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Only a few genetic maps based on recombinant inbred line (RIL) and backcross (BC) populations have been developed for tetraploid groundnut. The marker density, however, is not very satisfactory especially in the context of large genome size (2800 Mb/1C) and 20 linkage groups (LGs). Therefore, using marker segregation data for 10 RILs and one BC population from the international groundnut community, with the help of common markers across different populations, a reference consensus genetic map has been developed. This map is comprised of 897 marker loci including 895 simple sequence repeat (SSR) and 2 cleaved amplified polymorphic sequence (CAPS) loci distributed on 20 LGs (a01–a10 and b01–b10) spanning a map distance of 3, 863.6 cM with an average map density of 4.4 cM. The highest numbers of markers (70) were integrated on a01 and the least number of markers (21) on b09. The marker density, however, was lowest (6.4 cM) on a08 and highest (2.5 cM) on a01. The reference consensus map has been divided into 20 cM long 203 BINs. These BINs carry 1 (a10_02, a10_08 and a10_09) to 20 (a10_04) loci with an average of 4 marker loci per BIN. Although the polymorphism information content (PIC) value was available for 526 markers in 190 BINs, 36 and 111 BINs have at least one marker with >0.70 and >0.50 PIC values, respectively. This information will be useful for selecting highly informative and uniformly distributed markers for developing new genetic maps, background selection and diversity analysis. Most importantly, this reference consensus map will serve as a reliable reference for aligning new genetic and physical maps, performing QTL analysis in a multi-populations design, evaluating the genetic background effect on QTL expression, and serving other genetic and molecular breeding activities in groundnut.

Groundnut (Arachis hypogaea L.) is an important food and cash crop grown mainly in semi-arid tropics (SAT) regions of the world where drought is the major constraint on productivity. With the aim of understanding the genetic basis and identification of quantitative trait loci (QTL) for drought tolerance, two new recombinant inbred line (RIL) mapping populations, namely ICGS 76 × CSMG 84-1 (RIL-2) and ICGS 44 × ICGS 76 (RIL-3), were used. After screening of 3,215 simple sequence repeat (SSR) markers on the parental genotypes of these populations, two new genetic maps were developed with 119 (RIL-2) and 82 (RIL-3) SSR loci. Together with these maps and the reference map with 191 SSR loci based on TAG 24 × ICGV 86031 (RIL-1), a consensus map was constructed with 293 SSR loci distributed over 20 linkage groups, spanning 2,840.8 cM. As all these three populations segregate for drought-tolerance-related traits, a comprehensive QTL analysis identified 153 main effect QTL (M-QTL) and 25 epistatic QTL (E-QTL) for drought-tolerance-related traits. Localization of these QTL on the consensus map provided 16 genomic regions that contained 125 QTL. A few key genomic regions were selected on the basis of the QTL identified in each region, and their expected role in drought adaptation is also discussed. Given that no major QTL for drought adaptation were identified, novel breeding approaches such as marker-assisted recurrent selection (MARS) and genomic selection (GS) approaches are likely to be the preferred approaches for introgression of a larger number of QTL in order to breed drought-tolerant groundnut genotypes.

In recent years, Pongamia has been considered as important renewable source of biodiesel, however not much molecular information is available in this species. Molecular characterization of this legume tree will enhance our understanding in improving the optimal yields of oil through breeding and enable us to meet the future demands for biodiesel. To assess the molecular genetic diversity in 46 Pongamia pinnata accessions collected from six different states of India, amplified fragment length polymorphism (AFLP) marker system was employed. Five AFLP primer combinations produced 520 discernible fragments, of which 502 (96.5%) were polymorphic. AFLP primer informativeness was estimated evaluating four parameters namely polymorphism information content (PIC), effective multiplex ratio (EMR), marker index (MI) and resolving power (RP). In total, 51 unique fragments were detected of which 19 unique fragments were observed with primer combination E-ACG / M-CTA. Although neighbour joining (NJ) method did not group accessions strictly according to their region of collection, a good level of genetic diversity was observed in examined germplasm. However, accessions collected from Karnataka showed comparatively higher diversity than accessions from other states. The diverse accessions identified in this study may be useful in Pongamia pinnata improvement to meet the future demands of biodiesel.

