Genomweite analyse komplexer merkmale beim rind

The implementation of high-throughput genotyping arrays in routine applications in livestock breeding programs yields genotypes for a large number of single nucleotide polymorphisms (SNPs). Dense SNP information enables both genomic predictions and the identification of quantitative trait loci (QTL) via genome-wide association studies (GWAS). Current genome-wide analyses of cattle populations rely on genotypes of 45,000 SNPs: We demonstrate that increasing the marker density only marginally increases the power of GWAS in the Fleckvieh population. However, sufficiently sized samples are crucial for successful genome-wide analyses of complex traits. Using pheno-types for milkfat percentage, we highlight that the identification of QTL that explain a small fraction (< 1%) of the genetic variation only, requires genotypes of several thousands of individuals. Identifying the underlying genomic variation is mandatory to permanently integrate QTL information in breeding programs. A key factor for the identification of causal trait variants is the availability of sequencing data of a population's key animals. Sequence-derived variants can be imputed for any individual with high-density genotypes. This enables to perform sequence-based association studies and to directly test putatively causal variants for association with phenotypes of interest.