BMC Plant Biology (Sep 2021)

Genome-wide identification and analysis of WRKY gene family in maize provide insights into regulatory network in response to abiotic stresses

  • Wenjing Hu,
  • Qiaoyu Ren,
  • Yali Chen,
  • Guoliang Xu,
  • Yexiong Qian

DOI
https://doi.org/10.1186/s12870-021-03206-z
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 21

Abstract

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Abstract Background The WRKY transcription factor family plays significant roles in biotic and abiotic stress responses, which has been associated with various biological processes in higher plants. However, very little is known regarding the structure and function of WRKY genes in maize. Results In this study, a total of 140 ZmWRKY proteins encoded by 125 ZmWRKY genes were eventually identified in maize. On the basis of features of molecular structure and a comparison of phylogenetic relationships of WRKY transcription factor families from Arabidopsis, rice and maize, all 140 ZmWRKY proteins in maize were divided into three main groups (Groups I, II and III) and the Group II was further classified into five subgroups. The characteristics of exon-intron structure of these putative ZmWRKY genes and conserved protein motifs of their encoded ZmWRKY proteins were also presented respectively, which was in accordance with the group classification results. Promoter analysis suggested that ZmWRKY genes shared many abiotic stress-related elements and hormone-related elements. Gene duplication analysis revealed that the segmental duplication and purifying selection might play a significant role during the evolution of the WRKY gene family in maize. Using RNA-seq data, transcriptome analysis indicated that most of ZmWRKY genes displayed differential expression patterns at different developmental stages of maize. Further, by quantitative real-time PCR analysis, twenty-one ZmWRKY genes were confirmed to respond to two different abiotic stress treatments, suggesting their potential roles in various abiotic stress responses. In addition, RNA-seq dataset was used to conduct weighted gene co-expression network analysis (WGCNA) in order to recognize gene subsets possessing similar expression patterns and highly correlated with each other within different metabolic networks. Further, subcellular localization prediction, functional annotation and interaction analysis of ZmWRKY proteins were also performed to predict their interactions and associations involved in potential regulatory network. Conclusions Taken together, the present study will serve to present an important theoretical basis for further exploring function and regulatory mechanism of ZmWRKY genes in the growth, development, and adaptation to abiotic stresses in maize.

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