A set of 22 pearl millet inbred lines including the parents of eleven mapping populations, was screened with 627 markers including 100 pearl millet genomic SSRs (gSSRs), 60 pearl millet EST-SSRs (eSSRs), 410 intron sequence haplotypes (ISHs), and 57 exon sequence haplotypes (ESHs). In all, 267 (59%) of the markers were informative for at least one of the 11 mapping populations, which segregate for traits like drought and salinity tolerance; host plant resistance to downy mildew, rust and blast; fertility restoration and sterility and maintenance of cytoplasmic male sterility etc. An average of 116 polymorphic markers was identified per mapping population. The average PIC values and number of profiles (P) per polymorphic marker were: gSSRs (PIC = 0.62, P = 6.1), ISHs (PIC = 0.39, P = 2.6), eSSRs (PIC = 0.36, P = 3.1) and ESHs (PIC = 0.35, P = 3.1). A high correlation (r > 0.97, P < 0.05) was observed between the patterns of diversity exposed by the different marker systems. The polymorphic markers identified are suitable for the de novo construction, or the supplementation of pearl millet linkage maps. The genetic relationships identified among the panel of inbred lines may be useful in designing strategies to improve the use of available genetic variation in the context of pearl millet breeding.

Background The genus Arachis, originated in South America, is divided into nine taxonomical sections comprising of 80 species. Most of the Arachis species are diploids (2n = 2x = 20) and the tetraploid species (2n = 2x = 40) are found in sections Arachis, Extranervosae and Rhizomatosae. Diploid species have great potential to be used as resistance sources for agronomic traits like pests and diseases, drought related traits and different life cycle spans. Understanding of genetic relationships among wild species and between wild and cultivated species will be useful for enhanced utilization of wild species in improving cultivated germplasm. The present study was undertaken to evaluate genetic relationships among species (96 accessions) belonging to seven sections of Arachis by using simple sequence repeat (SSR) markers developed from Arachis hypogaea genomic library and gene sequences from related genera of Arachis. Results The average transferability rate of 101 SSR markers tested to section Arachis and six other sections was 81% and 59% respectively. Five markers (IPAHM 164, IPAHM 165, IPAHM 407a, IPAHM 409, and IPAHM 659) showed 100% transferability. Cluster analysis of allelic data from a subset of 32 SSR markers on 85 wild and 11 cultivated accessions grouped accessions according to their genome composition, sections and species to which they belong. A total of 109 species specific alleles were detected in different wild species, Arachis pusilla exhibited largest number of species specific alleles (15). Based on genetic distance analysis, the A-genome accession ICG 8200 (A. duranensis) and the B-genome accession ICG 8206 (A. ipaënsis) were found most closely related to A. hypogaea. Conclusion A set of cross species and cross section transferable SSR markers has been identified that will be useful for genetic studies of wild species of Arachis, including comparative genome mapping, germplasm analysis, population genetic structure and phylogenetic inferences among

With an objective to expand the repertoire of molecular markers in pigeonpea (Cajanus cajan), 36 microsatellite or simple sequence repeat (SSR) loci were isolated from a SSR-enriched genomic library. Primer pairs were designed for 23 SSR loci, of which 16 yielded amplicons of expected size. Thirteen SSR markers were polymorphic amongst 32 cultivated and eight wild pigeonpea genotypes representing six Cajanus species. These markers amplified a total of 72 alleles ranging from two to eight alleles with an average of 5.5 alleles per locus. The polymorphic information content for these markers ranged from 0.05 to 0.55 with an average of 0.32 per marker. Phenetic analysis clearly distinguished all wild species genotypes from each other and from the cultivated pigeonpea genotypes. These markers should be useful for genome mapping, trait mapping, diversity studies and assessment of gene flow between populations in pigeonpea.

