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基于加权基因共表达网络分析挖掘牡丹耐热关键基因。

Mining Heat-Resistant Key Genes of Peony Based on Weighted Gene Co-Expression Network Analysis.

机构信息

College of Landscape Architecture, Central South University of Forestry and Technology, Changsha 410004, China.

College of Art and Design, Nanning University, Nanning 530200, China.

出版信息

Genes (Basel). 2024 Mar 21;15(3):383. doi: 10.3390/genes15030383.

Abstract

The RNA-Seq and gene expression data of mature leaves under high temperature stress of 'Hu Hong' were used to explore the key genes of heat tolerance of peony. The weighted gene co-expression network analysis (WGCNA) method was used to construct the network, and the main modules and core genes of co-expression were screened according to the results of gene expression and module function enrichment analysis. According to the correlation of gene expression, the network was divided into 19 modules. By analyzing the expression patterns of each module gene, Blue, Salmon and Yellow were identified as the key modules of peony heat response related functions. GO and KEGG functional enrichment analysis was performed on the genes in the three modules and a network diagram was constructed. Based on this, two key genes (TRINITY_DN60998_c1_g2, TRINITY_DN71537_c0_g1) and (TRINITY_DN56794_c0_g1) were excavated, which may play a key role in the heat shock response of peony. The three co-expression modules and two key genes were helpful to further elucidate the heat resistance mechanism of 'Hu Hong'.

摘要

利用 '胡红' 牡丹高温胁迫下成熟叶片的 RNA-Seq 和基因表达数据,探讨牡丹耐热性的关键基因。采用加权基因共表达网络分析(WGCNA)方法构建网络,根据基因表达和模块功能富集分析结果筛选共表达的主要模块和核心基因。根据基因表达的相关性,将网络分为 19 个模块。通过分析每个模块基因的表达模式,鉴定出蓝色、鲑鱼色和黄色模块与牡丹耐热相关功能有关。对三个模块中的基因进行 GO 和 KEGG 功能富集分析,并构建网络图。在此基础上,挖掘出两个关键基因(TRINITY_DN60998_c1_g2、TRINITY_DN71537_c0_g1)和(TRINITY_DN56794_c0_g1),它们可能在牡丹的热休克反应中发挥关键作用。这三个共表达模块和两个关键基因有助于进一步阐明 '胡红' 的耐热机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4d5/10970469/cfc917fe1796/genes-15-00383-g001.jpg

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