Wang Qiuju, Gao Bingnan, Yue Xueqing, Cui Yizhe, Loor Juan J, Dai Xiaoxia, Wei Xu, Xu Chuang
College of Animal Science and Technology, Heilongjiang Bayi Agricultural University, Daqing, China.
Key Laboratory of Low-Carbon Green Agriculture in Northeastern China, Ministry of Agriculture and Rural Affairs P. R. China, Heilongjiang Bayi Agricultural University, Daqing, China.
Front Vet Sci. 2022 Jun 10;9:897714. doi: 10.3389/fvets.2022.897714. eCollection 2022.
Weighted gene co-expression network analysis (WGCNA) was used to understand the pathogenesis of subacute ruminal acidosis (SARA) and identify potential genes related to the disease. Microarray data from dataset GSE143765, which included 22 cows with and nine cows without SARA, were downloaded from the NCBI Gene Expression Omnibus (GEO). Results of WGCNA identified highly correlated modules of sample genes, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses allowed further biological insights into SARA-related modules. The protein-protein interaction (PPI) network, modules from the PPI network, and cistron annotation enrichment of modules were also analyzed. A total of 14,590 DEGs were used for the WGCNA. Construction of a protein-protein network identified , and as hub genes. Functional annotation showed that mainly exhibited L-xylulose reductase (NADP+) activity, glucose metabolic process, xylulose metabolic process, and carbonyl reductase (NADPH) activity, which are involved in the pentose and glucuronate interconversion pathways. and mainly have a collagen catabolic process. Overall, the results of this study aid the clarification of the biological and metabolic processes associated with SARA at the molecular level. The data highlight potential mechanisms for the future development of intervention strategies to reduce or alleviate the risk of SARA.
加权基因共表达网络分析（WGCNA）被用于了解亚急性瘤胃酸中毒（SARA）的发病机制，并识别与该疾病相关的潜在基因。从NCBI基因表达综合数据库（GEO）下载了数据集GSE143765的微阵列数据，其中包括22头患有SARA的奶牛和9头未患SARA的奶牛。WGCNA的结果确定了样本基因的高度相关模块，基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析为与SARA相关的模块提供了进一步的生物学见解。还分析了蛋白质-蛋白质相互作用（PPI）网络、PPI网络中的模块以及模块的顺反子注释富集情况。总共14590个差异表达基因用于WGCNA。蛋白质-蛋白质网络的构建确定了 和 作为枢纽基因。功能注释表明， 主要表现出L-木酮糖还原酶（NADP+）活性、葡萄糖代谢过程、木酮糖代谢过程以及羰基还原酶（NADPH）活性，这些都参与戊糖和葡萄糖醛酸相互转化途径。 和 主要具有胶原蛋白分解代谢过程。总体而言，本研究结果有助于在分子水平上阐明与SARA相关的生物学和代谢过程。这些数据突出了未来开发干预策略以降低或减轻SARA风险的潜在机制。