In order to maximize polymorphism in the mapping populations for mapping loci for Fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea, a set of 32 pigeonpea lines were screened for polymorphism with 30 microsatellite or simple sequence repeat markers. A total of 23 marker loci showed polymorphism with 2–4 alleles and the polymorphism information content for these markers ranged from 0.12 to 0.65 with an average of 0.43 per marker. High number of polymorphic markers, higher genetic dissimilarity coefficient and contrasting phenotypic data taken into consideration and five parental combinations were identified and crosses initiated for developing five genetically diverse mapping populations. Of these crosses, one cross segregates for FW resistance, two for SMD resistance and the remaining two crosses segregate for resistance to both FW and SMD. Development of mapping populations is in progress for mapping loci for resistance to FW and SMD in pigeonpea.

This study presents the development and mapping of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers in chickpea. The mapping population is based on an inter-specific cross between domesticated and non-domesticated genotypes of chickpea (Cicer arietinum ICC 4958 × C. reticulatum PI 489777). This same population has been the focus of previous studies, permitting integration of new and legacy genetic markers into a single genetic map. We report a set of 311 novel SSR markers (designated ICCM—ICRISAT chickpea microsatellite), obtained from an SSR-enriched genomic library of ICC 4958. Screening of these SSR markers on a diverse panel of 48 chickpea accessions provided 147 polymorphic markers with 2–21 alleles and polymorphic information content value 0.04–0.92. Fifty-two of these markers were polymorphic between parental genotypes of the inter-specific population. We also analyzed 233 previously published (H-series) SSR markers that provided another set of 52 polymorphic markers. An additional 71 gene-based SNP markers were developed from transcript sequences that are highly conserved between chickpea and its near relative Medicago truncatula. By using these three approaches, 175 new marker loci along with 407 previously reported marker loci were integrated to yield an improved genetic map of chickpea. The integrated map contains 521 loci organized into eight linkage groups that span 2,602 cM, with an average inter-marker distance of 4.99 cM. Gene-based markers provide anchor points for comparing the genomes of Medicago and chickpea, and reveal extended synteny between these two species. The combined set of genetic markers and their integration into an improved genetic map should facilitate chickpea genetics and breeding, as well as translational studies between chickpea and Medicago.

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Grain legumes are rich resource of dietary proteins, minerals, and vitamins; however, productivity remains low, narrow genetic base of the cultivars being one of the several reasons to low productivity. Worldwide approximately half a million legume germplasm acceSSIOns are preserved in genebanks. However, there has been limited use of these resources in crop breeding. Core collection (10% of the entire collection), a subset of accessions representing at least 70% of the genetic variation in the entire collection of the species, has been suggested as a gateway to enhance utilization of germpJasm. Core and mini core (10% of core) collections have been reported in several legumes that when evaluated identified new sources of variation for agronomic traits including resistance to biotic and abiotic stresses. Legumes genomics resources in the past lagged behind cereals. However, situation dramatically changed with emergence of Medicago truncatula, Lotus japonicus, and Glycine max as models for comparative genomics within legume family. Several genomic resources including markers, maps, transcriptomics, proteomics, metabolomics, and bioinformatics resources have been developed. These resources in model plants will not only allow investigation of basic processes important to legumes, but also open the possibility to transfer those processes to- or locate them in other crop species including several legumes. Several genomic projects are developing tools for less-studied legumes which are economically important in Africa and Asia. These genetic and genomic resources represent major milestones in the history of…

The ability to identify genetic variation is indispensable for effective management and use of genetic resources in crop breeding. Genetic variation among 189 groundnut (Arachis hypogaea L.) accessions comprising landraces, cultivars, a mutant, advanced breeding lines and others (unknown genetic background) representing 29 countries and 10 geographical regions was assessed at 25 microsatellite or simple sequence repeat loci. A high number of alleles (265) were detected in the range of 3 (Ah1TC6G09) to 20 (Ah1TC11H06) with an average of 10.6 alleles per locus. The polymorphism information content value at these loci varied from 0.38 (Ah1TC6G09) to 0.88 (Ah1TC11H06) with an average of 0.70. A total of 59 unique alleles and 127 rare alleles were detected at almost all the loci assayed. Cluster analysis grouped 189 accessions into four clusters. In general, genotypes of South America and South Asia showed high level of diversity. Extraordinary level of natural genetic variation reported here provides opportunities to the groundnut community to make better decisions and define suitable strategies for harnessing the genetic variation in groundnut breeding.

