Gene discovery and tissue-specific transcriptome analysis in chickpea with massively parallel pyrosequencing and web resource development

NGS QC Toolkit: a toolkit for quality control of next generation sequencing data

Next generation sequencing (NGS) technologies provide a high-throughput means to generate large amount of sequence data. However, quality control (QC) of sequence data generated from these technologies is extremely important for meaningful downstream analysis. Further, highly efficient and fast processing tools are required to handle the large volume of datasets. Here, we have developed an application, NGS QC Toolkit, for quality check and filtering of high-quality data. This toolkit is a standalone and open source application freely available at http://www.nipgr.res.in/ngsqctoolkit.html. All the tools in the application have been implemented in Perl programming language. The toolkit is comprised of user-friendly tools for QC of sequencing data generated using Roche 454 and Illumina platforms, and additional tools to aid QC (sequence format converter and trimming tools) and analysis (statistics tools). A variety of options have been provided to facilitate the QC at user-defined parameters. The toolkit is expected to be very useful for the QC of NGS data to facilitate better downstream analysis.

NGS QC Toolkit: a toolkit for quality control of next generation sequencing data

Next generation sequencing (NGS) technologies provide a high-throughput means to generate large amount of sequence data. However, quality control (QC) of sequence data generated from these technologies is extremely important for meaningful downstream analysis. Further, highly efficient and fast processing tools are required to handle the large volume of datasets. Here, we have developed an application, NGS QC Toolkit, for quality check and filtering of high-quality data. This toolkit is a standalone and open source application freely available at http://www.nipgr.res.in/ngsqctoolkit.html. All the tools in the application have been implemented in Perl programming language. The toolkit is comprised of user-friendly tools for QC of sequencing data generated using Roche 454 and Illumina platforms, and additional tools to aid QC (sequence format converter and trimming tools) and analysis (statistics tools). A variety of options have been provided to facilitate the QC at user-defined parameters. The toolkit is expected to be very useful for the QC of NGS data to facilitate better downstream analysis.

Genome-enabled insights into legume biology

Legumes are the third-largest family of angiosperms, the second-most-important crop family, and a key source of biological nitrogen in agriculture. Recently, the genome sequences of Glycine max (soybean), Medicago truncatula, and Lotus japonicus were substantially completed. Comparisons among legume genomes reveal a key role for duplication, especially a whole-genome duplication event approximately 58 Mya that is shared by most agriculturally important legumes. A second and more recent genome duplication occurred only in the lineage leading to soybean. Outcomes of genome duplication, including gene fractionation and sub- and neofunctionalization, have played key roles in shaping legume genomes and in the evolution of legume-specific traits. Analysis of legume genome sequences also enables the discovery of legume-specific gene families and provides a framework for genome-wide association mapping that will target phenotypes of special importance in legumes. Translating genomic resources from sequenced species to less studied but still important "orphan" legumes will enhance prospects for world food production.

Next generation quantitative genetics in plants

Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.

Pyrosequencing data reveals tissue-specific expression of lineage-specific transcripts in chickpea

Chickpea is a very important crop legume plant, which provides a protein-rich supplement to cereal-based diets and has the ability to fix atmospheric nitrogen. Despite its economic importance, the functional genomic resources for chickpea are very limited. Recently, we reported the complete transcriptome of chickpea using next generation sequencing technologies. We analyzed the tissue-specific expression of chickpea transcripts based on RNA-seq data. In addition, we identified two sets of lineage-specific genes, including a total of 3,632 chickpea-specific and 741 as legume-specific transcripts based on sequence comparison with other species within plant kingdom. The study of lineage-specific genes provides insights into the species-/lineage-specific functions and evolutionary processes. In this study, we further analyze the expression profiles of legume- and chickpea-specific transcripts in various tissue samples. Several legume- and chickpea-specific transcripts showed preferential and/or specific expression in the tissue samples analyzed. Our analysis provides evidence for the role of legume- and chickpea-specific transcripts in various tissues and opens an important area of future research to elucidate the exact role of these genes.