Genetics Selection EvolutionBioinformaticsPeer-reviewed journal article
The application of mixed linear models for the estimation of functional effects on bovine stature based on SNP summary statistics from a whole-genome association study
Krzysztof KotlarziD, Barbara Kosińska-SelbiiD, Zexi CaiiD, Goutam SahanaiD, Joanna SzydaiD
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Abstract
Genome-Wide Association Studies (GWAS) help identify polymorphic sites or genes linked to phenotypic variance, but a few identified genes / Single Nucleotide Polymorphisms are unlikely to explain a large part of the phenotypic variability of complex traits. In this study, the focus was moved from single loci to functional units, expressed by the metabolic pathways: Kyoto Encyclopaedia of Genes and Genomes (KEGG). Consequently, this study aimed to estimate KEGG effects on stature in three Nordic dairy cattle breeds using SNPs effects from GWAS as the dependent variable. The SNPs were annotated to genes, then the genes to KEGG pathways. The effects of KEGG were estimated separately for each breed using a mixed linear model incorporating the similarity between pathways expressed by common genes. The KEGG pathway D-amino acid metabolism (map00473) was estimated as significant on stature in two of the analysed breeds and revealed a borderline significance in the third breed. Interestingly, biological evidence exists that described the importance of D-amino acids for growth in experimental organisms as well as in cattle.
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- research focus: fine-mapping
- approach: statistical model
- approach: mixed model
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