Letter | Published:

Finding the sources of missing heritability in a yeast cross

Nature volume 494, pages 234237 (14 February 2013) | Download Citation

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Abstract

For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic-mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this ‘missing heritability’ have been proposed1. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits, and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene–gene interactions varies among traits, from near zero to approximately 50 per cent. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits.

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Change history

  • 19 February 2013

    A minor change was made to the Online Methods section.

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Acknowledgements

We thank D. Botstein, M. McClean, E. Andersen, F. Albert, S. Treusch, R. Ghosh and X. Wang for comments on the manuscript, Y. Jia and S. Schrader for technical assistance and E. Lander for discussions. This work was supported by National Institutes of Health (NIH) grants R37 MH59520 and R01 GM102308, a James S. McDonnell Centennial Fellowship, and the Howard Hughes Medical Institute (L.K.), a National Science Foundation (NSF) fellowship (J.S.B.), NIH postdoctoral fellowship F32 HG51762 (I.M.E.) and NIH grant P50 GM071508 to the Center for Quantitative Biology at the Lewis-Sigler Institute of Princeton University.

Author information

Affiliations

  1. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08540, USA

    • Joshua S. Bloom
    • , Ian M. Ehrenreich
    • , Wesley T. Loo
    • , Thúy-Lan Võ Lite
    •  & Leonid Kruglyak
  2. Department of Molecular Biology, Princeton University, Princeton, New Jersey 08540, USA

    • Joshua S. Bloom
    • , Wesley T. Loo
    •  & Thúy-Lan Võ Lite
  3. Molecular and Computational Biology Section, University of Southern California, Los Angeles, California 90089, USA

    • Ian M. Ehrenreich
  4. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08540, USA

    • Leonid Kruglyak
  5. Howard Hughes Medical Institute, Princeton University, Princeton, New Jersey 08540, USA

    • Leonid Kruglyak

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Contributions

Experiments were designed by J.S.B., I.M.E. and L.K. Experiments were performed by J.S.B., I.M.E., W.T.L. and T.-L.V.L. Analyses were conducted by J.S.B. The manuscript was written by J.S.B. and L.K. and incorporates comments by all other authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Leonid Kruglyak.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Figures 1-4 and a link to the additional Supplementary Data and Code.

Excel files

  1. 1.

    Supplementary Table 1

    This table contains drug doses, heritability statistics, and QTL summary statistics for traits investigated in this study.

  2. 2.

    Supplementary Table 2

    This table shows the additive genetic variance, partitioned by chromosome, for each trait.

  3. 3.

    Supplementary Table 3

    This is a table of detected QTL. Positions, effect sizes, confidence intervals and genes underneath detected QTL for each trait are listed.

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DOI

https://doi.org/10.1038/nature11867

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