ArticleCommunications biology2022
An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Pooled it
- A portable recalibration workflow for reference-based variant calling in non-human genomes.PLoS computational biology · 2026Article
- Pan-transcriptome analysis of diverse chickpea accessions reveals specific expression patterns and genetic variations associated with agronomic traits.Plant molecular biology · 2026Article
- From gene discovery to breeding tools: functional KASP markers for flowering time selection in chickpea.BMC plant biology · 2026Article
- Functional Genomics: From Soybean to Legume.International journal of molecular sciences · 2025Review
- Article
- Temporal gene expression profiling suggests stage-specific regulation of apocarotenoid biosynthesis genes during stigma development inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2025Article
- Molecular and expression analyses indicate the role of fusion transcripts in mediating abiotic stress responses in chickpea.Frontiers in plant science · 2025Article
- Phenotypic and genetic characterization of a near-isogenic line pair: insights into flowering time in chickpea.BMC plant biology · 2024Article
- Insights intoFrontiers in plant science · 2024Article
- Unravelling Differential DNA Methylation Patterns in Genotype Dependent Manner under Salinity Stress Response in Chickpea.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large-scale transcriptome analysis can provide a systems-level understanding of biological processes. To accelerate functional genomic studies in chickpea, we perform a comprehensive transcriptome analysis to generate full-length transcriptome and expression atlas of protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs) from 32 different tissues/organs via deep sequencing. The high-depth RNA-seq dataset reveal expression dynamics and tissue-specificity along with associated biological functions of PCGs and lncRNAs during development. The coexpression network analysis reveal modules associated with a particular tissue or a set of related tissues. The components of transcriptional regulatory networks (TRNs), including transcription factors, their cognate cis-regulatory motifs, and target PCGs/lncRNAs that determine developmental programs of different tissues/organs, are identified. Several candidate tissue-specific and abiotic stress-responsive transcripts associated with quantitative trait loci that determine important agronomic traits are also identified. These results provide an important resource to advance functional/translational genomic and genetic studies during chickpea development and environmental conditions.
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Registered trials
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