Using weighted gene co-expression network analysis (WGCNA) to identify the hub genes related to hypoxic adaptation in yak (Bos grunniens)

文献类型： 外文期刊

第一作者： Bao, Qi

作者： Bao, Qi;Zhang, Xiaolan;Bao, Pengjia;Liang, Chunnian;Guo, Xian;Chu, Min;Yan, Ping;Bao, Qi;Zhang, Xiaolan;Bao, Pengjia;Liang, Chunnian;Guo, Xian;Chu, Min;Yan, Ping

作者机构：

关键词： Hypoxia adaptability; Bos grunniens; WGCNA; Hub gene

期刊名称：GENES & GENOMICS （ 影响因子：1.839； 五年影响因子：1.329 ）

ISSN： 1976-9571

年卷期： 2021 年 43 卷 10 期

页码：

收录情况： SCI

摘要： Background As a mammal living at the highest altitude in the world, the yak has strong adaptability to the harsh natural environment (such as low temperature, scarce food, especially low oxygen) of Qinghai-Tibet Plateau (QTP) after a long process of natural selection. Objective Here, we used Weighted Correlation Network Analysis (WGCNA), a systematic biology method, to identify hypoxic adaptation-related modules and hub genes. The research of the adaptability of yak against hypoxia is of great significance to identify the genetic characteristics and yak breeding. Methods Based on the transcriptome sequencing data (PRJNA362606), the R package DESeq2 and WGCNA were conducted to analyze differentially expressed genes (DEGs) and construct the gene co-expression network. The module hub genes were identified and characterized by the correlation of gene and trait, module membership (kME). In addition, GO and KEGG enrichment analyses were used to explore the functions of hub genes. Results Our results revealed that 1098, 1429, and 1645 DEGs were identified in muscle, spleen, and lung, respectively. Besides, a total of 13 gene co-expression modules were detected, of which two hypoxic adaptation-related modules (saddlebrown and turquoise) were found. We identified 39 and 150 hub genes in these two modules. Functional enrichment analyses showed that 12 GO terms and 18 KEGG pathways were enriched in the saddlebrown module while 85 GO terms and 22 KEGG pathways were enriched in the turquoise module. The significant pathways related to hypoxia adaptation include FoxO signaling pathway, Thermogenesis pathway, and Retrograde endocannabinoid signaling pathway, etc. Conclusions In this study, we obtained two hypoxia-related specific modules and identified hub genes based on the connectivity by constructing a weighted gene co-expression network. Function enrichment analysis of two modules revealed mitochondrion is the most important organelle for hypoxia adaptation. Moreover, the insulin-related pathways and thermogenic-related pathways played a major role. The results of this study provide theoretical guidance for further understanding the molecular mechanism of yak adaptation to hypoxia.

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