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Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast

Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that co...

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Detalles Bibliográficos
Autores principales: Forsberg, Simon K. G., Bloom, Joshua S., Sadhu, Meru J., Kruglyak, Leonid, Carlborg, Örjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5459553/
https://www.ncbi.nlm.nih.gov/pubmed/28250458
http://dx.doi.org/10.1038/ng.3800
Descripción
Sumario:Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that contribute to quantitative trait variation in a large yeast intercross population. The additive variance explained by individual loci in a network is highly dependent on the allele frequencies of the interacting loci. Modeling of phenotypes for multi-locus genotype classes in the epistatic networks is often improved by accounting for the interactions. We discuss the implications of these results for attempts to dissect genetic architectures and to predict individual phenotypes and long-term responses to selection.