA

    G102

    (CA)12

    FP-AAAGCACAGCACAACACGAC

    260-280

    54

    RP-AACAAGGACGACGGTAGGTG

    G110

    (CA)6

    FP-CACAAACACGCACAAACACA

    150-170

    52

     

    RP-CGTCGGTATAACCGTGTCGT

    G116

    (CA)6(CACACG)5

    FP-CACACAGGACAGCACTCACA

    150-180

    52

    RP-GTCGTCGGTGTGTCGTAGTC

    G119

    (CA)6cgacacacncgcgcgcgcgacacac(ACG)8

    FP-CGTCTCTTCAAAGGGCCATA

    190-200

    52

    RP-CGACCGACCGACGTACTACT

    G120

    (CA)6cgcacgcacgcacacagacacg(CA)7

    FP-GCGCACGCATACATACACA

    160-170

    54

    RP-TTGCCGTTGTCGTGTTAGTG

    G123

    (CA)6gn(AC)6

    FP-CATAACAACACGCAGCATTACC

    130-140

    52

    RP-TTGCGTTGTTGTGTTGTGTTT

    G128

    (CA)7

    FP-CCACACACCCACATGTTCA

    210-230

    56

    RP-TTGTGGTGGGTCTGAGAGTG

    G131

    (CA)7aacacgttcg(CA)8

    FP-GCGCTCACACCAACATAAAG

    140-150

    54

    RP-TGTATGCGTGCGTATGTCTG

    G133

    (CA)7cgcacat(AC)6

    FP-ACGCGTGCACACATTTTATC

    200-220

    52

    RP-TATGTGGGCGCGTGTAAGTA

    G136

    (CA)7tacacacacat(AC)7aa(AC)6

    FP-ACGACGACCACCAGTACGA

    110-130

    54

    RP-ACGAGTGCGTGTGTGAGTGT

    G142

    (CA)8cgcacaa(AC)10

    FP-CGTGCACGCACAGATACG

    160-180

    52

    RP-GTGTGTGTGTTCGTCGTTTG

    G143

    (CA)8cggcgcgcg(AC)9

    FP-GACACACACAACCCGAACAC

    230-260

    52

    RP-TGAGCGAACGTACGTGGTAG

    G145

    (CA)8tacgcacg(CA)10

    FP-ATACAAGCACGCATCCACAG

    100-120

    52

    RP-AGTTCGTGTCGTGTCGTGTC

    G147

    (CA)9

    FP-CGTCACACACGTCACGTACA

    210-230

    54

    RP-CTACGAGACGCACGACGATA

    G150

    (CA)9 g(AC)25

    FP-CACACACACCAAGCGTTACA

    140-160

    54

    RP-TCGTGTGTGTCGTGTGTGTAG

    G151

    (CAA)10

    FP-CAACAACGACAACAAAATTGTAA

    175-185

    52

    RP-CTGCTGATGTTGTTGGTGCT

    G154

    (CAA)5agaccacaacaccaccacc aacaacaacaataataaaacag(AAC)5

    FP-CTGGCGTAATAGCGAAGAGG

    240-260

    56

    RP-TGTGTTGCTTTGTGTTGTCGT

    G157

    (CAA)6

    FP-ACATCCAATCCCCACCATAA

    210-230

    56

    RP-AATGCATGGTTGTTGCTTGA

    G165

    (CGA)5

    FP-GAACGTACGACGACACGAACT

    270-290

    54

    RP-CGTGTGGTGTGTGTGTGTGT

    G171

    (CT)9

    FP-CTTCACTGCATGCTTTCCAC

    200-230

    52

    RP-CTGGGGTGGTTTTTGTCAGT

    G174

    (GA)19

    FP-CACAAGGGTCAAGGGAGAGA

    140-160

    52

    RP-GTTTACGTTACTTATTCGTTCGTTAG

    G184

    (GT)15

    FP-GCGTGTGTGCGAATGTGT

    180-190

    52

    RP-CACGCACGCACACTAGACTAC

    G185

    (GT)19

    FP-TGCGTGTGTCGCTCTATCAT

    130-135

    56

    RP-TACTGCGACAACCGAACGTA

    G188

    (GT)6

    FP-GCGCGTTAGTGTGTGTTTGA

    140-150

    52

    RP-CACGCACGCACACTTACATA

    G191

    (GT)6

