The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation

Author:

Gilbert Kimberly J1ORCID,Zdraljevic Stefan23,Cook Daniel E2ORCID,Cutter Asher D4ORCID,Andersen Erik C2ORCID,Baer Charles F56ORCID

Affiliation:

1. Institute of Plant Sciences, University of Bern, Bern 3013, Switzerland

2. Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA

3. Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA

4. Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON M5S 3B2, Canada

5. Department of Biology, University of Florida, Gainesville, FL 32611-8525, USA

6. University of Florida Genetics Institute, Gainesville, FL 32611, USA

Abstract

Abstract The distribution of fitness effects (DFE) for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the DFE from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, genome structure, and nonrandom mating. Although inference methods aim to control for population size changes, the influence of nonrandom mating remains incompletely understood, despite being a common feature of many species. We report the DFE estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection on linked sites can conspire to compromise estimates of the DFE from extant polymorphisms with existing methods. These factors together tend to bias inferences toward weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the DFE are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.

Funder

EMBO

Swiss National Science Foundation Ambizione

Natural Sciences and Engineering Research Council

NSERC

NIH

Publisher

Oxford University Press (OUP)

Subject

Genetics

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