Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

Anders P. Charmouh; Greta Bocedi; Matthew Hartfield

doi:10.1093/g3journal/jkad140

Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

Anders P. Charmouh^*, Greta Bocedi, Matthew Hartfield

^*Corresponding author for this work

Department of Molecular Biology and Genetics - Bioinformatics Research Centre (BiRC)

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Abstract

The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (p_lth) to capture the proportion of strongly deleterious mutations. We show that p_lth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As p_lth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.

Original language	English
Article number	jkad140
Journal	G3: Genes, Genomes, Genetics
Volume	13
Issue	9
ISSN	2160-1836
DOIs	https://doi.org/10.1093/g3journal/jkad140
Publication status	Published - Sept 2023

Keywords

distribution of fitness effects
mutational effect inference
Poisson random field theory
site frequency spectrum
theoretical population genetics
Wright–Fisher simulations

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10.1093/g3journal/jkad140

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title = "Inferring the distributions of fitness effects and proportions of strongly deleterious mutations",

abstract = "The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show that plth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As plth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.",

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author = "Charmouh, {Anders P.} and Greta Bocedi and Matthew Hartfield",

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Inferring the distributions of fitness effects and proportions of strongly deleterious mutations. / Charmouh, Anders P.; Bocedi, Greta; Hartfield, Matthew.
In: G3: Genes, Genomes, Genetics, Vol. 13, No. 9, jkad140, 09.2023.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

AU - Charmouh, Anders P.

AU - Bocedi, Greta

AU - Hartfield, Matthew

N1 - Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.

PY - 2023/9

Y1 - 2023/9

N2 - The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show that plth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As plth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.

AB - The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show that plth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As plth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.

KW - distribution of fitness effects

KW - mutational effect inference

KW - Poisson random field theory

KW - site frequency spectrum

KW - theoretical population genetics

KW - Wright–Fisher simulations

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DO - 10.1093/g3journal/jkad140

M3 - Journal article

C2 - 37337692

AN - SCOPUS:85169296921

SN - 2160-1836

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JO - G3: Genes, Genomes, Genetics

JF - G3: Genes, Genomes, Genetics

IS - 9

M1 - jkad140

ER -

Inferring the distributions of fitness effects and proportions of strongly deleterious mutations

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