WGCNA鉴定奶山羊妊娠至泌乳期乳腺发育关键基因

doi:10.11843/j.issn.0366-6964.2020.11.007

摘要/Abstract

摘要： 旨在通过加权基因共表达网络分析（weighted gene co-expression network analysis，WGCNA）筛选奶山羊不同生理阶段乳腺发育的关键基因。本研究从GEO数据库中下载奶山羊不同生理阶段（妊娠46天、70天、90天、110天和产后40天）的乳腺组织微阵列数据集GSE14008，使用R语言的WGCNA包对数据进行共表达分析。将得到的模块与生理阶段进行关联分析，选择目标模块，并根据连接度选出枢纽基因。使用DAVID网站对模块进行富集分析后，使用String网站构建模块的蛋白互作网络，并使用Cytoscape软件得到核心基因，最终与枢纽基因取交集得到目标基因。对18个样本的8 443个基因进行加权基因共表达分析，得到30个模块，并选出4个与不同生理阶段相关的目标模块及每个模块的30个枢纽基因，同时也得到4个模块的蛋白互作网络及每个网络的20个核心基因。最终，4个模块共得到13个与乳腺发育相关的目标基因（UQCR、RGL2、NOTCH1、PTBP1、PPP5C、FZR1、UBE2L3、TNF、MAT2A、ITGB2、GPR18、JAK1、CSN2）。本研究通过WGCNA、GO富集分析和PPI网络等生物信息学技术，阐明了不同生理时期乳腺发育的关键过程，及在这些过程中起关键作用的基因，这为进一步研究乳腺发育机制提供了新的思路和线索。

关键词: 加权基因共表达网络分析, 乳腺发育, 妊娠期, 泌乳期, 山羊

Abstract: The purpose of this study was to select the key genes of mammary gland development at different physiological stages in dairy goats by weighted gene co-expression network analysis(WGCNA). GSE14008 mammary gland tissue microarray data set of dairy goats at different physiological stages (pregnancy 46 days, 70 days, 90 days, 110 days and 40 days postpartum) was downloaded from GEO database, and co-expression analysis was carried out using WGCNA package of R language. The target modules were selected by correlation analysis between the modules and physiological stages, and the hub genes were selected according to the connectivity degree. After enrichment analysis of the modules using DAVID website, the protein-protein interaction network of the modules was constructed using String website and the core genes were obtained using Cytoscape software, and finally the target genes were obtained from intersection of core genes and hub genes. A total of 8 443 genes from 18 samples were analyzed for co-expression of weighted genes. The 30 modules were obtained, and 4 target modules related to different physiological stages and 30 hub genes of each module were selected. Meanwhile, protein-protein interaction network of 4 modules and 20 core genes of each network were also obtained. Finally, 13 target genes related to mammary gland development were obtained from the 4 modules, which were UQCR, RGL2, NOTCH1, PTBP1, PPP5C, FZR1, UBE2L3, TNF, MAT2A, ITGB2, GPR18, JAK1 and CSN2 genes. The key processes of mammary gland development at different physiological stages and the genes that played the key role in these processes were elucidated by WGCNA, GO enrichment analysis, PPI network and other bioinformatics techniques, which provided a new idea and clue for the further research on the mechanism of mammary gland development.

Key words: WGCNA, mammary gland development, pregnancy, lactation, goat

中图分类号:

S827.2

高慧杰, 郑惠玲. WGCNA鉴定奶山羊妊娠至泌乳期乳腺发育关键基因[J]. 畜牧兽医学报, 2020, 51(11): 2679-2688.

GAO Huijie, ZHENG Huiling. Identification of Key Genes of Mammary Gland Development from Pregnancy to Lactation in Dairy Goats by WGCNA[J]. Acta Veterinaria et Zootechnica Sinica, 2020, 51(11): 2679-2688.

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