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Dissection of genetically complex traits with extremely large pools of yeast segregants

Nature volume 464, pages 1039–1042 (2010)Cite this article

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Abstract

Most heritable traits, including many human diseases1, are caused by multiple loci. Studies in both humans and model organisms, such as yeast, have failed to detect a large fraction of the loci that underlie such complex traits2,3. A lack of statistical power to identify multiple loci with small effects is undoubtedly one of the primary reasons for this problem. We have developed a method in yeast that allows the use of much larger sample sizes than previously possible and hence permits the detection of multiple loci with small effects. The method involves generating very large numbers of progeny from a cross between two Saccharomyces cerevisiae strains and then phenotyping and genotyping pools of these offspring. We applied the method to 17 chemical resistance traits and mitochondrial function, and identified loci for each of these phenotypes. We show that the level of genetic complexity underlying these quantitative traits is highly variable, with some traits influenced by one major locus and others by at least 20 loci. Our results provide an empirical demonstration of the genetic complexity of a number of traits and show that it is possible to identify many of the underlying factors using straightforward techniques. Our method should have broad applications in yeast and can be extended to other organisms.

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Figure 1: X-QTL design and quantitative allele frequency measurement in DNA pools.
Figure 2: X-QTL detection of loci for 4-NQO resistance.
Figure 3: Genetic architecture of chemical resistance traits.
Figure 4: X-QTL mapping of mitochondrial activity by cell sorting.

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Acknowledgements

The authors are grateful to members of the Kruglyak laboratory for comments on this manuscript; D. Botstein, J. Gerke, G. Lang and E. Perlstein for input regarding experiments; J. Bloom, L. Parsons, D. Sangurdekar and J. Storey for advice regarding analyses; and E. Alani for sharing the EAY1467 strain. This work was supported by NIH grant R37 MH59520, a James S. McDonnell Centennial Fellowship, and the Howard Hughes Medical Institute (L.K.), a 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 Contributions Experiments were designed by I.M.E., A.A.C. and L.K. Strains were constructed by I.M.E., Y.J., S.M. and A.A.C. Microarrays were designed by I.M.E. and D.G. Experiments were performed by I.M.E., N.T., Y.J., J.K., S.M. and A.A.C. Simulation scripts were written by I.M.E. and J.A.S. Analyses were conducted by I.M.E. The manuscript was written by I.M.E. and L.K., and incorporates comments by all other authors.

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Author notes

  1. David Gresham

    Present address: Present address: Center for Genomics and Systems Biology, New York University, New York, New York 10003, USA.,

Authors and Affiliations

  1. Lewis-Sigler Institute for Integrative Genomics,,

    Ian M. Ehrenreich, Noorossadat Torabi, Yue Jia, Jonathan Kent, Stephen Martis, Joshua A. Shapiro, David Gresham, Amy A. Caudy & Leonid Kruglyak

  2. Department of Ecology and Evolutionary Biology,,

    Ian M. Ehrenreich, Joshua A. Shapiro & Leonid Kruglyak

  3. Howard Hughes Medical Institute,,

    Ian M. Ehrenreich, Yue Jia, Joshua A. Shapiro & Leonid Kruglyak

  4. Department of Molecular Biology, Princeton University, Princeton, New Jersey 08540, USA,

    Noorossadat Torabi

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Correspondence to Leonid Kruglyak.

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Supplementary information

Supplementary Information

This file contains Supplementary Tables S1 - S2 and Supplementary Figures S1A-S1D, S2A-S2D, S3, S4, S5A-S5Q and S6 with legends. (PDF 5002 kb)

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Ehrenreich, I., Torabi, N., Jia, Y. et al. Dissection of genetically complex traits with extremely large pools of yeast segregants. Nature 464, 1039–1042 (2010). https://doi.org/10.1038/nature08923

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