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

Prog Biophys Mol Biol

School of Animal and Veterinary Sciences, The University of Adelaide, Adelaide, SA, Australia; Genomics Research Platform, La Trobe University, Melbourne, Victoria 3086, Australia; Division of Information Technology, Engineering and the Environment, School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, SA, Australia; Faculty of Science and Engineering, School of Biological Sciences, Flinders University, Adelaide, SA, Australia.

Published: September 2019

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.

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http://dx.doi.org/10.1016/j.pbiomolbio.2019.02.005DOI Listing

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