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Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

Author

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  • Joshua S. Bloom

    (University of California, Los Angeles
    Howard Hughes Medical Institute, University of California, Los Angeles)

  • Iulia Kotenko

    (Princeton University)

  • Meru J. Sadhu

    (University of California, Los Angeles)

  • Sebastian Treusch

    (Twist Bioscience)

  • Frank W. Albert

    (University of California, Los Angeles)

  • Leonid Kruglyak

    (University of California, Los Angeles
    Howard Hughes Medical Institute, University of California, Los Angeles
    University of California)

Abstract

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies.

Suggested Citation

  • Joshua S. Bloom & Iulia Kotenko & Meru J. Sadhu & Sebastian Treusch & Frank W. Albert & Leonid Kruglyak, 2015. "Genetic interactions contribute less than additive effects to quantitative trait variation in yeast," Nature Communications, Nature, vol. 6(1), pages 1-6, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9712
    DOI: 10.1038/ncomms9712
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    Cited by:

    1. Boyang Zheng & Weijie Zhang & Gongwang Yu & Wenjun Shi & Shuyun Deng & Xiaoyi Zhang & Jingyu Chen & Ziwei Zhou & Yuyan Shan & Wanting Wu & Erping Long & Xiaoshu Chen & Jian-Rong Yang, 2025. "Translational fidelity and longevity are genetically linked," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    2. Anna K. Miller & Jacquelaine Bartlett & Calvin Pan & Aldons J. Lusis & Dana C. Crawford & Scott M. Williams & David A. Buchner, 2025. "Concordance between male- and female-specific GWAS results helps define underlying genetic architecture of complex traits," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
    3. Mohammad Erfan Mowlaei & Chong Li & Oveis Jamialahmadi & Raquel Dias & Junjie Chen & Benyamin Jamialahmadi & Timothy Richard Rebbeck & Vincenzo Carnevale & Sudhir Kumar & Xinghua Shi, 2025. "STICI: Split-Transformer with integrated convolutions for genotype imputation," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    4. Takeshi Matsui & Martin N. Mullis & Kevin R. Roy & Joseph J. Hale & Rachel Schell & Sasha F. Levy & Ian M. Ehrenreich, 2022. "The interplay of additivity, dominance, and epistasis on fitness in a diploid yeast cross," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    5. Srijith Sasikumar & Shannara Taylor Parkins & Suresh Sudarsan & Himanshu Sinha, 2025. "Interaction of genetic variants activates latent metabolic pathways in yeast," Nature Communications, Nature, vol. 16(1), pages 1-18, December.

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