Evidence map›Paper›PMID 36332644›Full record

ReviewAnnual review of animal biosciences2023

Deleterious Variation in Natural Populations and Implications for Conservation Genetics.

Jacqueline Robinson, Christopher C Kyriazis, Stella C Yuan, Kirk E Lohmueller

Open access · hybridAbstract readReview
In one paragraph

Review in Annual review of animal biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed
26.0field-weighted citation impact, top 1% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

88 citing papers in PubMed, 143 citations in OpenAlex.

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  14. On the Use of the Jackknife to Compare RMolecular ecology resources · 2026
    Review
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28 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jacqueline RobinsonInstitute for Human Genetics, University of California, San Francisco, California, USA; email: jacqueline.robinson@ucsf.edu.
Christopher C KyriazisDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; email: ckyriazis@g.ucla.edu, scy8@g.ucla.edu, klohmueller@ucla.edu.
Stella C YuanDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; email: ckyriazis@g.ucla.edu, scy8@g.ucla.edu, klohmueller@ucla.edu.
Kirk E LohmuellerDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; email: ckyriazis@g.ucla.edu, scy8@g.ucla.edu, klohmueller@ucla.edu.
University of California, Los Angeles · USUniversity of California, San Francisco · US

Funding

Population genomics of the selective effects of new mutationsR35GM119856 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LOHMUELLER, KIRK · 2016 to 2025
$3.4M
NIGMS NIH HHS R35 GM119856
6 · The paper itself

Abstract

Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.

Indexed as

Genetics, PopulationModels, GeneticAnimalsGenetic VariationInbreedingMutationPopulation Densityconservation biologydeleterious mutationsgenetic loadinbreeding depressionsimulations

Identifiers

PMID36332644
PMCPMC9933137
OpenAlexW4308174537

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.