Traits such as height, weight, blood pressure, or longevity vary greatly among individuals and have continuously distributed phenotypes within populations that do not show simple Mendelian inheritance. Likewise, most economically important traits in crops (such as yield, root architecture, seed proteins and fatty acids content, photosynthesis efficiency...) and livestock species (litter size, milk production, meat organoleptic properties) are quantitative rather than qualitative.
Quantitative genetic variation is the substrate for phenotypic evolution in natural populations and for selective breeding of domestic crop and animal species. Quantitative genetic variation also underlies susceptibility to common complex diseases and behavioral disorders in humans, as well as responses to pharmacological therapies. As such, a thorough understanding of the underlying genetic control of these traits can help alleviate complex diseases and develop new and more personalized therapeutic interventions to improve human health.
Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on a model in which many genes control the trait and in which non-genetic environmental factors may also influence.
During this course, implemented in a skill-based learning approach based on analysis of real data sets and case studies, and team-based projects, the students will learn and practice the most up-to-date computational and statistical methods in quantitative genetics, from high-density genetic maps and Quantitative Trait Loci (QTL) mapping to GWAS (Genome-Wide Association Studies) and Genomic Prediction.