Identification of central regulators related to residual feed intake in Huainan chickens based on weighted gene...

The residual feed intake (RFI) is a crucial economic trait in chickens. However, the genetic network and regulatory mechanisms that underpin RFI traits and the effects of RFI on meat quality and slaughter performance in chickens remain unclear. In this study, a total of 315 male Huainan chickens were reared from 7 to 13 weeks of age, and feed intake and weight gain were recorded for each individual bird. Based on the calculated RFI values, the 30 chickens with the highest RFI values are classified into the high residual feed intake (HRFI) group, while the 30 chickens with the lowest RFI values are classified into low residual feed intake (LRFI) group. The results revealed a significantly lower abdominal fat percentage in the LRFI group; however, no significant differences were detected in other meat quality traits or slaughter performance parameters. This phenotypic difference may be associated with the high expression of PCK1 in the HRFI group, which is likely to enhance glucose metabolism and thereby promote abdominal fat deposition. Two groups randomly selected 9 samples each for RNA seq analysis. The obtained transcriptome data were subjected to differential gene expression analysis, which revealed that 170 genes exhibited down-regulation while 109 genes displayed up-regulation in HRFI group relative to LRFI group. A total of 23097 genes were used to construct the weighted gene co-expression network analysis (WGCNA), and 27 co-expression gene modules were identified. Among these modules, the magenta module (R = 0.66, P = 0.003) has a significant positive correlation with RFI, while the pink module(R=﹣0.6,P = 0.009) has a significant negative correlation. The hub genes within the above modules were identified based on MM > 0.8 and GS > 0.4. Combining differential and hub genes, 56 key genes were identified as being significantly correlated with RFI traits. Several genes were identified as central regulator genes due to their involvement in the regulation of mitochondrial function (e.g., ACE2, ACMSD), glucose metabolism (e.g., FABP2, FETUB, PCK1) and lipid metabolism (e.g., APOA1). The findings will contribute to a more profound comprehension of the genetic expression and regulation of RFI traits, thereby providing a foundation for genetic breeding.