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Soybean gene co‐expression network analysis identifies two co‐regulated gene modules associated with nodule formation and development

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Abstract Gene co‐expression network analysis is an efficient systems biology approach for the discovery of novel gene functions and trait‐associated gene modules. To identify clusters of functionally related genes involved… Click to show full abstract

Abstract Gene co‐expression network analysis is an efficient systems biology approach for the discovery of novel gene functions and trait‐associated gene modules. To identify clusters of functionally related genes involved in soybean nodule formation and development, we performed a weighted gene co‐expression network analysis. Two nodule‐specific modules (NSM‐1 and NSM‐2, containing 304 and 203 genes, respectively) were identified. The NSM‐1 gene promoters were significantly enriched in cis‐binding elements for ERF, MYB, and C2H2‐type zinc transcription factors, whereas NSM‐2 gene promoters were enriched in cis‐binding elements for TCP, bZIP, and bHLH transcription factors, suggesting a role of these regulatory factors in the transcriptional activation of nodule co‐expressed genes. The co‐expressed gene modules included genes with potential novel roles in nodulation, including those involved in xylem development, transmembrane transport, the ethylene signalling pathway, cytoskeleton organization, cytokinesis and regulation of the cell cycle, regulation of meristem initiation and growth, transcriptional regulation, DNA methylation, and histone modifications. Functional analysis of two co‐expressed genes using TILLING mutants provided novel insight into the involvement of unsaturated fatty acid biosynthesis and folate metabolism in nodule formation and development. The identified gene co‐expression modules provide valuable resources for further functional genomics studies to dissect the genetic basis of nodule formation and development in soybean.

Keywords: gene; development; gene expression; nodule formation; formation development

Journal Title: Molecular Plant Pathology
Year Published: 2023

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