Marker-assisted and Genomic Selection of Beef Cattle

Abstract

This article provides an overview of modern genetic technologies for improving production traits and predicting breeding value in beef cattle. In particular, in marker-assisted selection the most promising is the selectionby desirable genotypes in the genes of myostatin (MSTN), calpain (CAPN), calpastatin (CAST), growth hormone (GH), leptin (LEP), thyroglobulin (TG), fatty acid binding protein (FABP), retinoic acid C-receptor (RORC), diacyl-glycerol acyltransferase (DGATI), sterol-Co desaturase (SCD). A modern and much more advanced approach is the Single Step Genomic Best Linear Unbiased Predictions (ssGBLUP) method, which calculates a Genomic Estimated Breeding Value (GEBV) using DNA chip genotyping, phenotype and pedigree data. Genome-wide association studies (GWAS), based on the use of genetic markers distributed throughout the genome and in non-equilibrium linkage with at least one of the quantitative traits, are currently recognised as more informative for finding new genes for beef cattle productivity. New genes associated with live weight at different stages of ontogenesis, average daily live weight gain, residual feed intake, carcass weight and flesh content have been identified. Most of the identified genes control cell division, lipid and carbohydrate metabolism. The accumulated data on full-genome association studies and exome sequencing led to new methods of genetic analysis – gene ontology and gene networks. The use of gene networks provided the first detailed understanding of the genetic basis for the formation of complex phenotypic traits based on the complex interaction of regulatory networks of «major» and «peripheral» genes controlling the development of a particular trait.