2023
DOI: 10.1111/mpp.13327
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Soybean gene co‐expression network analysis identifies two co‐regulated gene modules associated with nodule formation and development

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, MY… Show more

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Cited by 4 publications
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“…For expression profiling of the candidate genes, the publicly available RNA-seq datasets were used. Description and accession number of these RNA-seq datasets were provided in Piya et al. (2023) .…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…For expression profiling of the candidate genes, the publicly available RNA-seq datasets were used. Description and accession number of these RNA-seq datasets were provided in Piya et al. (2023) .…”
Section: Methodsmentioning
confidence: 99%
“…Heatmap plot was created by the PhytoMine tool ( https://phytozome.jgi.doe.gov ) presented at the Phytozome v12 website ( https://phytozome.jgi.doe.gov ). Gene expression analysis and heatmap plot construction were performed as described in Piya et al. (2023) .…”
Section: Methodsmentioning
confidence: 99%