Inferring the shape of global epistasis

Otwinowski, J., McCandlish, D. M., Plotkin, J. B. (July 2018) Inferring the shape of global epistasis. Proc Natl Acad Sci U S A. ISSN 0027-8424

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URL: https://www.ncbi.nlm.nih.gov/pubmed/30037990
DOI: 10.1073/pnas.1804015115

Abstract

Genotype-phenotype relationships are notoriously complicated. Idiosyncratic interactions between specific combinations of mutations occur and are difficult to predict. Yet it is increasingly clear that many interactions can be understood in terms of global epistasis. That is, mutations may act additively on some underlying, unobserved trait, and this trait is then transformed via a nonlinear function to the observed phenotype as a result of subsequent biophysical and cellular processes. Here we infer the shape of such global epistasis in three proteins, based on published high-throughput mutagenesis data. To do so, we develop a maximum-likelihood inference procedure using a flexible family of monotonic nonlinear functions spanned by an I-spline basis. Our analysis uncovers dramatic nonlinearities in all three proteins; in some proteins a model with global epistasis accounts for virtually all of the measured variation, whereas in others we find substantial local epistasis as well. This method allows us to test hypotheses about the form of global epistasis and to distinguish variance components attributable to global epistasis, local epistasis, and measurement error.

Item Type: Paper
Uncontrolled Keywords: deep mutational scanning evolution fitness landscape genotype-phenotype map protein
Subjects: bioinformatics
evolution
CSHL Authors:
Communities: CSHL labs > McCandlish lab
Depositing User: Matthew Dunn
Date: 23 July 2018
Date Deposited: 26 Jul 2018 15:45
Last Modified: 21 Sep 2018 19:02
PMCID: PMC6094095
Related URLs:
URI: http://repository.cshl.edu/id/eprint/37049

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