Many of the world's most important food legumes are grown in arid and semi-arid regions of Africa and Asia, where crop productivity is hampered by biotic and abiotic stresses. Until recently, these crops have also suffered from a dearth of genomic and molecular-genetic resources and thus were ‘orphans’ of the genome revolution. However, the community of legume researchers has begun a concerted effort to change this situation. The driving force is a series of international collaborations that benefit from recent advances in genome sequencing and genotyping technologies. The focus of these activities is the development of genome-scale data sets that can be used in high-throughput approaches to facilitate genomics-assisted breeding in these legumes.

The progress made in DNA marker technology has been remarkable and exciting in recent years. DNA markers have proved valuable tools in various analyses in plant breeding, for example, early generation selection, enrichment of complex F(1)s, choice of donor parent in backcrossing, recovery of recurrent parent genotype in backcrossing, linkage block analysis and selection. Other main areas of applications of molecular markers in plant breeding include germplasm characterization/fingerprinting, determining seed purity, systematic sampling of germplasm, and phylogenetic analysis. Molecular markers, thus, have proved powerful tools in replacing the bioassays and there are now many examples available to show the efficacy of such markers. We have illustrated some basic concepts and methodology of applying molecular markers for enhancing the selection efficiency in plant breeding. Some successful examples of product developments of molecular breeding have also been presented.

Amplified fragment length polymorphism (AFLP) was employed to assess the diversity in the elite germplasm collection of Jatropha curcas, which has gained tremendous significance as a biofuel plant in India and many other countries recently. Forty-eight accessions, collected from six different states of India, were used with seven AFLP primer combinations that generated a total of 770 fragments with an average of 110 fragments per primer combination. A total of 680 (88%) fragments showed polymorphism in the germplasm analyzed, of which 59 (8.7%) fragments were unique (accession specific) and 108 (15.9%) fragments were rare (present in less than 10% accessions). In order to assess the discriminatory power of seven primer combinations used, a variety of marker attributes like polymorphism information content (PIC), marker index (MI) and resolving power (RP) values were calculated. Although the PIC values ranged from 0.20 (E-ACA/M-CAA) to 0.34 (E-ACT/M-CTT) with an average of 0.26 per primer combination and the MI values were observed in the range of 17.60 (E-ACA/M-CAA) to 32.30 (E-ACT/M-CTT) with an average of 25.13 per primer combination, the RP was recognized the real attribute for AFLP to determine the discriminatory power of the primer combination. The RP values for different primer combinations varied from 23.11 (E-ACA/M-CAA) to 46.82 (E-ACT/M-CTT) with an average of 35.21. Genotyping data obtained for all 680 polymorphic fragments were used to group the accessions analyzed using the UPGMA-phenogram and principal component analysis (PCA). Majority of groups obtained in phenogram and PCA contained accessions as per geographical locations. In general, accessions coming from Andhra Pradesh were found diverse as these were scattered in different groups, whereas accessions coming from Chhattisgarh showed occurrence of higher number of unique/rare fragments. Molecular diversity estimated in the present study combined with the datasets on other morphological/agronomic tr

