Chickpea (Cicer arietinum L.) is an important legume crop in the semi-arid regions of Asia and Africa. Gains in crop productivity have been low however, particularly because of biotic and abiotic stresses. To help enhance crop productivity using molecular breeding techniques, next generation sequencing technologies such as Roche/454 and Illumina/Solexa were used to determine the sequence of most gene transcripts and to identify drought-responsive genes and gene-based molecular markers. A total of 103 215 tentative unique sequences (TUSs) have been produced from 435 018 Roche/454 reads and 21 491 Sanger expressed sequence tags (ESTs). Putative functions were determined for 49 437 (47.8%) of the TUSs, and gene ontology assignments were determined for 20 634 (41.7%) of the TUSs. Comparison of the chickpea TUSs with the Medicago truncatula genome assembly (Mt 3.5.1 build) resulted in 42 141 aligned TUSs with putative gene structures (including 39 281 predicted intron/splice junctions). Alignment of ∼37 million Illumina/Solexa tags generated from drought-challenged root tissues of two chickpea genotypes against the TUSs identified 44 639 differentially expressed TUSs. The TUSs were also used to identify a diverse set of markers, including 728 simple sequence repeats (SSRs), 495 single nucleotide polymorphisms (SNPs), 387 conserved orthologous sequence (COS) markers, and 2088 intron-spanning region (ISR) markers. This resource will be useful for basic and applied research for genome analysis and crop improvement in chickpea.

A set of 2486 single nucleotide polymorphisms (SNPs) were compiled in chickpea using four approaches, namely (i) Solexa/Illumina sequencing (1409), (ii) amplicon sequencing of tentative orthologous genes (TOGs) (604), (iii) mining of expressed sequence tags (ESTs) (286) and (iv) sequencing of candidate genes (187). Conversion of these SNPs to the cost-effective and flexible throughput Competitive Allele Specific PCR (KASPar) assays generated successful assays for 2005 SNPs. These marker assays have been designated as Chickpea KASPar Assay Markers (CKAMs). Screening of 70 genotypes including 58 diverse chickpea accessions and 12 BC3F2 lines showed 1341 CKAMs as being polymorphic. Genetic analysis of these data clustered chickpea accessions based on geographical origin. Genotyping data generated for 671 CKAMs on the reference mapping population (Cicer arietinum ICC 4958 × Cicer reticulatum PI 489777) were compiled with 317 unpublished TOG-SNPs and 396 published markers for developing the genetic map. As a result, a second-generation genetic map comprising 1328 marker loci including novel 625 CKAMs, 314 TOG-SNPs and 389 published marker loci with an average inter-marker distance of 0.59 cM was constructed. Detailed analyses of 1064 mapped loci of this second-generation chickpea genetic map showed a higher degree of synteny with genome of Medicago truncatula, followed by Glycine max, Lotus japonicus and least with Vigna unguiculata. Development of these cost-effective CKAMs for SNP genotyping will be useful not only for genetics research and breeding applications in chickpea, but also for utilizing genome information from other sequenced or model legumes.

BackgroundChickpea (Cicer arietinum L.), an important grain legume crop of the world is seriously challenged by terminal drought and salinity stresses. However, very limited number of molecular markers and candidate genes are available for undertaking molecular breeding in chickpea to tackle these stresses. This study reports generation and analysis of comprehensive resource of drought- and salinity-responsive expressed sequence tags (ESTs) and gene-based markers.ResultsA total of 20,162 (18,435 high quality) drought- and salinity- responsive ESTs were generated from ten different root tissue cDNA libraries of chickpea. Sequence editing, clustering and assembly analysis resulted in 6,404 unigenes (1,590 contigs and 4,814 singletons). Functional annotation of unigenes based on BLASTX analysis showed that 46.3% (2,965) had significant similarity (≤1E-05) to sequences in the non-redundant UniProt database. BLASTN analysis of unique sequences with ESTs of four legume species (Medicago, Lotus, soybean and groundnut) and three model plant species (rice, Arabidopsis and poplar) provided insights on conserved genes across legumes as well as novel transcripts for chickpea. Of 2,965 (46.3%) significant unigenes, only 2,071 (32.3%) unigenes could be functionally categorised according to Gene Ontology (GO) descriptions. A total of 2,029 sequences containing 3,728 simple sequence repeats (SSRs) were identified and 177 new EST-SSR markers were developed. Experimental validation of a set of 77 SSR markers on 24 genotypes revealed 230 alleles with an average of 4.6 alleles per marker and average polymorphism information content (PIC) value of 0.43. Besides SSR markers, 21,405 high confidence single nucleotide polymorphisms (SNPs) in 742 contigs (with ≥ 5 ESTs) were also identified. Recognition sites for restriction enzymes were identified for 7,884 SNPs in 240 contigs. Hierarchical clustering of 105 selected contigs provided clues about stress- responsive candidate genes and their expression profile showed predominance in specific stress-challenged libraries.ConclusionGenerated set of chickpea ESTs serves as a resource of high quality transcripts for gene discovery and development of functional markers associated with abiotic stress tolerance that will be helpful to facilitate chickpea breeding. Mapping of gene-based markers in chickpea will also add more anchoring points to align genomes of chickpea and other legume species.

