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Epistasis and balanced polymorphism influencing complex trait variation

Author

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  • Juergen Kroymann

    (Max Planck Institute for Chemical Ecology)

  • Thomas Mitchell-Olds

    (Max Planck Institute for Chemical Ecology)

Abstract

Complex traits such as human disease, growth rate, or crop yield are polygenic, or determined by the contributions from numerous genes in a quantitative manner. Although progress has been made in identifying major quantitative trait loci (QTL), experimental constraints have limited our knowledge of small-effect QTL, which may be responsible for a large proportion of trait variation1,2,3. Here, we identified and dissected a one-centimorgan chromosome interval in Arabidopsis thaliana without regard to its effect on growth rate, and examined the signature of historical sequence polymorphism among Arabidopsis accessions. We found that the interval contained two growth rate QTL within 210 kilobases. Both QTL showed epistasis; that is, their phenotypic effects depended on the genetic background. This amount of complexity in such a small area suggests a highly polygenic architecture of quantitative variation, much more than previously documented4. One QTL was limited to a single gene. The gene in question displayed a nucleotide signature indicative of balancing selection, and its phenotypic effects are reversed depending on genetic background. If this region typifies many complex trait loci, then non-neutral epistatic polymorphism may be an important contributor to genetic variation in complex traits.

Suggested Citation

  • Juergen Kroymann & Thomas Mitchell-Olds, 2005. "Epistasis and balanced polymorphism influencing complex trait variation," Nature, Nature, vol. 435(7038), pages 95-98, May.
    • Handle: RePEc:nat:nature:v:435:y:2005:i:7038:d:10.1038_nature03480
    DOI: 10.1038/nature03480
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    Cited by:

    1. Marie Bouteillé & Gaëlle Rolland & Crispulo Balsera & Olivier Loudet & Bertrand Muller, 2012. "Disentangling the Intertwined Genetic Bases of Root and Shoot Growth in Arabidopsis," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-13, February.
    2. Ulrike Ober & Wen Huang & Michael Magwire & Martin Schlather & Henner Simianer & Trudy F C Mackay, 2015. "Accounting for Genetic Architecture Improves Sequence Based Genomic Prediction for a Drosophila Fitness Trait," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.

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