Gene-gene interactions of fatty acid synthase (FASN) using multifactor-dimensionality reduction method in Korean...

We examined the gene-gene interactions of five exonic single nucleotide polymorphisms (SNPs) in the gene encoding fatty acid synthase using 513 Korean cattle and using the model free and the non-parametrical multifactor dimensionality reduction method for the analysis. The five SNPs of g.12870 T>C, g.13126 T>C, g.15532 C>A, g.16907 T>C and g.17924 G>A associated with a variety of fatty acid compositions and marbling score were used in this study. The two-factor interaction between g.13126 T>C and g.15532 C>A had the highest training-balanced among the five-factor models and a testing-balanced accuracy at 70.18 % on C18:1 with a cross-validation consistency of 10 out of 10. Also, the two-factor interaction between g.13126 T>C and g.15532 C>A had the highest testing-balanced accuracy at 68.59 % with a 10 out of 10 cross-validation consistency, than any other models on MUFA. In MS, a single SNP g.15532 C>A had the best accuracy at 58.85 % and the two-factor interaction model g.12870 T>C and g.15532 C>A had the highest testing-balanced accuracy at 64.00 %. The three-factor interaction model g.12870 T>C, g.13126 T>C and g.15532 C>A was recorded as having a high testing-balanced accuracy of 63.24 %, but it was lower than the two-factor interaction model. We used likelihood ratio tests for interaction, and Chi square tests to validate our results, with all tests showing statistical significance. We also compared this with mean scores between the high-risk trait group and low-risk trait group. The genotypes of TTCA, TTAA and TCAA at g.15532 and g.13126 on C18:1, genotypes TTCC, TTCA, TTAA, TCAA CCAA at g.15532 and g.13126 on MUFA and genotypes CCCC, TCCA, CCCA, TTAA, TCAA and CCAA at g.15532 and g.12870 on MS were recommended for the genetic improvement of beef quality.