Treffer: An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea.

Title:
An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea.
Authors:
Jain, Mukesh1,2 (AUTHOR) mjain@jnu.ac.in, Bansal, Juhi1 (AUTHOR), Rajkumar, Mohan Singh1 (AUTHOR), Garg, Rohini3 (AUTHOR)
Source:
Communications Biology. 10/19/2022, Vol. 5 Issue 1, p1-18. 18p.
Database:
Academic Search Index

Weitere Informationen

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. A full-length transcriptome and expression atlas of protein-coding genes and long non-coding RNAs is generated in chickpea. Components of transcriptional regulatory networks and candidate tissue-specific transcripts associated with quantitative trait loci are identified. [ABSTRACT FROM AUTHOR]