title: The selective values of alleles in a molecular network model are context dependent.
abstract: Classical quantitative genetics has applied linear modeling to the problem of mapping genotypic to phenotypic variation. Much of this theory was developed prior to the availability of molecular biology. The current understanding of the mechanisms of gene expression indicates the importance of nonlinear effects resulting from gene interactions. We provide a bridge between genetics and gene network theories by relating key concepts from quantitative genetics to the parameters, variables, and performance functions of genetic networks. We illustrate this methodology by simulating the genetic switch controlling galactose metabolism in yeast and its response to selection for a population of individuals. Results indicate that genes have heterogeneous contributions to phenotypes and that additive and nonadditive effects are context dependent. Early cycles of selection suggest strong additive effects attributed to some genes. Later cycles suggest the presence of strong context-dependent nonadditive effects that are conditional on the outcomes of earlier selection cycles. A single favorable allele cannot be consistently identified for most loci. These results highlight the complications that can arise with the presence of nonlinear effects associated with genes acting in networks when selection is conducted on a population of individuals segregating for the genes contributing to the network.
authors.affiliation: Pioneer Hi-Bred International, Johnston, Iowa 50131-0552, USA. jean.peccoud@pioneer.com
authors.forename: Jean
authors.initials: J
authors.lastname: Peccoud
authors.forename: Kent Vander
authors.initials: KV
authors.lastname: Velden
authors.forename: Dean
authors.initials: D
authors.lastname: Podlich
authors.forename: Chris
authors.initials: C
authors.lastname: Winkler
authors.forename: Lane
authors.initials: L
authors.lastname: Arthur
authors.forename: Mark
authors.initials: M
authors.lastname: Cooper
mesh_terms: D000483:Alleles; D003198:Computer Simulation; D005690:Galactose / Q000235:genetics* / Q000378:metabolism; D015870:Gene Expression; D005828:Genetics, Population; D005838:Genotype; D008958:Models, Molecular; D017711:Nonlinear Dynamics; D010641:Phenotype; D012641:Selection, Genetic; D015003:Yeasts
chemical_list: D005690:Galactose