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

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Title Gene network modules associated with abiotic stress response in tolerant rice genotypes identified by transcriptome meta-analysis
 
Creator Smita, Shuchi
Katiyar, Amit
Lenka, Sangram Keshari
Dalal, Monika
Kumar, Amish
Mahtha, Sanjeet Kumar
Yadav, Gitanjali
Chinnusamy, Viswanathan
Pandey, Dev Mani
Bansal, Kailash Chander
 
Subject Rice (Oryza sativa)
Gene network module
Abiotic stress
QTLs
Tolerant genotype
Meta-analysis
Transcriptome
 
Description Accepted date: 19 June 2019
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.
The authors would like to thank the Indian Council of Agricultural Research (ICAR) for supporting this work through the ICAR-sponsored project on the National Initiative on Climate Resilient Agriculture (NICRA) project. VC was supported by NASF (ICAR) grant No. Phen 2015/2011-12. Cis-element GRN analysis was performed using Computational facilities provided by the BTISNET program of the DBT, Govt. of India Grant No. BT/BI/04/069/2006. Use of computational resources of Bioinformatics Center, NII, and New Delhi for TRANSFAC analysis is gratefully acknowledged.
 
Date 2019-07-12T06:46:00Z
2019-07-12T06:46:00Z
2020
 
Type Article
 
Identifier Functional & Integrative Genomics, (In Press)
1438-7948
http://223.31.159.10:8080/jspui/handle/123456789/961
https://link.springer.com/article/10.1007%2Fs10142-019-00697-w
https://doi.org/10.1007/s10142-019-00697-w
 
Language en_US
 
Format application/pdf
 
Publisher Springer Nature Publishing AG