Application Of Pathway-based Genome-wide Association Studies In Simmental Cattle

With the development of genome sequencing and high throughput SNP genotyping technologies, Genome-wide association studies(GWAS) have been proved to be a powerful tool to detect genes associated with complex disease in humans or economically important traits in domestic animals. Many genetics variations, mostly in form of single nucleotide polymorphisms(SNPs), have been identified associated with human disease traits or economically important traits of livestock. However, a common theme arising from these studies is that the genetic varaitions discovered by GWAS can only explain a small fraction of the genetic risks associated with the trait of interest, but complex quantitative traits are usually determined by many genes with small effects, results of single SNP cannot explain all of the genotypic variation. Thus, new strategies and statistical approaches are needed to address this lack of explanation. One such approach is pathway-based GWAS analysis, which considers the genetic variations underlying a biological pathway, rather than separately in traditional GWA studies. With the development of this strategy, several algorithms for pathway-based GWAS have been developed. However, most of the current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene.In this study, we present a new pathway based enrichment method for GWAS to solve this problem.This method mainly consists of following two steps: 1) for a given pathway, using the principal component analysis(PCA) strategy to extract principal component(PC) matrix of each gene, then ranking all of these PCs by the significance of their statistical association with a trait of interest; 2) calculating the gene’s statistical value using Maxmean method, and testing if the set of genes from a particular pathway is significantly enriched with high ranks using weighted Kolmogorov-Smirnov. Based on the dataset with approximately 7,700,000 SNPs for 807 Simmental cattles, live weight and longissimus muscle area were analyzed with our modified pathway-based GWAS method. As a result, of 263 biologic pathways for cattle collected form KEGG database, the GABAergic synapse pathway and Non-alcoholic fatty liver disease(NAFLD) pathway were identified to be significantly associated with two analyzed traits. The results corresponded to biological roles of the GABAergic synapse pathway in animal feed intake and weight gain process.Our SNP-based pathway enrichment method firstly take away the linkage disequilibrium among SNPs in genes, may provide a new alternative approach for pathway-based GWAS analysis, and more importantly, this is a pathway-based GWAS analysis in cattle, our findings may provide some useful significant pathways regarding the important meat production traits in cattle.