Genome-wide identification of WRKY transcription factors in kiwifruit (Actinidia spp.) and analysis of WRKY expression in responses to biotic and abiotic stresses
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As one of the largest transcriptional factor families in plants, WRKY transcription factors play important roles in various biotic and abiotic stress responses. To date, WRKY genes in kiwifruit (Actinidia spp.) remain poorly understood. In our study, o total of 97 AcWRKY genes have been identified in the kiwifruit genome. An overview of these AcWRKY genes is analyzed, including the phylogenetic relationships, exon–intron structures, synteny and expression profiles. The 97 AcWRKY genes were divided into three groups based on the conserved WRKY domain. Synteny analysis indicated that segmental duplication events contributed to the expansion of the kiwifruit AcWRKY family. In addition, the synteny analysis between kiwifruit and Arabidopsis suggested that some of the AcWRKY genes were derived from common ancestors before the divergence of these two species. Conserved motifs outside the AcWRKY domain may reflect their functional conservation. Genome-wide segmental and tandem duplication were found, which may contribute to the expansion of AcWRKY genes. Furthermore, the analysis of selected AcWRKY genes showed a variety of expression patterns in five different organs as well as during biotic and abiotic stresses. The genome-wide identification and characterization of kiwifruit WRKY transcription factors provides insight into the evolutionary history and is a useful resource for further functional analyses of kiwifruit.
KeywordsAbiotic and biotic stress Evolution Expression profile Kiwifruit Phylogenetic analysis WRKY genes
This work was supported by the earmarked fund for China Postdoctoral Science Foundation (2015M582712), Postdoctoral Science Foundation of Shaanxi Province (2016BSHYDZZ07), Science and Technology Research and Development Program of Shaanxi Province (2015KTZDNY02-03-01, 2016KJXX-58). We thank AJE (https://www.aje.com/) for editing this manuscript, Chunlei Guo, Li Wang, Jinhua Yang, and Jiao Zhao for teaching data analysis.
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Conflict of interest
Zhaobin Jing, Zhande Liu declares that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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