| Literature DB >> 31286320 |
Shuchi Smita1,2,3,4, Amit Katiyar1,2,5, Sangram Keshari Lenka6, Monika Dalal7, Amish Kumar8, Sanjeet Kumar Mahtha8, Gitanjali Yadav8, Viswanathan Chinnusamy9, Dev Mani Pandey2, Kailash Chander Bansal10,11.
Abstract
Abiotic stress tolerance is a complex trait regulated by multiple genes and gene networks in plants. A range of abiotic stresses are known to limit rice productivity. Meta-transcriptomics has emerged as a powerful approach to decipher stress-associated molecular network in model crops. However, retaining specificity of gene expression in tolerant and susceptible genotypes during meta-transcriptome analysis is important for understanding genotype-dependent stress tolerance mechanisms. Addressing this aspect, we describe here "abiotic stress tolerant" (ASTR) genes and networks specifically and differentially expressing in tolerant rice genotypes in response to different abiotic stress conditions. We identified 6,956 ASTR genes, key hub regulatory genes, transcription factors, and functional modules having significant association with abiotic stress-related ontologies and cis-motifs. Out of the 6956 ASTR genes, 73 were co-located within the boundary of previously identified abiotic stress trait-related quantitative trait loci. Functional annotation of 14 uncharacterized ASTR genes is proposed using multiple computational methods. Around 65% of the top ASTR genes were found to be differentially expressed in at least one of the tolerant genotypes under different stress conditions (cold, salt, drought, or heat) from publicly available RNAseq data comparison. The candidate ASTR genes specifically associated with tolerance could be utilized for engineering rice and possibly other crops for broad-spectrum tolerance to abiotic stresses.Entities:
Keywords: Abiotic stress; Gene network module; Meta-analysis; QTLs; Rice (Oryza sativa); Tolerant genotype; Transcriptome
Mesh:
Year: 2019 PMID: 31286320 DOI: 10.1007/s10142-019-00697-w
Source DB: PubMed Journal: Funct Integr Genomics ISSN: 1438-793X Impact factor: 3.410