The g.841G>C SNP of FASN gene is associated with fatty acid composition in beef cattle.

The objective of the current study is to evaluate the association between fatty acid composition and fatty acid synthase gene polymorphisms as responsible mutations. For this purpose, we selected seven previously reported single nucleotide polymorphisms (SNPs) in FASN gene, including one within promoter region (g.841G>C) and six non-synonymous SNPs (g.8805C>T, g.13126C>T, g.15532A>C, g.16024A>G, g.16039C>T, g.17924A>G), and genotyped them in Japanese Black cattle. Genotyping results revealed that g.8805 C>T and g.17924 A>G were monomorphic loci. Genome-wide association analysis including the other five SNPs revealed that only g.841G>C showed significant associations with the percentages of C14:0, C14:1, C16:1 and C18:1 at 5% genome-wide significance level. In order to further evaluate the effect, we genotyped g.841G>C using additional three populations, including two Japanese Black populations and a Holstein cattle population. g.16024A>G was also genotyped and included in the analysis because it has been reported to be associated with fatty acid composition in Japanese Black cattle. In the result of analysis of variance, g.841G>C showed stronger effects on fatty acid percentage than those of g.16024A>G in all populations. These results suggested that g.841G>C would be a responsible mutation for fatty acid composition and contribute to production of high-grade beef as a selection marker in beef cattle.

Genome-wide association study for fatty acid composition in Japanese Black cattle.

Fatty acid composition is one of the important traits in beef. The aim of this study was to identify candidate genomic regions for fatty acid composition by genome-wide association study with 50 K single nucleotide polymorphism (SNP) array in Japanese Black cattle. A total of 461 individuals and 40 657 SNPs were used in this study. We applied genome-wide rapid association using mixed model and regression (GRAMMAR) and genomic control approaches to estimate the associations between genotypes and fatty acid composition. In addition, two SNPs in fatty acid synthase (FASN) (T1952A) and stearoyl-CoA desaturase (SCD) (V293A) genes were also genotyped. Association analysis revealed that 30 significant SNPs for several fatty acids (C14:0, C14:1, C16:1 and C18:1) were located in the BTA19 FASN gene located within this region but the FASN mutation had no significant effect on any traits. We also detected one significant SNP for C18:1 on BTA23 and two SNPs for C16:0 on BTA25. The region around 17 Mb on BTA26 harbored two significant SNPs for C14:1 and SNP in SCD in this region showed the strongest association with C14:1. This study demonstrated novel candidate regions in BTA19, 23 and 25 for fatty acid composition.

Identification of divergently selected regions between Japanese Black and Holstein cattle using bovine 50k SNP array.

Differences between average allelic frequencies of genes that relate to traits suggest that it would be evidence of artificial selections. Sliding window approach is a useful method to identify genomic regions that have been differently selected between two breeds. The objective of this study was to identify the divergently selected regions between Japanese Black (JB) and Japanese Holstein (JH) cattle based on genotypic information obtained through a high-density single nucleotide polymorphism (SNP) panel. After genotyping of 54 001 SNP markers on 100 animals (50 JB and 50 JH), 40 635 SNPs were suitable for the analysis. For each of these SNPs, the absolute difference between allelic frequencies of JB and JH was calculated. In the current study, 10 consecutive SNPs were defined as components of a window. For each window, the average difference in allelic frequency was calculated. This was termed sliding window average difference (SWAD). Among 40 055 windows, we focused on 39 windows with the largest SWAD. This was equivalent to 0.1% of all windows and the SWAD was more than 0.435. Some of these windows overlapped and were distributed in 11 regions. These regions were in good agreement with reported quantitative trait locus, therefore would be selection signatures and good candidates that harbor the causative mutations.