AI Summary & Key Takeaways
AI InsightThese findings have significant implications for the understanding of the way in which common ancestors and/or the presence of quantitative trait loci might affect the accuracy of the GP results.
📌 3 Key Takeaways
Abstract
Body weight BW is an important heritable phenotype and related to other functional and production traits in cattle. The past decade has seen an increase in emphasis on genome wide association studies GWAS for detecting single nucleotide polymorphisms SNPs that are associated with quantitative phenotypes. Prediction of phenotypes using across-breed GWAS information [genomic prediction GP ] is an also important research area but received less attention from the community. Understanding the link between major genes and common ancestors within and between breeds will contribute to a deeper understanding of GP across breeds. The aims of the present study were two-fold: 1 to examine genetic structure and to detect associated SNPs for BW using various single and multiple locus genomic models and 2 genomic prediction of BW using Siberian cattle populations based on across-breed genomic information. The most obvious finding to emerge from this study was the increase in the across-GP accuracy when gene segregation in both related populations was found. These findings have significant implications for the understanding of the way in which common ancestors and/or the presence of quantitative trait loci might affect the accuracy of the GP results.