Browsing by Author "Patel, Ravi K."

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CTDB: an integrated chickpea transcriptome database for functional and applied genomics
(PLOS, 2015) Verma, Mohit; Kumar, Vinay; Patel, Ravi K.; Garg, Rohini; Jain, Mukesh
Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology) search and comparative gene expression analysis. The current release of CTDB (v2.0) hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types) and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms) between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.
A draft genome sequence of the pulse crop chickpea (Cicer arietinum L.)
(John Wiley & Sons, 2013) Jain, Mukesh; Misra, Gopal; Patel, Ravi K.; Priya, Pushp; Jhanwar, Shalu; Khan, Aamir W.; Shah, Niraj; Singh, Vikas K.; Garg, Rohini; Jeena, Ganga; Yadav, Manju; Kant, Chandra; Sharma, Priyanka; Yadav, Gitanjali; Bhatia, Sabhyata; Tyagi, Akhilesh K.; Chattopadhyay, Debasis
Cicer arietinum L. (chickpea) is the third most important food legume crop. We have generated the draft sequence of a desi-type chickpea genome using next-generation sequencing platforms, bacterial artificial chromosome end sequences and a genetic map. The 520-Mb assembly covers 70% of the predicted 740-Mb genome length, and more than 80% of the gene space. Genome analysis predicts the presence of 27,571 genes and 210 Mb as repeat elements. The gene expression analysis performed using 274 million RNA-Seq reads identified several tissue-specific and stress-responsive genes. Although segmental duplicated blocks are observed, the chickpea genome does not exhibit any indication of recent whole-genome duplication. Nucleotide diversity analysis provides an assessment of a narrow genetic base within the chickpea cultivars. We have developed a resource for genetic markers by comparing the genome sequences of one wild and three cultivated chickpea genotypes. The draft genome sequence is expected to facilitate genetic enhancement and breeding to develop improved chickpea varieties.
Gene discovery and tissue-specific transcriptome analysis in chickpea with massively parallel pyrosequencing and web resource development
(Am. Soc. of Plant Biologists, 2011) Garg, Rohini; Patel, Ravi K.; Jhanwar, Shalu; Priya, Pushp; Bhattacharjee, Annapurna; Yadav, Gitanjali; Bhatia, Sabhyata; Chattopadhyay, Debasis; Tyagi, Akhilesh K.; Jain, Mukesh
Chickpea (Cicer arietinum) is an important food legume crop but lags in the availability of genomic resources. In this study, we have generated about 2 million high-quality sequences of average length of 372 bp using pyrosequencing technology. The optimization of de novo assembly clearly indicated that hybrid assembly of long-read and short-read primary assemblies gave better results. The hybrid assembly generated a set of 34,760 transcripts with an average length of 1,020 bp representing about 4.8% (35.5 Mb) of the total chickpea genome. We identified more than 4,000 simple sequence repeats, which can be developed as functional molecular markers in chickpea. Putative function and Gene Ontology terms were assigned to at least 73.2% and 71.0% of chickpea transcripts, respectively. We have also identified several chickpea transcripts that showed tissue-specific expression and validated the results using real-time polymerase chain reaction analysis. Based on sequence comparison with other species within the plant kingdom, we identified two sets of lineage-specific genes, including those conserved in the Fabaceae family (legume specific) and those lacking significant similarity with any non chickpea species (chickpea specific). Finally, we have developed a Web resource, Chickpea Transcriptome Database, which provides public access to the data and results reported in this study. The strategy for optimization of de novo assembly presented here may further facilitate the transcriptome sequencing and characterization in other organisms. Most importantly, the data and results reported in this study will help to accelerate research in various areas of genomics and implementing breeding programs in chickpea.
NGS QC Toolkit: A toolkit for quality control of next generation sequencing data
(PLOS, 2012) Patel, Ravi K.; Jain, Mukesh
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.
De novo assembly of chickpea transcriptome using short reads for gene discovery and marker identification
(Oxford University Press, 2011) Garg, Rohini; Patel, Ravi K.; Tyagi, Akhilesh K.; Jain, Mukesh
Chickpea ranks third among the food legume crops production in the world. However, the genomic resources available for chickpea are still very limited. In the present study, the transcriptome of chickpea was sequenced with short reads on Illumina Genome Analyzer platform. We have assessed the effect of sequence quality, various assembly parameters and assembly programs on the final assembly output. We assembled ~107million high-quality trimmed reads using Velvet followed by Oases with optimal parameters into a non-redundant set of 53 409 transcripts (≥100 bp), representing about 28 Mb of unique transcriptome sequence. The average length of transcripts was 523 bp and N50 length of 900 bp with coverage of 25.7 rpkm (reads per kilobase per million). At the protein level, a total of 45 636 (85.5%) chickpea transcripts showed significant similarity with unigenes/predicted proteins from other legumes or sequenced plant genomes. Functional categorization revealed the conservation of genes involved in various biological processes in chickpea. In addition, we identified simple sequence repeat motifs in transcripts. The chickpea transcripts set generated here provides a resource for gene discovery and development of functional molecular markers. In addition, the strategy for de novo assembly of transcriptome data presented here will be helpful in other similar transcriptome studies.
PlantRGS: a web server for the identification of most suitable candidate reference genes for quantitative gene expression studies in plants
(Oxford University Press, 2011) Patel, Ravi K.; Jain, Mukesh
Normalization of quantitative gene expression data with a suitable reference gene is essential for accurate and reliable results. However, the availability and choice of most suitable reference gene(s) showing uniform expression across all the experimental conditions remain a drawback. We have developed a web server, PlantRGS (http://www.nipgr.res.in/PlantRGS), for the identification of most suitable candidate reference gene(s) at the whole-genome level using microarray data for quantitative gene expression studies in plants. Microarray data from more than 11 000 tissue samples for nine plant species have been included in the PlantRGS for meta-analysis. The web server provides a user-friendly graphical user interface-based analysis tool for the identification of most suitable reference genes in the selected plant species under user-defined experimental conditions. Various parameter options and output formats will help users to investigate desired number of most suitable reference genes with wide range of expression levels. Validation of results revealed that novel reference genes identified by the PlantRGS outperforms the traditionally used reference genes in terms of expression stability. We anticipate that the PlantRGS will provide a platform for the identification of most suitable reference gene(s) under given experimental conditions and facilitate quantitative gene expression studies in plants.