RNA-Seq based selection signature analysis for identifying genomic footprints associated with the fat-tail phenotype in sheep

Understanding the genetic background behind fat-tail development in sheep can be useful to develop breeding programs for genetic improvement, while the genetic basis of fat-tail formation is still not well understood. Here, to identify genomic regions influencing fat-tail size in sheep, a comprehensive selection signature identification analysis was performed through comparison of fat- and thin-tailed sheep breeds. Furthermore, to gain the first insights into the potential use of RNA-Seq for selection signature identification analysis, SNP calling was performed using RNA-Seq datasets. In total, 45 RNA-Seq samples from seven cohort studies were analyzed, and the F ST method was used to detect selection signatures. Our findings indicated that RNA-Seq could be of potential utility for selection signature identification analysis. In total, 877 SNPs related to 103 genes were found to be under selection in 92 genomic regions. Functional annotation analysis reinforced the hypothesis that genes involved in fatty acid oxidation May modulate fat accumulation in the tail of sheep and highlighted the potential regulatory role of angiogenesis process in the fat deposition. In agreement with most previous studies, our results re-emphasize that the BMP2 gene is targeted by selection during sheep evolution. Further gene annotation analysis of the regions targeted by the sheep evolution process revealed that a large number of genes included in these regions are directly associated with fat metabolism, including those previously reported as candidates involved in sheep fat-tail morphology, such as NID2 , IKBKG , RGMA, IGFBP7, UBR5, VEGFD and WLS . Moreover, a number of genes, including BDH2 , ECHS1 , AUH , ERBIN and CYP4V2 were of particular interest because they are well-known fat metabolism-associated genes and are considered novel candidates involved in fat-tail size. Consistent with the selection signature identification analysis, principal component analysis clustered the samples into two completely separate groups according to fat- and thin-tailed breeds. Our results provide novel insights into the genomic basis of phenotypic diversity related to the fat-tail of sheep breeds and can be used to determine directions for improving breeding strategies in the future.