Selection signature analysis in chickens divergently selected for growth rate reveals novel candidate genes...

Decades of intensive breeding for rapid growth rate has resulted in increased abdominal fat content in commercial broilers, which also led to significant economic loss in this industry. In the present study, we integrated RNA-Seq datasets of 44 samples, including 22 fat- and 22 lean-line, to identify the selection signatures linked to abdominal fat content in chickens.

In total, 68 selection signature regions in the top 0.1% were screened out via Fst analysis on chromosomes 1, 2, 4, 5, 9, 11, 13, 15, and 18 were identified under differential selection between fat- and lean-lines, which harbored 1,140 SNPs and 44 genes. Functional annotation analysis highlighted key biological processes and KEGG pathways related to fat metabolism, such as "Fatty Acid Metabolic Process", "Lipid Import Into Cell", "Triglyceride Biosynthetic Process" and "Long-Chain Fatty Acid Transport". The results confirmed several previously reported candidate genes involved in fat deposition, such as ACSL3, ACSF2, MOGAT1, TBXAS1, and NDST4. Notably, the NDST4 and YIPF7 genes were of particular interest, as they are closely linked with the QTLs associated with fatness traits, which makes them well suited for future applications in poultry breeding programs. Moreover, some novel candidate genes associated with fat metabolism were identified, including GUF1, GNPDA2, SLC25A48, RBFOX3, FRMD4A and KCNE4. While the exact mechanisms by which novel candidate genes contribute to abdominal fat deposition are not fully understood yet, but they appear to play relevant roles in fat metabolism that make them promising candidates for further investigations. Furthermore, the identified candidate regions harbored two miRNAs, of which mir-205b is of particular interest and can be considered as a potential candidate involved in the genetic control of abdominal fat deposition, as mainly participate in pathways associated with lipid metabolism. These genes can pave the way for the optimization of the breeding programs associated with fatness to promote chicken broilers performance.

Overall, these findings enrich our understanding of the genetic mechanisms underlying abdominal fat deposition in chickens. Of note, our approach for selection signature analysis can be applied to other traits as well as species with available RNA-Seq data to identify the genomic signals associated with the divergence of different phenotypes.