title: Parameters in dynamic models of complex traits are containers of missing heritability.
abstract: Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.
authors.affiliation: Centre for Integrative Genetics, Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.
authors.forename: Yunpeng
authors.initials: Y
authors.lastname: Wang
authors.forename: Arne B
authors.initials: AB
authors.lastname: Gjuvsland
authors.forename: Jon Olav
authors.initials: JO
authors.lastname: Vik
authors.forename: Nicolas P
authors.initials: NP
authors.lastname: Smith
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Hunter
authors.forename: Stig W
authors.initials: SW
authors.lastname: Omholt
mesh_terms: D000200:Action Potentials / Q000235:genetics*; D000818:Animals; D020013:Calcium Signaling / Q000502:physiology*; D002478:Cells, Cultured; D003198:Computer Simulation; D051379:Mice; D008957:Models, Genetic; D032383:Myocytes, Cardiac / Q000502:physiology*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D019655:Quantitative Trait, Heritable