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Effect of Regulatory Architecture on Broad versus Narrow Sense Heritability

Additive genetic variance (V(A)) and total genetic variance (V(G)) are core concepts in biomedical, evolutionary and production-biology genetics. What determines the large variation in reported V(A)/V(G) ratios from line-cross experiments is not well understood. Here we report how the V(A)/V(G) rati...

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Detalles Bibliográficos
Autores principales: Wang, Yunpeng, Vik, Jon Olav, Omholt, Stig W., Gjuvsland, Arne B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3649986/
https://www.ncbi.nlm.nih.gov/pubmed/23671414
http://dx.doi.org/10.1371/journal.pcbi.1003053
Descripción
Sumario:Additive genetic variance (V(A)) and total genetic variance (V(G)) are core concepts in biomedical, evolutionary and production-biology genetics. What determines the large variation in reported V(A)/V(G) ratios from line-cross experiments is not well understood. Here we report how the V(A)/V(G) ratio, and thus the ratio between narrow and broad sense heritability (h(2)/H(2)), varies as a function of the regulatory architecture underlying genotype-to-phenotype (GP) maps. We studied five dynamic models (of the cAMP pathway, the glycolysis, the circadian rhythms, the cell cycle, and heart cell dynamics). We assumed genetic variation to be reflected in model parameters and extracted phenotypes summarizing the system dynamics. Even when imposing purely linear genotype to parameter maps and no environmental variation, we observed quite low V(A)/V(G) ratios. In particular, systems with positive feedback and cyclic dynamics gave more non-monotone genotype-phenotype maps and much lower V(A)/V(G) ratios than those without. The results show that some regulatory architectures consistently maintain a transparent genotype-to-phenotype relationship, whereas other architectures generate more subtle patterns. Our approach can be used to elucidate these relationships across a whole range of biological systems in a systematic fashion.