Project description:Microarrays have increasingly become a powerful tool for high throughput gene-expression studies and discovery of novel biomarker genes. Developed for a large number of organisms, including plants, microarrays are commonly performed for species that have sequenced data, for performing gene expression analysis, miRNA profiling, comparative genomic hybridization (CGH), ChIP-on-chip and SNP analysis. Genomic resources are still very limited for chickpea, a very important food legume crop. Here, we report the design and comprehensive validation of Next Generation Sequencing transcriptome data for chickpea through microarray technology to develop a high-throughput resource for studying the expression of all the transcripts in different biological samples to help functional genomics and breeding programs. This microarray design was developed and validated jointly by Genotypic Technology Private Limited and National Institute of Plant Genome Research. First, we designed 400k probes using reads covering 35k assembled contigs and 100k singletons chickpea transcripts. The 400k chip was hybridized with DNA and RNA samples of chickpea and microarray analysis was carried out. A total of 73,922 probes were found to be specific to chickpea transcripts. Best probes were filtered from the analyzed data and a total of 61,659 probes were selected to develop the final microarray design in 60k gene-expression microarray format. The probes represented 51,444 unique transcripts. The probes were annotated based on their corresponding chickpea transcript and similarity with other plants species. Microarray results were concordant with previous results from the NGS studies. The design of custom oligonucleotide probes for microarrays have varied functional genomic applications and this approach represents a valuable resource for chickpea.
Project description:Microarrays have increasingly become a powerful tool for high throughput gene-expression studies and discovery of novel biomarker genes. Developed for a large number of organisms, including plants, microarrays are commonly performed for species that have sequenced data, for performing gene expression analysis, miRNA profiling, comparative genomic hybridization (CGH), ChIP-on-chip and SNP analysis. Genomic resources are still very limited for chickpea, a very important food legume crop. Here, we report the design and comprehensive validation of Next Generation Sequencing transcriptome data for chickpea through microarray technology to develop a high-throughput resource for studying the expression of all the transcripts in different biological samples to help functional genomics and breeding programs. This microarray design was developed and validated jointly by Genotypic Technology Private Limited and National Institute of Plant Genome Research. First, we designed 400k probes using reads covering 35k assembled contigs and 100k singletons chickpea transcripts. The 400k chip was hybridized with DNA and RNA samples of chickpea and microarray analysis was carried out. A total of 73,922 probes were found to be specific to chickpea transcripts. Best probes were filtered from the analyzed data and a total of 61,659 probes were selected to develop the final microarray design in 60k gene-expression microarray format. The probes represented 51,444 unique transcripts. The probes were annotated based on their corresponding chickpea transcript and similarity with other plants species. Microarray results were concordant with previous results from the NGS studies. The design of custom oligonucleotide probes for microarrays have varied functional genomic applications and this approach represents a valuable resource for chickpea.
Project description:Microarrays have increasingly become a powerful tool for high throughput gene-expression studies and discovery of novel biomarker genes. Developed for a large number of organisms, including plants, microarrays are commonly performed for species that have sequenced data, for performing gene expression analysis, miRNA profiling, comparative genomic hybridization (CGH), ChIP-on-chip and SNP analysis. Genomic resources are still very limited for chickpea, a very important food legume crop. Here, we report the design and comprehensive validation of Next Generation Sequencing transcriptome data for chickpea through microarray technology to develop a high-throughput resource for studying the expression of all the transcripts in different biological samples to help functional genomics and breeding programs. This microarray design was developed and validated jointly by Genotypic Technology Private Limited and National Institute of Plant Genome Research. First, we designed 400k probes using reads covering 35k assembled contigs and 100k singletons chickpea transcripts. The 400k chip was hybridized with DNA and RNA samples of chickpea and microarray analysis was carried out. A total of 73,922 probes were found to be specific to chickpea transcripts. Best probes were filtered from the analyzed data and a total of 61,659 probes were selected to develop the final microarray design in 60k gene-expression microarray format. The probes represented 51,444 unique transcripts. The probes were annotated based on their corresponding chickpea transcript and similarity with other plants species. Microarray results were concordant with previous results from the NGS studies. The design of custom oligonucleotide probes for microarrays have varied functional genomic applications and this approach represents a valuable resource for chickpea.
Project description:Purpose: High-altitude adaptive evolution of transcription, and the convergence and divergence of transcriptional alteration across species in response to high-altitude environments, is an important topic of broad interest to the general biology community. Our study aims to answer this important biological question. Methods: We generated deep transcriptome data of high- and low- altitude populations across four species: chicken, pig, goat and sheep, as well as high-altitude yak and low-altitude cattle, from six tissues (heart, kidney, liver, lung, skeletal muscle and spleen). Results: Here we provide a comprehensive comparative transcriptome landscape of expression and alternative splicing variation between low- and high-altitude populations across multiple species for distinct tissues. Conclusions: Our data serves a valuable resource for further study on adaptive transcription evolution and identification of candidate adaptive genes.
Project description:In this study, we have identified small RNA during salinity stress response in chickpea. Small RNA library was prepared and sequencing was performed using Illumina platform. A total of 79 million reads were generated. These reads were mapped to the chickpea genome using Bowtie.
Project description:This research highlights the importance of combining genomics and metabolomics to advance our understanding of the chemical diversity underpinning fungal signaling and communication.