Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify
variants related to economic traits. Results can enhance the accuracy of genomic prediction …

Background Genome-wide association studies (GWAS) are widely used to identify regions
of the genome that harbor genetic determinants of quantitative traits. However, the multiple …

Genome-wide association studies (GWAS) were used to discover genomic regions
explaining variation in dairy production and fertility traits. Associations were detected with …

Background Genome wide association studies (GWAS) in most cattle breeds result in large
genomic intervals of significant associations making it difficult to identify causal mutations …

Background Genome-wide association studies (GWAS) have been successfully
implemented in cattle research and breeding. However, moving from the associations to …

Background Over the last years, genome-wide association studies (GWAS) based on
imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci …

Background Sequence data can potentially increase the reliability of genomic predictions,
because such data include causative mutations instead of relying on linkage disequilibrium …

The objective of this study was to compare mapping precision and power of within-breed
and multibreed genome-wide association studies (GWAS) and to compare the results …

Background In livestock, as in humans, the number of genetic variants that can be tested for
association with complex quantitative traits, or used in genomic predictions, is increasing …

Multiple-trait genome-wide association study (GWAS) analyses were compared with single-
trait GWAS for power to discover and subsequently validate genetic markers (single …