Evidence map›Paper›PMID 38207127›Full record

ArticleGenome biology and evolution2024

The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects.

Vivak Soni, Susanne P Pfeifer, Jeffrey D Jensen

Abstract read
In one paragraph

Article in Genome biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Vivak SoniSchool of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.ORCID 0000-0002-9496-9562
Susanne P PfeiferSchool of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.ORCID 0000-0003-1378-2913
Jeffrey D JensenSchool of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.

Funding

On differentiating selective and neutral evolutionary processesR35GM139383 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI JENSEN, JEFFREY D · 2021 to 2025
$3.0M
NIGMS NIH HHS R35 GM139383
6 · The paper itself

Abstract

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.

Indexed as

Genetic DriftSelection, GeneticDemographyModels, GeneticMutationRecombination, Geneticbackground selectiondemographydistribution of fitness effectsmutation raterecombination rate

Identifiers

PMID38207127
PMCPMC10834165

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.