Molecular markers and genetic linkage maps are pre-requisites for molecular breeding in any crop species. In case of peanut or groundnut (Arachis hypogaea L.), an amphidiploid (4X) species, not a single genetic map is, however, available based on a mapping population derived from cultivated genotypes. In order to develop a genetic linkage map for tetraploid cultivated groundnut, a total of 1,145 microsatellite or simple sequence repeat (SSR) markers available in public domain as well as unpublished markers from several sources were screened on two genotypes, TAG 24 and ICGV 86031 that are parents of a recombinant inbred line mapping population. As a result, 144 (12.6%) polymorphic markers were identified and these amplified a total of 150 loci. A total of 135 SSR loci could be mapped into 22 linkage groups (LGs). While six LGs had only two SSR loci, the other LGs contained 3 (LG_AhXV) to 15 (LG_AhVIII) loci. As the mapping population used for developing the genetic map segregates for drought tolerance traits, phenotyping data obtained for transpiration, transpiration efficiency, specific leaf area and SPAD chlorophyll meter reading (SCMR) for 2 years were analyzed together with genotyping data. Although, 2–5 QTLs for each trait mentioned above were identified, the phenotypic variation explained by these QTLs was in the range of 3.5–14.1%. In addition, alignment of two linkage groups (LGs) (LG_AhIII and LG_AhVI) of the developed genetic map was shown with available genetic maps of AA diploid genome of groundnut and Lotus and Medicago. The present study reports the construction of the first genetic map for cultivated groundnut and demonstrates its utility for molecular mapping of QTLs controlling drought tolerance related traits as well as establishing relationships with diploid AA genome of groundnut and model legume genome species. Therefore, the map should be useful for the community for a variety of applications.

Background Chickpea (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. Results A 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 the

The transcription factor, DREB2A, is one of the promising candidate genes involved in dehydration tolerance in crop plants. In order to isolate DREB2A homologues across cereals (rice, barley and sorghum) and legumes (common bean and chickpea), specific or degenerate primers were used. Gene/phylogenetic trees were constructed using a non-redundant set of 19 DREB1A and 27 DREB2A amino acid sequences and were combined with taxonomic/species tree to prepare reconciled phylogenetic trees. In total, 86 degenerate primers were designed for different clades and 295 degenerate primer combinations were used to amplify DREB homologues in targeted crop species. Successful amplification of DREB2A was obtained in case of sorghum. In parallel, gene-specific primers were used to amplify DREB2A homologues in rice, barley, common bean and chickpea. Seven to eight diverse genotypes from targeted species were used for sequence analysis at DREB2A locus identified/isolated. A maximum of eight SNPs were found in the common bean DREB2A, indicating two distinct haplotypes, three SNPs with five haplotypes were observed in barley whereas a single SNP was observed in rice, sorghum and chickpea. Parsimony based phylogenetic tree revealed distinct clustering of cereals and legumes. Furthermore, alignment of corresponding amino acid sequences showed conservation of AP2 domain across the targeted species.

Cultivated groundnut (Arachis hypogaea L.), is an important oil seed crop grown mostly in tropical and subtropical regions of the world. However, it suffers with narrow genetic diversity due to genetic bottlenecks such as the recent polyploidization and self pollinating nature of the crop. In such crop species, simple sequence repeats (SSRs), as compared to other marker systems such as restriction fragment length polymorphisms (RFLPs), randomly amplified polymorphic DNAs (RAPDs) and amplified fragment length polymorphisms (AFLPs) have been found more informative for genetic studies and breeding applications. Therefore, with an aim to develop new SSR markers in groundnut, a SSR-enriched library was constructed from the genotype ICGV 86031. Out of 29 SSRs isolated, primer pairs were designed for 23 SSR loci, of which 14 (61%) primer pairs yielded scorable amplicons. Eight (57%) primer pairs showed polymorphism among 23 groundnut genotypes that are parents of different groundnut mapping populations at ICRISAT, India and EMBRAPA, Brazil. The polymorphism information content (PIC) for polymorphic SSR markers ranged from 0.13 to 0.36, with an average of 0.25. Newly isolated SSR loci showed good interspecific transferability rates ranging from 13% to 100% across seven legumes and 43% to 100% within the seven legumes. The present set of newly developed SSR markers enriches the existing groundnut SSR repertoire and the transferable SSR markers will be useful for comparative genome analysis in related legumes.