    FP-TGTGCGTGGTGTTTGAGTG

    140-160

    52

    RP-CACATACGCACAGCCCATAC

    G192

    (GT)6a(TG)7

    FP-TGCGTGATAAGGTGCTTGAG

    160-170

    56

    RP-ACACACACACGCACACACAC

    G200

    (GT)7

    FP-GGATGGTGTGCTGTGTGTGT

    120-135

    52

    RP-AACACCAACTACCGGCAACT

    G205

    (GT)7gcgtgtgcctgcgtctctgcgagtgcgtgc(GT)6

    FP-TGTCTGGTGTGTGTGGTGTG

    230-250

    52

    RP-CGACACGTACGCAACGAC

    G206

    (GT)8

    FP-AAACTGGCCCTGCATTTTC

    190-210

    52

    RP-GGTCATGGCAATTTGAGACA

    G209

    (GT)8

    FP-TTTGCACGTGTCCTGTGTTT

    240-260

    52

    RP-ACGACGACCACACACCACTA

    G211

    (GT)9

    FP-ATGGCGTCGTATGTGTGTGT

    200-210

    52

    RP-GTTACGGCCGAATCAACAAC

    G219

    (GTT)10

    FP-CCAGTTGTGCCGAACACAT

    130-160

    52

    RP-CCAACAGCAGATTGCCAGTA

    G225

    (GTT)7

    FP-GGGCAGTGGACCAGTTAGAG

    250-270

    52

    RP-CCGAGGGAATAAACGACAAA

    G228

    (T)10

    FP-CCTACGGACATGCCTGTTTT

    280-310

    52

    RP-GCGGTAGGGGAAAAACAACT

    G233

    (TC)20

    FP-CGTTCGTCCTTCTCCTCCTA

    120-140

    52

    RP-AGACGACTACGGACGACGAC

    G234

    (TC)7

    FP-GTTGGGTTTGGCATTGAACT

    190-210

    52

    RP-GAAGGGGCGAACAAATAAAA

    G244

    (TG)6

    FP-CAATCCGAAAATCACCACCT

    230-250

    52

    RP-GCACTCACATGCACACAAAC

    G245

    (TG)6

    FP-CGTTGGTTGTTAGTCGGTCA

    240-260

    52

    RP-GAACGAAACAACGACGACAA

    G249

    (TG)6c(GT)7

    FP-TATGTGTGCAACGGCAACTT

    140-160

    52

    RP-GCACACCCACCACACAATAG

    G254

    (TG)7

    FP-TGAGTGCGTACGTGTGTCTG

    100-120

    52

    RP-GCGCGTGTTCACACATAGAC

    G262

    (TGGT)5

    FP-TGTGCGTGTGTGTGTTTTTG

    300-320

    52

    RP-ACCACAACCCCTACCCTACC

    G268

    (TGT)5tattn(TTG)6

    FP-TTGTTTGTTGTTGTTGTGTCTTG

    290-305

    52

    RP-CTACAGTACAGACCCGCCACT

    G269

    (TGT)6

    FP-ATGCTGTTGATGCGTCAGTT

    220-240

    52

    RP-TGCAGCAACAACAAATAAGACA

    G273

    (TGT)7

    FP- TTTTTGGTATTGTTGTTGTCGT

    250-270

    52

    RP- CTGCAGCAATAACAGCATCAG

    G284

    (TTG)6

    FP-TGTGTTGTGTTGTGCTGTATGTA

    160-170

    52

    RP-GCAGCAACATTAAAACGAACAG

    G285

    (TTG)6

    FP-TTTGTGCGGTTGATGTTGTT

    190-200

    52

    RP-CTACGTCAGCCCGTCATACC

    Evaluation of polymorphic primers in different accessions

    288 SSR markers were randomly selected for validation feasibility and size polymorphism among 23 grasspea (L. sativus) genotypes from diverse geographical locations and one red pea (L. cicera) genotype. POPGEN1.32 [24] software was used to calculate the observed number of alleles (Na), the level of observed heterozygosity (Ho) and the Shannon’s information index (I).

