Extensive impact of low-frequency variants on the phenotypic landscape at population-scale

  1. Téo Fournier
  2. Omar Abou Saada
  3. Jing Hou
  4. Jackson Peter
  5. Elodie Caudal
  6. Joseph Schacherer  Is a corresponding author
  1. Université de Strasbourg, CNRS, France

Abstract

Genome-wide association studies (GWAS) allow to dissect complex traits and map genetic variants, which often explain relatively little of the heritability. One potential reason is the preponderance of undetected low-frequency variants. To increase their allele frequency and assess their phenotypic impact in a population, we generated a diallel panel of 3,025 yeast hybrids, derived from pairwise crosses between natural isolates and examined a large number of traits. Parental versus hybrid regression analysis showed that while most phenotypic variance is explained by additivity, a third is governed by non-additive effects, with complete dominance having a key role. By performing GWAS on the diallel panel, we found that associated variants with low frequency in the initial population are overrepresented and explain a fraction of the phenotypic variance as well as an effect size similar to common variants. Overall, we highlighted the relevance of low frequency variants on the phenotypic variation.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1 and 4.

The following previously published data sets were used

Article and author information

Author details

  1. Téo Fournier

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4860-6728
  2. Omar Abou Saada

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Jing Hou

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Jackson Peter

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Elodie Caudal

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Joseph Schacherer

    Department of Genetics, Genomics and Microbiology, Université de Strasbourg, CNRS, Strasbourg, France
    For correspondence
    schacherer@unistra.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6606-6884

Funding

National Institutes of Health (R01 GM101091-01)

  • Joseph Schacherer

European Research Council (Consolidator grants (772505))

  • Joseph Schacherer

Fondation pour la Recherche Médicale (Graduate student grant)

  • Téo Fournier

Institut Universitaire de France

  • Joseph Schacherer

University of Strasbourg Institute for Advanced Study

  • Joseph Schacherer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Christian R Landry, Université Laval, Canada

Publication history

  1. Received: June 12, 2019
  2. Accepted: October 23, 2019
  3. Accepted Manuscript published: October 24, 2019 (version 1)
  4. Version of Record published: December 4, 2019 (version 2)

Copyright

© 2019, Fournier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Téo Fournier
  2. Omar Abou Saada
  3. Jing Hou
  4. Jackson Peter
  5. Elodie Caudal
  6. Joseph Schacherer
(2019)
Extensive impact of low-frequency variants on the phenotypic landscape at population-scale
eLife 8:e49258.
https://doi.org/10.7554/eLife.49258

Further reading

    1. Genetics and Genomics
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    Insight

    Rare genetic variants in yeast explain a large amount of phenotypic variation in a complex trait like growth.

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