Knowledge of the molecular genetic variation of the accessions of core collections will be important for their efficient use in breeding programs, and for conservation purposes. The present study was undertaken for genotyping the part of the USDA chickpea core collection (Hannan et al 1994) with 20 microsatellite or simple sequence repeat (SSR) markers. In addition to understand the molecular diversity in the core collection, the genetic relationship was studied. A total of 376 accessions from the USDA chickpea core collection were genotyped. Twenty SSR markers revealed a total of 388 alleles among the 376 accessions. In the USDA core collection, the shared allele frequency (SAF) varied from 7.5% to 47.5% with an average of 21.6%. In the present study, the structure of the population was determined by using K=4 based on model-based (Bayesian) clustering algorithm.

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Pigeonpea [Cajanus cajan (L.) Millspaugh] is a very versatile legume with diversified uses as food, feed, fodder and fuel. With the objective of enhancing the utilization of germplasm in breeding and genomic research, a composite collection of 1000 accessions was developed and profiled using 20 SSR markers. Analysis of molecular data for 952 accessions detected 197 alleles, of which 115 were rare and 82 common. Gene diversity varied from 0.002 to 0.726. There were 60 group-specific unique alleles in wild types and 64 in cultivated. Among the cultivated accessions, 37 unique alleles were found in indeterminate (NDT) types. Geographically, 32 unique alleles were found in Asia 4 (Southern Indian provinces, Maldives, and Sri Lanka). Only two alleles differentiated Africa from other regions. Wild and cultivated types shared 73, DT (Determinate) and NDT shared 10, DT and wild shared 4, and the NDT and wild shared 20 alleles. Wild types as a group were genetically more diverse than cultivated types. NDT types were more diverse than the other two groups based on flowering pattern (DT and SDT: Semi-determinate). A reference set based on SSR data and consisting of 300 most diverse accessions, captured 187 (95%) of the 197 alleles of the composite collection. Another reference set based on qualitative traits captured 87% alleles of the composite set. The reference set consisting of 300 most diverse accessions will be profiled with additional markers and extensively phenotyped for traits of economic importance to identify accessions for beneficial traits for utilization in pigeonpea breeding and genomics.

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Chickpea is the fourth largest grain legume crop globally. A composite collection of 3000 accessions was formed and genotyped using 50 SSR markers. The accessions were also field evaluated for seven qualitative traits. Analysis of 48 SSR markers data on 2915 accessions detected 1683 alleles, of which 935 were rare and 748 common. Gene diversity varied from 0.533 to 0.975. Kabuli chickpea as a group were genetically more diverse than other seed types. Several group-specific unique alleles were detected: 104 in Kabuli, 297 in desi, and 69 in wild Cicer; 114 each in West Asia and Mediterranean, 117 in South and South East Asia, and 10 in African region accessions. A genotype-based reference set captured 1315 alleles compared to 1237 alleles in the reference set based on qualitative traits or 1354 alleles based on SSRs and qualitative traits data. The relative usefulness of these reference sets in chickpea breeding and genomics studies are being further investigated.

To increase the number of polymorphic simple sequence repeat markers (SSRs) in chickpea, a genomic library was constructed, and the SSRs derived from this approach are characterized. A genomic DNA library from the chickpea genotype ICC 4958 was constructed after digesting total DNA of ICC 4958 with MBO/Sau and TaqI at University of Frankfurt, Germany. The study increases the existing SSR repertoire in chickpea, which will help to enhance the coverage of linkage maps especially in intraspecific crosses where marker polymorphism is found to be very less.

