Title |
Parameters in Dynamic Models of Complex Traits are Containers of Missing Heritability
|
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Published in |
PLoS Computational Biology, April 2012
|
DOI | 10.1371/journal.pcbi.1002459 |
Pubmed ID | |
Authors |
Yunpeng Wang, Arne B. Gjuvsland, Jon Olav Vik, Nicolas P. Smith, Peter J. Hunter, Stig W. Omholt |
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. |
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Geographical breakdown
Country | Count | As % |
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United States | 2 | 25% |
Australia | 1 | 13% |
Unknown | 5 | 63% |
Demographic breakdown
Type | Count | As % |
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Scientists | 4 | 50% |
Members of the public | 4 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 4 | 4% |
Norway | 2 | 2% |
Netherlands | 1 | 1% |
China | 1 | 1% |
Austria | 1 | 1% |
Unknown | 81 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 37 | 41% |
Student > Ph. D. Student | 18 | 20% |
Professor > Associate Professor | 10 | 11% |
Professor | 5 | 6% |
Student > Master | 5 | 6% |
Other | 12 | 13% |
Unknown | 3 | 3% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 50 | 56% |
Biochemistry, Genetics and Molecular Biology | 7 | 8% |
Environmental Science | 5 | 6% |
Computer Science | 4 | 4% |
Medicine and Dentistry | 4 | 4% |
Other | 12 | 13% |
Unknown | 8 | 9% |