    Genetic diversity analysis

    Cluster analysis was conducted based on Nei’s [25] unbiased genetic distance, by using POPGEN1.32 [24] software with the unweighted pair group method on arithmetic averages (UPGMA) algorithm. The resulting clusters were expressed as a dendrogram drawn by MEGA4 [26].

    Results

    Quality control during library construction

    The quality of SSR enriched grasspea library was inspected by sequencing 186 randomly selected clones. The resulting data verified that, the recombination rate was 95%, and 29 sequences contained 89 SSR motifs within the cloned sequences.

    454 sequencing and characterization reads

    A total of 493,364 reads were generated from the Roche 454 GS FLX Titanium platform. After adaptor removing, 370,079 read sequences were used for further analysis. The most common nucleotide was thymidine, according for 27.7% of total nucleotides, followed by adenosine (27.2%), guanine (22.2%) and cytosine (22.1%). The mean GC content was 44.3%. The average length of read sequence was 453 bp, with a maximum length of 1,162 bp (Figure 1).
    Figure 1
    Figure 1

    Size distribution of 454 reads.

    Mining for SSRs (simple sequence repeats)

    Firstly, we employed the program CD-HIT (http://weizhong-lab.ucsd.edu/cd-hit/) to produce a set of 280,791 non-redundant representative sequences. Then, Microsatellite identification tool (MISA) (http://pgrc.ipk-gatersleben.de/misa/) was used for microsatellite mining. As a result, 651,827 SSRs were identified in 129,886 read sequences. Among them, 115,172 read sequences contained more than one SSR. The number of SSRs presenting in compound formation was 464,271 (Table 2), which meant high proportion of SSR loci (71.2%) was located within compound repeats. The majority of identified SSRs (65.4%) were located within 200 bp from the 5′-terminus, and few of SSRs fell into the 3′-terminus (Figure 2).
    Table 2

    MISA result in the genome survey

    Category

    Numbers

    Total number of sequences examined

    280,791

    Total size of examined sequences (bp)

    130,484,900

    Total number of identified SSRs

    651,827

    Number of SSR containing sequences

    129,886

    Number of sequences containing more than one SSRs

    115,172

    Number of SSRs present in compound formation

    464,271

    Figure 2
    Figure 2

    Distribution of SSR motif start position.

    SSR motifs characterizing

    The identified SSRs included 995 (0.2%) mononucleotide repeat motifs, 385,385 (59.1%) dinucleotide repeat motifs, 238,752 (36.6%) trinucleotide repeat motifs, 21,200 (3.3%) tetranucleotide repeat motifs, 2,911 (0.4%) pentanucleotide repeat motifs, and 2,584 (0.4%) hexanucleotide repeat motifs (Figure 3). Thus over 95% of the motifs were di- and tri-nucleotides. The most abundant repeat motif type was (AC/GT)n, followed by (AAC/GTT)n, (AG/CT)n, (ACG/CTG)n and (ACGT/ATGC)n, respectively (Additional file 2: Figure S1, Additional file 3: Figure S2, Additional file 4: Figure S3, Additional file 5: Figure S4, Additional file 6: Figure S5, Additional file 7: FigureS6).
    Figure 3
    Figure 3

    A pie-chart of different SSR motifs in the grasspea sequence data obtained by the current project.

    Compound SSR analysis

    In our study, perfect SSRs (i.e., (CA)8 which were named as P2 type) were relatively less frequent (29.4%) than the compound SSRs (70.6%). In addition, there were two kinds of compound SSRs: those with interruption between two motifs (i.e., (CT)8cacacg(CA)9 which were named as C type); and those without interruption between two motifs (i.e., (GT)6(GTC)6 which were named as C* type). There were 123,444C type (93.2%) and 8,989C* type (6.8%) compound SSRs detected, which suggested the complexity of the grasspea genome.