The large amounts of EST sequence data available from a single species of an organism as well as for several species within a genus provide an easy source of identification of intra- and interspecies single nucleotide polymorphisms (SNPs). In the case of model organisms, the data available are numerous, given the degree of redundancy in the deposited EST data. There are several available bioinformatics tools that can be used to mine this data; however, using them requires a certain level of expertise: the tools have to be used sequentially with accompanying format conversion and steps like clustering and assembly of sequences become time-intensive jobs even for moderately sized datasets. We report here a pipeline of open source software extended to run on multiple CPU architectures that can be used to mine large EST datasets for SNPs and identify restriction sites for assaying the SNPs so that cost-effective CAPS assays can be developed for SNP genotyping in genetics and breeding applications. At the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the pipeline has been implemented to run on a Paracel high-performance system consisting of four dual AMD Opteron processors running Linux with MPICH. The pipeline can be accessed through user-friendly web interfaces at http://hpc.icrisat.cgiar.org/PBSWeb and is available on request for academic use. We have validated the developed pipeline by mining chickpea ESTs for interspecies SNPs, development of CAPS assays for SNP genotyping, and confirmation of restriction digestion pattern at the sequence level.

The use of molecular markers has been shown to be a powerful approach for the genetic dissection andmanipulation of many traits of importance in agriculture. However, their full impact, especially in breeding, is yet to be realized. This is due to a number of limitations such as the time and resources required to discover a large number of polymorphic markers for a species, requirements for sequence information for marker development, and the cost and time for scoring the markers (average per datapoint cost of overUS$1.00). With the advent of Restriction Fragment...

A total of 1499 ESTs generated from 26 different Cicer species, available in the public domain at the time of analysis, were used for in silico identification of SNPs using the bioinformatic tools developed at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) (http://hpc.icrisat.org/PBSWeb). Cluster analysis provided a total of 118 clusters, of which 11 clusters contained sequences from more than one Cicer species. Further, these clusters were assembled into 19 contigs and 184 putative SNPs were identified in 15 contigs. However, only 73 SNPs involved restriction enzyme sites for development of the CAPS assays as identified through the SNP2CAPs program. Primer pairs were designed for only 8 contigs (CL3a, CL3c, CL3d, CL3e, CL4a, CL10, CL20 and CL99) which had SNPs, resulting in putative recognition sites to commonly used restriction enzymes. Results of the demonstrates the utility of Cicer EST resources and the availability of bioinformatics analysis pipelines for the large-scale identification of SNPs on the HPC (High Performance Computer) at ICRISAT and the development of costeffective CAPS assay for SNP genotyping. It is anticipated that the availability of large number of ESTs from more than one genotype of cultivated chickpea (C. arietinum) in the near future will make it possible to develop larger number of SNPs in cultivated chickpea germplasm for genome analysis and breeding applications

Salinity is an ever-increasing problem in agriculture worldwide, especially in South Asia (India, Pakistan) and Australia. Improved genotypes that are well adapted to saline conditions are needed to enhance and sustain production in these areas. A screening of 263 accessions of chickpea, including 211 accessions from ICRISAT's mini-core collection (10% of the core collection and 1% of the entire collection), showed a 6-fold range of variation for seed yield under salinity (1.9 L of 80 mM NaCl per 7.5 kg Vertisol), with several genotypes yielding 20% more than a previously released salinity tolerant cultivar. The range of variation in yields under salinity was similar in both kabuli and desi chickpeas, indicating that breeding for salinity tolerance can be undertaken in both groups. A strong relationship (r2 = 0.50) was found between the seed yield under salinity and the seed yield under a non-saline control treatment, indicating that the seed yield under salinity was explained in part by a yield potential component and in part by salinity tolerance per se. Seed yields under salinity were therefore computed to separate the yield potential component from the residuals that accounted for salinity tolerance per se. Among the genotypes evaluated, desi genotypes had higher salinity tolerance than kabuli genotypes. The residuals were highly correlated to the ratio of seed yield under salinity to that of the control, indicating that both parameters can be used to assess salinity tolerance. A similar ratio was calculated for shoot dry weight at 50 days after sowing. However, no significant correlation was found between the shoot dry weight ratio and the yield ratio, indicating that differences in salinity tolerance among genotypes could not be inferred from measurements in the vegetative stage. The major trait related to salinity tolerance was the ability to maintain a large number of filled pods, whereas seed size was similar in tolerant and sensitive genotypes. Salinity to

