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Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes
Journal of Animal Science and Biotechnology ( IF 7 ) Pub Date : 2021-08-20 , DOI: 10.1186/s40104-021-00616-9
Kai Xing 1 , Huatao Liu 2 , Fengxia Zhang 2 , Yibing Liu 2 , Yong Shi 2 , Xiangdong Ding 2 , Chuduan Wang 2
Affiliation  

Fat deposition is an important economic consideration in pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers’ choice of pork. Weighted gene co-expression network analysis (WGCNA) is effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low) and to identify the core genes in each of these modules. We used RNA sequences generated in different pig tissues to construct a gene expression matrix consisting of 12,862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA and the number of genes in these modules ranged from 39 to 3,363. Four co-expression modules were significantly correlated with backfat thickness. A total of 16 genes (RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN) were associated with fat deposition. RAD9A, TCAP, SMYD1, PFKM, GPS2, and APOF were the key genes in the four modules based on the degree of gene connectivity. Combining these results with those from differential gene analysis, SMYD1 and PFKM were proposed as strong candidate genes for body size traits. This study explored the key genes that regulate porcine fat deposition and lays the foundation for further research into the molecular regulatory mechanisms underlying porcine fat deposition.

中文翻译:

基于加权基因共表达网络分析的影响猪脂肪沉积关键基因的鉴定

脂肪沉积是养猪生产中一个重要的经济考虑因素。猪体内脂肪沉积量严重影响生产效率、质量和繁殖性能,同时也影响消费者对猪肉的选择。加权基因共表达网络分析 (WGCNA) 在猪遗传研究中很有效。因此,本研究旨在确定与极端背膘水平(高和低)猪(松辽黑和长白品种)脂肪沉积相关基因的共表达模块,并确定每个模块中的核心基因。我们使用在不同猪组织中产生的 RNA 序列构建了一个基因表达矩阵,该矩阵由来自 36 个样本的 12,862 个基因组成。使用 WGCNA 鉴定了 11 个共表达模块,这些模块中的基因数量从 39 到 3,363 不等。四个共表达模块与背膘厚度显着相关。共有 16 个基因(RAD9A、IGF2R、SCAP、TCAP、SMYD1、PFKM、DGAT1、GPS2、IGF1、MAPK8、FABP、FABP5、LEPR、UCP3、APOF 和 FASN)与脂肪沉积相关。RAD9A、TCAP、SMYD1、PFKM、GPS2和APOF是基于基因连接程度的四个模块中的关键基因。将这些结果与差异基因分析的结果相结合,SMYD1 和 PFKM 被认为是体型特征的有力候选基因。本研究探索了调控猪脂肪沉积的关键基因,为进一步研究猪脂肪沉积的分子调控机制奠定了基础。FABP5、LEPR、UCP3、APOF 和 FASN)与脂肪沉积有关。RAD9A、TCAP、SMYD1、PFKM、GPS2和APOF是基于基因连接程度的四个模块中的关键基因。将这些结果与差异基因分析的结果相结合,SMYD1 和 PFKM 被认为是体型特征的有力候选基因。本研究探索了调控猪脂肪沉积的关键基因,为进一步研究猪脂肪沉积的分子调控机制奠定了基础。FABP5、LEPR、UCP3、APOF 和 FASN)与脂肪沉积有关。RAD9A、TCAP、SMYD1、PFKM、GPS2和APOF是基于基因连接程度的四个模块中的关键基因。将这些结果与差异基因分析的结果相结合,SMYD1 和 PFKM 被认为是体型特征的有力候选基因。本研究探索了调控猪脂肪沉积的关键基因,为进一步研究猪脂肪沉积的分子调控机制奠定了基础。SMYD1 和 PFKM 被提议作为体型特征的有力候选基因。本研究探索了调控猪脂肪沉积的关键基因,为进一步研究猪脂肪沉积的分子调控机制奠定了基础。SMYD1 和 PFKM 被提议作为体型特征的有力候选基因。本研究探索了调控猪脂肪沉积的关键基因,为进一步研究猪脂肪沉积的分子调控机制奠定了基础。
更新日期:2021-08-21
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