    Primer pairs designing

    A total of 62,342 primer pairs flanking the SSRs were successfully designed using the public shareware Primer 3.0 (http://www-genome.wi.mit.edu/genome_software/other/primer3.html.), based on criteria of melting temperature, GC content and the lack of secondary structure. Furthermore, 50,144 non-redundant primers were achieved by in house developed programs (Additional file 8: Table S2).

    Validation of SSR markers

    To validate the SSR sequences, 288 SSR primer pairs were randomly selected for PCR amplification for size polymorphism among 23 grasspea (L. sativus) genotypes from diverse geographical locations and one red pea (L. cicera) genotype. After two rounds of PCR amplifications, 74 primer pairs were confirmed of being able to amplify polymorphic based across the 24 genotypes (Table 1), 70 primer pairs were confirmed to amplify only monomorphic fragments, and 144 primer pairs produced no products. The number of observed alleles (Na) ranged from two to five, the observed heterozygosity (Ho) from 0 to 0.9545, and Shannon’s information index (I) ranged from 0.1013 to 1.0980 (Table 3). These results indicate the broad utility of the SSR markers obtained from next-generation sequencing for future studies of grasspea genetics.
    Table 3

    Results of initial primer screening through 24 diversified accessions in Lathyrus

    Primer pair ID

       
     