Drought, salinity, and extreme variations in temperature are the major abiotic constraints to chickpea production worldwide. With support from GCP, we developed a global composite collection (3,000 accessions), profiled its structure and diversity using SSRs (50), and a reference set of 300 accessions (211 chickpea mini core + 89 additional diverse accessions) identified using DARwin-5.0. This reference set captured 78% (1403 alleles) of the 1791 alleles of the composite collection. Currently, we are saturating this reference set with additional SSRs and have plans to survey this reference set using DArT markers once the DArT technology is established at ICRISAT. Techniques for screening for drought (root traits) and salinity tolerance have been standardized. Published studies revealed genetic variability for traits associated with drought and salinity tolerance among chickpea mini core germplasm accessions. We plan to extensively evaluate this reference set (300 accessions) for drought and salinity tolerance besides agronomic and quality traits and associate this variation with allelic diversity present in the reference subset. The genetically diverse accessions with contrasting response to drought and salinity will be identified for diverse uses in chickpea genomics and breeding.

Chickpea (Cicer arietinum L.), also known as Garbanzo bean or Bengal gram, is the second most cultivated grain legume grown globally after dry bean (FAOSTAT data, 2007). It is cultivated annually on an area of about 10 million hectares over 50 countries. Over 80% of its area is in the semi-arid tropics (SAT) that encompass most of south Asia, parts of southeast Asia, a swathe across sub-Saharan Africa, much of southern and eastern Africa, and parts of Latin America. These regions are characterized by high atmospheric water demand, a high mean annual temperature, limited and erratic monsoonal rainfall, and nutrient poor soils. The major constraints to chickpea production in SAT include terminal drought and heat stresses, fusarium wilt and Helicoverpa pod borer. Soil salinity is also a major constraint to adaptation of chickpea in some areas, particularly in India, Pakistan, Bangladesh, Iran and Australia. High instances of dry root rot are reported from Sub- Saharan Africa and India. India is the largest chickpea producing country with 64% of global chickpea production (FAOSTAT data, 2007). Chickpea is grown on 6.7 m ha from latitude 32°N in northern India with cooler, long-season environment to 10°N in southern India with warmer, short season environment. There has been a large, shift in chickpea area from north to central and southern India, mainly because of expansion in area under irrigation and wheat cultivation in northern India. During the past four decades, chickpea area declined by about 4.2 m ha in northern and north-eastern states (Punjab, Haryana, Uttar Pradesh and Bihar) and increased by 2.6 m ha in central and southern states (Madhya Pradesh, Maharashtra, Karnataka and Andhra Pradesh). This drastic shift in chickpea cultivation from cooler, long-season environments to warmer, short-season environments resulted in chickpeas being more prone to abiotic and biotic stresses that are prevalent in warm short season environments (e.g. terminal drought and heat

Grain legumes are important crops for providing key components in the diets of resource-poor people of the semi-arid tropic (SAT) regions of the world. Although there are several grain legume crops grown in SAT, the present chapter deals with three important legumes i.e. groundnut or peanut (Arachis hypogaea), chickpea (Cicer arietinum) and pigeonpea (Cajanus cajan). Production of these legume crops are challenged by serious abiotic stresses e.g. drought, salinity as well as several fungal, viral and nematode diseases. To tackle these constraints through molecular breeding, some efforts have been initiated to develop genomic resources e.g. molecular markers, molecular genetic maps, expressed sequence tags (ESTs), macro-/micro- arrays, bacterial artificial chromosomes (BACs), etc. These genomic resources together with recently developed genetic and genomics strategies e.g. functional molecular markers, linkage-disequilibrium (LD) based association mapping, functional and comparative genomics offer the possibility of accelerating molecular breeding for abiotic and biotic stress tolerances in the legume crops. However, low level of polymorphism present in the cultivated genepools of these legume crops, imprecise phenotyping of the germplasm and the higher costs of development and application of genomic tools are critical factors in utilizing genomics in breeding of these legume crops.

Background With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow. Results A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusion A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application wit

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.