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Predicting mutation outcome from early stochastic variation in genetic interaction partners

Abstract

Many mutations, including those that cause disease, only have a detrimental effect in a subset of individuals. The reasons for this are usually unknown, but may include additional genetic variation and environmental risk factors1. However, phenotypic discordance remains even in the absence of genetic variation, for example between monozygotic twins2, and incomplete penetrance of mutations is frequent in isogenic model organisms in homogeneous environments3,4. Here we propose a model for incomplete penetrance based on genetic interaction networks5,6. Using Caenorhabditis elegans as a model system, we identify two compensation mechanisms that vary among individuals and influence mutation outcome. First, feedback induction of an ancestral gene duplicate differs across individuals, with high expression masking the effects of a mutation. This supports the hypothesis that redundancy is maintained in genomes to buffer stochastic developmental failure7. Second, during normal embryonic development we find that there is substantial variation in the induction of molecular chaperones such as Hsp90 (DAF-21). Chaperones act as promiscuous buffers of genetic variation8,9, and embryos with stronger induction of Hsp90 are less likely to be affected by an inherited mutation. Simultaneously quantifying the variation in these two independent responses allows the phenotypic outcome of a mutation to be more accurately predicted in individuals. Our model and methodology provide a framework for dissecting the causes of incomplete penetrance. Further, the results establish that inter-individual variation in both specific and more general buffering systems combine to determine the outcome inherited mutations in each individual.

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Figure 1: Genetic interactions provide a general model for incomplete penetrance.
Figure 2: Early inter-individual variation in the induction of ancestral gene duplicates predicts the outcome of inherited mutations.
Figure 3: Inter-individual variation in chaperone induction predicts the outcome of a mutation.
Figure 4: Simultaneous quantification of inter-individual variation in two buffering systems accurately predicts the outcome of a mutation.

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Acknowledgements

This work was funded by grants from the European Research Council, Institució Catalana de Recerca i Estudis Avançats, Ministerio de Ciencia e Innovación Plan Nacional BFU2008-00365, Agència de Gestió d’juts Universitaris i de Recerca, ERASysBio+, the European Molecular Biology Organization Young Investigator Programme, the EMBL-CRG Systems Biology Program, by a Formación de Personal Investigador–Ministerio de Ciencia e Innovación fellowship to A.B. and by a Beatriu de Pinós Fellowship to M.O.C. We thank I. Hope, V. Ambros and S. Kim for providing strains. Additional strains were obtained from the Caenorhabditis Genetics Center, which is funded by the National Institutes of Health National Center for Research Resources. We thank T. Zimmermann and R. García from the CRG Advanced Light Microscopy Unit for advice and assistance, J. Miwa and Y. Yamaguchi for 608F antibody, J. Semple for providing complementary DNA clones, A. Marchetti and R. García-Verdugo for technical assistance, J. Tischler and C. Kiel for advice on single-molecule fluorescence in situ hybridization and western blotting, respectively, and L. Serrano, M. Isalan and J. Semple for comments on the manuscript.

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A.B. performed all experiments, developed the method and analysed the data; M.O.C. demonstrated that increased chaperone activity can suppress mutation outcome in C. elegans; A.B. and B.L. designed experiments, conceived the model and wrote the manuscript.

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Correspondence to Ben Lehner.

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The authors declare no competing financial interests.

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Burga, A., Casanueva, M. & Lehner, B. Predicting mutation outcome from early stochastic variation in genetic interaction partners. Nature 480, 250–253 (2011). https://doi.org/10.1038/nature10665

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