    Na 1

    Ho 2

    I 3

    G1

    3

    0.4211

    0.8258

    G4

    2

    0.0000

    0.1914

    G5

    2

    0.2381

    0.5196

    G6

    2

    0.5000

    0.5623

    G7

    2

    0.0000

    0.1849

    G9

    3

    0.8750

    0.7691

    G13

    2

    0.1176

    0.5456

    G15

    2

    0.0714

    0.1541

    G17

    2

    0.2000

    0.3251

    G18

    4

    0.1500

    0.5086

    G27

    4

    0.0870

    0.7216

    G33

    3

    0.5556

    0.7086

    G39

    3

    0.3846

    0.7436

    G49

    5

    0.9545

    1.0691

    G61

    4

    0.7143

    0.9592

    G64

    3

    0.1429

    1.0346

    G67

    5

    0.6250

    1.0782

    G68

    2

    0.9091

    0.6890

    G72

    2

    0.0000

    0.2146

    G73

    3

    0.0667

    0.7689

    G75

    2

    0.3478

    0.4620

    G76

    4

    0.5714

    1.0980

    G77

    3

    0.4737

    0.8011

    G80

    2

    0.0000

    0.1849

    G81

    4

    0.6818

    0.9351

    G83

    2

    0.0000

    0.2712

    G87

    3

    0.1111

    0.4258

    G101

    3

    0.1500

    0.3141

    G102

    2

    0.0000

    0.3768

    G110

    2

    0.5500

    0.6819

    G116

    3

    0.0000

    0.4634

    G119

    2

    0.0526

    0.2762

    G120

    2

    0.0556

    0.1269

    G123

    3

    0.0435

    0.2090

    G128

    2

    0.2500

    0.6919

    G131

    3

    0.2609

    0.4776

    G133

    3

    0.6190

    0.7920

    G136

    2

    0.6667

    0.6365

    G142

    2

    0.6000

    0.6730

    G143

    2

    0.6667

    0.6365

    G145

    2

    0.6154

    0.6172

    G147

    3

    0.3571

    0.7401

    G150

    2

    0.4286

    0.5196

    G151

    2

    0.3000

    0.4227

    G154

    4

    0.5000

    1.0251

    G157

    2

    0.3889

    0.6792

    G165

    2

    0.8095

    0.6749

    G171

    3

    0.0000

    0.4634

    G174

    2

    0.1667

    0.4029

    G184

    2

    0.0000

    0.3622

    G185

    2

    0.0417

    0.1013

    G188

    3

    0.0667

    0.5627

    G191

    2

    0.2500

    0.6616

    G192

    2

    0.8667

    0.6931

    G200

    4

    0.9000

    0.9386

    G205

    2

    0.0000

    0.6172

    G206

    2

    0.0000

    0.2868

    G209

    2

    0.5000

    0.5623

    G211

    2

    0.0000

    0.3768

    G219

    3

    0.7500

    0.9881

    G225

    2

    0.4348

    0.5236

    G228

    2

    0.1176

    0.3622

    G233

    3

    0.2000

    0.5627

    G234

    2

    0.1250

    0.4826

    G244

    3

    0.9167

    0.9222

    G245

    2

    0.3500

    0.4637

    G249

    2

    0.5294

    0.5779

    G254

    3

    0.0909

    0.3558

    G262

    2

    0.0000

    0.4506

    G268

    2

    0.0000

    0.1732

    G269

    2

    0.0000

    0.6365

    G273

    2

    0.0000

    0.1732

    G284

    2

    0.0000

    0.2237

    G285

    2

    0.1739

    0.2954

    1The number of observed alleles.

    2Estimated proportion of observed heterozygosity under random mating using Nei’s (1978) unbiased heterozygosity.

    3Shannon's Information index (Lewontin, 1972).

    Genetic diversity study

    To assess the efficiency of microsatellites for differentiation of L. sativus from other Lathyrus species, we chose one L. cicera accession (ELS 0246, Syria) as outgroup in the genetic diversity study. Cluster analysis based on Nei’s [25] genetic distance indicated good separation between L. sativus and L. cicera. Furthermore, the UPGMA procedure grouped most Chinese accessions into one cluster; come from the center of origin, Mediterranean accessions discovered the major genetic diversity in cultivated grasspea species as they spread allover, except Chinese cluster (Figure 4). These results absolutely validated the accuracy and effectiveness of our approach for developing SSR markers in grasspea with the NGS technology.
    Figure 4
    Figure 4

    UPGMA dendrogram of 24 germplasm resources.

    Discussion

    Grasspea as a potential vital crop in arid areas

    Frequent drought and water shortage are worldwide problems, especially for agricultural production. Dryland agriculture plays an important role in national economy and food security. For example, in China, 55% of the total arable land, and 43% of the total food supplies are related to dryland agriculture. Grasspea is popular among the resource poor farmers in marginal areas due to the ease with which it can be grown successfully under adverse agro-climatic conditions without much production inputs. Presently at global scale, it is grown on 1.5 million ha area with 1.2 million tonnes production [2]. In recent years, efforts are underway in many countries including China, Australia, Spain, Italy, and Canada to expand its cultivation as a break crop between cereals and as a bonus crop in fallow land because of its ability to fix large amount of atmospheric nitrogen in association with Rhizobium bacteria [7]. However, the presence of a neurotoxin, β-N-Oxalyl-L-α,β-diaminopropionic acid (β-ODAP), renders this crop neglected and underutilized. Despite the undesirable features such as high neurotoxin, grasspea has potential as an important crop in western China and other arid areas in the world.

    Mining genomic SSR loci using 454 pyrosequencing technology

    The traditional methods of microsatellite development used a library-based approach for targeted SSR repeat motifs, which was time consuming, expensive, with low-throughput. Hunting in silico for EST-SSRs from public database method is an alternative way, which was cost effective and easy to access. However, the total number of ESTs from grasspea and related species was very limited since grasspea has received less attention for molecular studies.

