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Gene network modules associated with abiotic stress response in tolerant rice genotypes identified by transcriptome meta-analysis.

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.

journal_name

Funct Integr Genomics

journal_title

Functional & integrative genomics

authors

Smita S,Katiyar A,Lenka SK,Dalal M,Kumar A,Mahtha SK,Yadav G,Chinnusamy V,Pandey DM,Bansal KC

doi

10.1007/s10142-019-00697-w

subject

Has Abstract

pub_date

2020-01-01 00:00:00

pages

29-49

issue

1

eissn

1438-793X

issn

1438-7948

pii

10.1007/s10142-019-00697-w

journal_volume

20

pub_type

杂志文章,meta分析

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