Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes.

ABSTRACT:

Background

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.

Results

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

SUBMITTER: Xing K 

PROVIDER: S-EPMC8379819 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature