Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1371/journal.pcbi.1002459 | PLOS COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
genome wide association study,polymorphism,genetic variation,computer model,computer simulation,calcium signaling,action potentials | Genetic correlation,Phenomics,Genetic architecture,Missing heritability problem,Biology,Genetic variation,Genome-wide association study,Genetic association,Bioinformatics,Genetics,Phenotypic trait | Journal |
Volume | Issue | ISSN |
8 | 4 | 1553-7358 |
Citations | PageRank | References |
2 | 0.44 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunpeng Wang | 1 | 2 | 0.77 |
| Arne B Gjuvsland | 2 | 39 | 3.68 |
| Jon Olav Vik | 3 | 10 | 1.67 |
| N P Smith | 4 | 79 | 10.92 |
| Hunter P J | 5 | 1352 | 177.64 |
| Stig W Omholt | 6 | 79 | 9.24 |