    The identification of SSRs from genomic DNA using the 454 pyrosequencing technology was relatively new and two strategies were published. These were shotgun sequencing [1618] and SSR-enriched sequencing [15, 19]. In the present study, we used SSR-enriched sequencing technology and generated 370,079 high quality grasspea genomic reads, with an average length of 453 bp. Theoretically, the longer reads would increase our chances of successfully designing primer pairs while making it possible to identify long SSR repeats comparable to the size obtained using traditional library-based approach [18, 27]. According to the MISA analysis, 651,827 SSRs were identified from 129,886 reads. This was a very positive result, as the high ratio of SSR-containing reads and the large number of putative SSRs we obtained. Among them, di- and tri-nucleotide repeat motifs dominated the grasspea genomic sequences, similar to findings in other crops [28]. (AC/GT)n was not only the predominant di-nucleotide repeat motif, but also the most frequent motif in the entire genome, accounting for 55.2% of the total SSRs, followed by (AAC/GTT)n, (AG/CT)n, (ACG/CTG)n, while, (AT/TA)n, (CG/GC)n, (CCG/CGG)n were rarely detected in this study. The pattern was moderately similar to that previously observed in faba bean [15]. Furthermore, isolated and identified low proportion of unwanted repeat motifs such as (AT/TA)n, (CG/GC)n, (CCG/CGG)n would enhance the success ratio in designing primers.

    Utilization of new SSR resources for ‘orphan crop’ grasspea research

    Conventional breeding and phenotype research achieved great progress in improving agricultural crops in the last few years. However, grasspea was left as ‘orphan crop’ due to the lack of available genetic and genomic resources [29]. The use of SSR markers as a conventional tool has played an important role in the study of genetic diversity, genetic linkage map, QTL mapping and association mapping, and paved the way to the integration of genomics for crop breeding.

    Due to the scarcity of user-friendly, highly polymorphic molecular markers in grasspea and other Lathyrus species, high-density genetic maps were not available. In the present study, we validated 288 non-redundant SSR primer pairs and 144 (50.0%) SSR primer pairs produced amplified bands, with 74 being polymorphic, and 70 monomorphic. This very large set of potential genomic-SSR markers will facilitate the construction of high-resolution maps for positional cloning and QTL mapping.

    The genus Lathyrus L. (Fabaceae) is consisted of about 160 species [30] distributed throughout the temperate regions of the northern hemisphere and extends into tropical East Africa and South America [31, 32]. This study, we used 74 new SSR primer pairs to clearly separate the 23 L. sativus accessions from one L. cicera accession, which is in agreement with the reported phylogenic studies of Lathyrus L. (Fabaceae) based on morphological and molecular markers [7, 31].

    Conclusion

    This study provides an extensive characterization of the SSRs in grasspea genome. For the first time, large-scale SSR-enriched sequence data was generated for the identification of SSRs and development of SSR markers to accelerate basic and applied genomics research in grasspea.

    Notes

    Declarations

    Acknowledgements

    We acknowledge the financial support from the Ministry of Agriculture of China, under the China Agriculture Research System (CARS-09) Program, the international cooperation projects (2010DFR30620 and 2010DFB33340), national research program (2013BAD01B03) from the Ministry of Science and Technology of China and also supported by The Agricultural Science and Technology Innovation Program (ASTIP) in CAAS. We are grateful to Dr. Dahai Wang, Liping Sun and Dr. Qi Liu (Beijing Autolab Biotechnology Co., Ltd) for their special contribution to this work. We also thank Dr. Xianfu Yin (Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences & Shanghai Jiao Tong University School of Medicine) for his SeqTools.pl script.

    Authors’ Affiliations

    (1)
    The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
    (2)
    Department of Leguminous Crops Genetic Resources, N. I. Vavilov Research Institute of Plant Industry, St. Petersburg, 190000, Russia
    (3)
    USDA-ARS Western Regional Plant Introduction Station (WRPIS), Pullman, WA 99164, USA
    (4)
    International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, 5466, Syria
    (5)
    Australian Temperate Field Crops Collection, Grains Innovation Park, The Department of Primary Industries, Private Bag 260, Horsham, Victoria, 3401, Australia
    (6)
    The Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau of Ministry of Agriculture/Institute of Crop Germplasm Resources, Shanxi Academy of Agricultural Sciences, Taiyuan, 030031, China

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    © Yang et al.; licensee BioMed Central Ltd. 2014

    This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

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