Institutional Publications

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Author: search.filters.author.Shah, NirajSubject: search.filters.subject.next generation sequencing

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    Global transcriptome analysis of developing chickpea (Cicer arietinum L.) seeds
    (Frontiers Media S.A., 2014) Pradhan, Seema; Bandhiwal, Nitesh; Shah, Niraj; Kant, Chandra; Gaur, Rashmi; Bhatia, Sabhyata
    Understanding developmental processes, especially in non-model crop plants, is extremely important in order to unravel unique mechanisms regulating development. Chickpea (C. arietinum L.) seeds are especially valued for their high carbohydrate and protein content. Therefore, in order to elucidate the mechanisms underlying seed development in chickpea, deep sequencing of transcriptomes from four developmental stages was undertaken. In this study, next generation sequencing platform was utilized to sequence the transcriptome of four distinct stages of seed development in chickpea. About 1.3 million reads were generated which were assembled into 51,099 unigenes by merging the de novo and reference assemblies. Functional annotation of the unigenes was carried out using the Uniprot, COG and KEGG databases. RPKM based digital expression analysis revealed specific gene activities at different stages of development which was validated using Real time PCR analysis. More than 90% of the unigenes were found to be expressed in at least one of the four seed tissues. DEGseq was used to determine differentially expressing genes which revealed that only 6.75% of the unigenes were differentially expressed at various stages. Homology based comparison revealed 17.5% of the unigenes to be putatively seed specific. Transcription factors were predicted based on HMM profiles built using TF sequences from five legume plants and analyzed for their differential expression during progression of seed development. Expression analysis of genes involved in biosynthesis of important secondary metabolites suggested that chickpea seeds can serve as a good source of antioxidants. Since transcriptomes are a valuable source of molecular markers like simple sequence repeats (SSRs), about 12,000 SSRs were mined in chickpea seed transcriptome and few of them were validated. In conclusion, this study will serve as a valuable resource for improved chickpea breeding.
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    Development of an expressed gene catalogue and molecular markers from the de novo assembly of short sequence reads of the lentil (Lens culinaris Medik.) transcriptome
    (John Wiley & Sons Ltd, 2013) Verma, Priyanka; Shah, Niraj; Bhatia, Sabhyata
    Genomic resources such as ESTs, molecular markers and linkage maps are essential for crop improvement. However, these resources are still limited in important legumes such as lentil (Lens culinaris Medik.), which is valued world wide as a rich source of dietary protein. In this study, the de novo transcriptome assembly of 119,855,798 short reads, generated by Illumina paired-end sequencing, was performed using various assembly programs. This resulted in 42,196 nonredundant high-quality transcripts of average length 810 bases, N50 value of 1,432 and an average expression per transcript of 26.21 rpkm reads per kilobase per million(RPKM). Similarity search with the unigenes and protein sequences of other plants resulted in maximum similarity with soybean. A total of 20,009 nonredundant transcripts showed similarity with the UniProtKB database and of these, 18,064 transcripts were grouped into three main GO categories, that is, biological process (15,126), molecular function (15,505) and cellular component (9,434). Annotated transcripts were mapped to 289 predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 8,893 transcripts were classified into 24 functional categories based on Cluster of Orthologous Groups (COG) of proteins. Mining the data set for the presence of SSRs resulted in 8,722 SSRs with a frequency occurrence of one SSR per 3.92 kb. From these, 5,673 SSR primer pairs were designed, and a subset of these were utilized for diversity analysis. This study, which provides a large data set of annotated transcripts and gene-based SSR markers, would serve as a foundation for various applications in lentil breeding and genetics.