Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2017 Apr 25;114(17):4465-4470. doi: 10.1073/pnas.1619508114. Epub 2017 Apr 11.

Determining the factors driving selective effects of new nonsynonymous mutations.

Author information

1
Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095; klohmueller@ucla.edu chuber53@ucla.edu.
2
Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095.
3
Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA 90095.
4
Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095.

Abstract

The distribution of fitness effects (DFE) of new mutations plays a fundamental role in evolutionary genetics. However, the extent to which the DFE differs across species has yet to be systematically investigated. Furthermore, the biological mechanisms determining the DFE in natural populations remain unclear. Here, we show that theoretical models emphasizing different biological factors at determining the DFE, such as protein stability, back-mutations, species complexity, and mutational robustness make distinct predictions about how the DFE will differ between species. Analyzing amino acid-changing variants from natural populations in a comparative population genomic framework, we find that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Furthermore, when comparing the DFE across yeast, Drosophila, mice, and humans, the average selection coefficient becomes more deleterious with increasing species complexity. Last, pleiotropic genes have a DFE that is less variable than that of nonpleiotropic genes. Comparing four categories of theoretical models, only Fisher's geometrical model (FGM) is consistent with our findings. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining the complexity of the organism. Our results suggest that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.

KEYWORDS:

Fisher’s geometrical model; Poisson random field; distribution of fitness effects; mutational robustness; protein stability

PMID:
28400513
PMCID:
PMC5410820
DOI:
10.1073/pnas.1619508114
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center