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