The contribution of whole-genome sequence data to genome-wide association studies in livestock: Outcomes and perspectives

Genome-wide association studies (GWAS) in livestock are a powerful method for pursuing deeper insights into the biological mechanisms that control complex traits, often with sights set on the improvement of productive efficiency. There has been a wide uptake of whole-genome sequence (WGS) data for GWAS across the main livestock species. In this review, we aim to provide a critical survey of the contribution of WGS-based GWAS in livestock, by spotlighting the outcomes of some of the most representative efforts. First, we review the empirical results on the efficacy of WGS data for GWAS compared to marker arrays, and what strategies are currently being applied to increase the detection power of WGS-based GWAS. Then, we review the contribution of WGS-based GWAS to our understanding of the genetic architecture of complex traits, and how data structure but also our own practices hinder the fine-mapping of causal variants. We also provide a perspective on our own biases in identifying candidate genes and variants, the practical relevance of GWAS results, and data sharing. There is a need to apply better GWAS practices as the availability of WGS data continues to grow in the future.