Order-preserving principles underlying genotype–phenotype maps ensure high additive proportions of genetic variance

Authors

  • A. B. GJUVSLAND,

    1. Department of Mathematical Sciences and Technology, Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, Ås, Norway
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  • J. O. VIK,

    1. Department of Mathematical Sciences and Technology, Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, Ås, Norway
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  • J. A. WOOLLIAMS,

    1. Department of Animal and Aquacultural Sciences, Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, Ås, Norway
    2. The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian, UK
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  • S. W. OMHOLT

    1. Department of Animal and Aquacultural Sciences, Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, Ås, Norway
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Arne B. Gjuvsland, Centre for Integrative Genetics (CIGENE), Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway.
Tel.: +47 64 96 52 92; fax: +47 64 96 54 01; e-mail: arne.gjuvsland@umb.no

Abstract

In quantitative genetics, the degree of resemblance between parents and offspring is described in terms of the additive variance (VA) relative to genetic (VG) and phenotypic (VP) variance. For populations with extreme allele frequencies, high VA/VG can be explained without considering properties of the genotype–phenotype (GP) map. We show that randomly generated GP maps in populations with intermediate allele frequencies generate far lower VA/VG values than empirically observed. The main reason is that order-breaking behaviour is ubiquitous in random GP maps. Rearrangement of genotypic values to introduce order-preservation for one or more loci causes a dramatic increase in VA/VG. This suggests the existence of order-preserving design principles in the regulatory machinery underlying GP maps. We illustrate this feature by showing how the ubiquitously observed monotonicity of dose–response relationships gives much higher VA/VG values than a unimodal dose–response relationship in simple gene network models.

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