WRKY transcription factors govern selenium metabolism in Broussonetia papyrifera: genome-wide identification, expression profiling, and regulatory network analysis

Broussonetia papyrifera, a novel forage tree species, exhibits a notable ability to accumulate selenium, making it a viable option for selenium enrichment feed. Nevertheless, the molecular mechanisms governing selenium metabolism in this tree are poorly understood, hindering its further development as a selenium accumulator. This study revealed 47 WRKY transcription factors from the B. papyrifera genome. These WRKY transcription factors were characterized by their gene structure, protein domains, and synteny analysis across different species. Based on the phylogenetic analysis, these WRKY genes were categorized into three distinct subfamilies. By integrating transcriptomic and physiological data, nine WRKY genes were strongly correlated with selenium. Subsequently, quantitative qRT-PCR results further confirmed BpWRKY34 and BpWRKY25 as potential regulators of selenium metabolism in B. papyrifera, subcellular localization studies indicated that BpWRKY34 and BpWRKY25 were functional in the cell nucleus. Furthermore, we identified several miRNAs that potentially target WRKY family members. Co-expression network analysis revealed downstream enzymatic networks functionally linked to WRKY transcription factors in the selenium metabolic pathway of B. papyrifera. The integrated analysis of BpWRKY genes identified candidate genes that regulate selenium metabolism, offering a theoretical foundation for developing Se-enriched B. papyrifera through genetic improvement.

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Journal
BMC Plant Biology
Published
2026-02-26
DOI
https://doi.org/10.1186/s12870-026-08407-y
Primary Topic
Plant Gene Expression Analysis
Type
article
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article

WRKY transcription factors govern selenium metabolism in Broussonetia papyrifera: genome-wide identification, expression profiling, and regulatory network analysis

Qiangwen Chen, Shiming Deng, Jie Li, Xin Cong et al.
BMC Plant Biology
Plant Gene Expression Analysis
article

WRKY transcription factors govern selenium metabolism in Broussonetia papyrifera: genome-wide identification, expression profiling, and regulatory network analysis

Qiangwen Chen, Shiming Deng, Jie Li, Xin Cong, Weiwei Zhang, Huimin He, Shuiyuan Cheng, Feng Xu
article en

Abstract

Broussonetia papyrifera, a novel forage tree species, exhibits a notable ability to accumulate selenium, making it a viable option for selenium enrichment feed. Nevertheless, the molecular mechanisms governing selenium metabolism in this tree are poorly understood, hindering its further development as a selenium accumulator. This study revealed 47 WRKY transcription factors from the B. papyrifera genome. These WRKY transcription factors were characterized by their gene structure, protein domains, and synteny analysis across different species. Based on the phylogenetic analysis, these WRKY genes were categorized into three distinct subfamilies. By integrating transcriptomic and physiological data, nine WRKY genes were strongly correlated with selenium. Subsequently, quantitative qRT-PCR results further confirmed BpWRKY34 and BpWRKY25 as potential regulators of selenium metabolism in B. papyrifera, subcellular localization studies indicated that BpWRKY34 and BpWRKY25 were functional in the cell nucleus. Furthermore, we identified several miRNAs that potentially target WRKY family members. Co-expression network analysis revealed downstream enzymatic networks functionally linked to WRKY transcription factors in the selenium metabolic pathway of B. papyrifera. The integrated analysis of BpWRKY genes identified candidate genes that regulate selenium metabolism, offering a theoretical foundation for developing Se-enriched B. papyrifera through genetic improvement.

BMC Plant Biology
Wuhan Polytechnic University (CN), Minzu University of China (CN), Yangtze University (CN), Hubei University for Nationalities (CN), Minda Hospital (CN), Hubei University (CN)
Openalex Percentile: Top 41%
Plant Gene Expression Analysis
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