A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2–20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-011-1556-1) contains supplementary material, which is available to authorized users.

BackgroundPigeonpea (Cajanus cajan (L.) Millsp) is one of the major grain legume crops of the tropics and subtropics, but biotic stresses [Fusarium wilt (FW), sterility mosaic disease (SMD), etc.] are serious challenges for sustainable crop production. Modern genomic tools such as molecular markers and candidate genes associated with resistance to these stresses offer the possibility of facilitating pigeonpea breeding for improving biotic stress resistance. Availability of limited genomic resources, however, is a serious bottleneck to undertake molecular breeding in pigeonpea to develop superior genotypes with enhanced resistance to above mentioned biotic stresses. With an objective of enhancing genomic resources in pigeonpea, this study reports generation and analysis of comprehensive resource of FW- and SMD- responsive expressed sequence tags (ESTs).ResultsA total of 16 cDNA libraries were constructed from four pigeonpea genotypes that are resistant and susceptible to FW ('ICPL 20102' and 'ICP 2376') and SMD ('ICP 7035' and 'TTB 7') and a total of 9,888 (9,468 high quality) ESTs were generated and deposited in dbEST of GenBank under accession numbers GR463974 to GR473857 and GR958228 to GR958231. Clustering and assembly analyses of these ESTs resulted into 4,557 unique sequences (unigenes) including 697 contigs and 3,860 singletons. BLASTN analysis of 4,557 unigenes showed a significant identity with ESTs of different legumes (23.2-60.3%), rice (28.3%), Arabidopsis (33.7%) and poplar (35.4%). As expected, pigeonpea ESTs are more closely related to soybean (60.3%) and cowpea ESTs (43.6%) than other plant ESTs. Similarly, BLASTX similarity results showed that only 1,603 (35.1%) out of 4,557 total unigenes correspond to known proteins in the UniProt database (≤ 1E-08). Functional categorization of the annotated unigenes sequences showed that 153 (3.3%) genes were assigned to cellular component category, 132 (2.8%) to biological process, and 132 (2.8%) in molecular function. Further, 19 genes were identified differentially expressed between FW- responsive genotypes and 20 between SMD- responsive genotypes. Generated ESTs were compiled together with 908 ESTs available in public domain, at the time of analysis, and a set of 5,085 unigenes were defined that were used for identification of molecular markers in pigeonpea. For instance, 3,583 simple sequence repeat (SSR) motifs were identified in 1,365 unigenes and 383 primer pairs were designed. Assessment of a set of 84 primer pairs on 40 elite pigeonpea lines showed polymorphism with 15 (28.8%) markers with an average of four alleles per marker and an average polymorphic information content (PIC) value of 0.40. Similarly, in silico mining of 133 contigs with ≥ 5 sequences detected 102 single nucleotide polymorphisms (SNPs) in 37 contigs. As an example, a set of 10 contigs were used for confirming in silico predicted SNPs in a set of four genotypes using wet lab experiments. Occurrence of SNPs were confirmed for all the 6 contigs for which scorable and sequenceable amp...

Molecular markers have proven to be useful tools for genetics and molecular breeding of crop plants, starting with low-throughput RFLPs (restriction fragment length polymorphisms) in 1980 and culminating in ultra high-throughput SNPs at present. Molecular marker technology has continuously evolved from hybridization-based RFLPs to PCR-based RAPDs, AFLPs, and SSRs, and finally high-throughput SNPs. More recently, ultra high-throughput genotyping by sequencing (GBS) has been established. Among these molecular markers, SSRs were considered the markers of choice for several plant breeding applications because of their various desirable attributes, and are still considered inexpensive for simply inherited traits. However, more recently, SNP markers have become markers of choice due to their abundance, uniform distribution throughout genomes and high resolution as well as their amenability to high-throughput approaches. With the advent of next-generation sequencing (NGS) technologies, new sequencing tools have been found to be valuable for the discovery, validation, and application of genetic markers. These ultra high-throughput markers will not only prove useful for preparation of high-density genetic maps and identification of QTLs for their deployment in plant breeding but will also facilitate genome-wide selection (GWS) and genome-wide association studies (GWAS).

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