Coverage-based consensus calling (CbCC) of short sequence reads and comparison of CbCC results to identify SNPs in chickpea (Cicer arietinum; Fabaceae), a crop species without a reference genome.

PREMISE OF THE STUDY: Next-generation sequencing (NGS) technologies are frequently used for resequencing and mining of single nucleotide polymorphisms (SNPs) by comparison to a reference genome. In crop species such as chickpea (Cicer arietinum) that lack a reference genome sequence, NGS-based SNP discovery is a challenge. Therefore, unlike probability-based statistical approaches for consensus calling and by comparison with a reference sequence, a coverage-based consensus calling (CbCC) approach was applied and two genotypes were compared for SNP identification. METHODS: A CbCC approach is used in this study with four commonly used short read alignment tools (Maq, Bowtie, Novoalign, and SOAP2) and 15.7 and 22.1 million Illumina reads for chickpea genotypes ICC4958 and ICC1882, together with the chickpea trancriptome assembly (CaTA). KEY RESULTS: A nonredundant set of 4543 SNPs was identified between two chickpea genotypes. Experimental validation of 224 randomly selected SNPs showed superiority of Maq among individual tools, as 50.0% of SNPs predicted by Maq were true SNPs. For combinations of two tools, greatest accuracy (55.7%) was reported for Maq and Bowtie, with a combination of Bowtie, Maq, and Novoalign identifying 61.5% true SNPs. SNP prediction accuracy generally increased with increasing reads depth. CONCLUSIONS: This study provides a benchmark comparison of tools as well as read depths for four commonly used tools for NGS SNP discovery in a crop species without a reference genome sequence. In addition, a large number of SNPs have been identified in chickpea that would be useful for molecular breeding.

A comprehensive resource of drought- and salinity- responsive ESTs for gene discovery and marker development in chickpea (Cicer arietinum L.).

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 (< or =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 > or = 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. CONCLUSION: Generated 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.

The generation challenge programme platform: semantic standards and workbench for crop science.

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

A database of annotated tentative orthologs from crop abiotic stress transcripts.

A minimal requirement to initiate a comparative genomics study on plant responses to abiotic stresses is a dataset of orthologous sequences. The availability of a large amount of sequence information, including those derived from stress cDNA libraries allow for the identification of stress related genes and orthologs associated with the stress response. Orthologous sequences serve as tools to explore genes and their relationships across species. For this purpose, ESTs from stress cDNA libraries across 16 crop species including 6 important cereal crops and 10 dicots were systematically collated and subjected to bioinformatics analysis such as clustering, grouping of tentative orthologous sets, identification of protein motifs/patterns in the predicted protein sequence, and annotation with stress conditions, tissue/library source and putative function. All data are available to the scientific community at http://intranet.icrisat.org/gt1/tog/homepage.htm. We believe that the availability of annotated plant abiotic stress ortholog sets will be a valuable resource for researchers studying the biology of environmental stresses in plant systems, molecular evolution and genomics.