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

ABSTRACT: Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion 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 multilocus 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.

SUBMITTER: Forsberg SK

PROVIDER: S-EPMC5459553 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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

Forsberg Simon K G SK Bloom Joshua S JS Sadhu Meru J MJ Kruglyak Leonid L Carlborg Örjan Ö

Nature genetics 20170227 4

Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion 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 frequencie ...[more]

PMID: 28250458

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