Literature DB >> 30802474

Integrative meta-analysis of transcriptomic responses to abiotic stress in cotton.

Ahmad Tahmasebi1, Elham Ashrafi-Dehkordi1, Amir Ghaffar Shahriari2, Seyed Mohammad Mazloomi3, Esmaeil Ebrahimie4.   

Abstract

Abiotic environmental stresses are important factors that limit the growth, fiber yield, and quality of cotton. In this study, an integrative meta-analysis and a system-biology analysis were performed to explore the underlying transcriptomic mechanisms that are critical for response to stresses. From the meta-analysis, it was observed that a total of 1465 differentially expressed genes (DEGs) between normal and stress conditions. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that DEGs were significantly enriched in the ubiquitin-dependent process, biosynthesis of secondary metabolites, plant hormone, and signaled transduction. The results also indicated that some of DEGs were assigned to transcription factors (TFs). A total of 148 TFs belonged to 25 conserved families were identified that among them S1Fa-like, ERF, NAC, bZIP families, were the most abundant groups. Moreover, we searched in upstream regions of DEGs for over-represented DNA motifs and were able to identify 11 conserved sequence motifs. The functional analysis of these motifs revealed that they were involved in regulation of transcription, DNA replication, cytoskeleton organization, and translation. Weighted gene co-expression network analysis (WGCNA) uncovered 12 distinct co-expression modules. Four modules were significantly associated with genes involved in response to stress and cell wall organization. The network analysis also identified hub genes such as RTNLB5 and PRA1, which may be involved in regulating stress response. The findings could help to understand the mechanisms of response to abiotic stress and introduce candidate genes that may be beneficial to cotton plant breeding programs.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Abiotic stress; Co-expression analysis; Gossypium ssp; Meta-analysis; Transcriptome data

Mesh:

Year:  2019        PMID: 30802474     DOI: 10.1016/j.pbiomolbio.2019.02.005

Source DB:  PubMed          Journal:  Prog Biophys Mol Biol        ISSN: 0079-6107            Impact factor:   3.667


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