Evidence map›Paper›PMID 30026797›Full record

ArticleEvolutionary applications2018

Impact of supplementation on deleterious mutation distribution in an exploited salmonid.

Anne-Laure Ferchaud, Martin Laporte, Charles Perrier, Louis Bernatchez

Abstract read
In one paragraph

Article in Evolutionary applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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.

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

14 citing papers in PubMed.

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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.

Anne-Laure FerchaudInstitut de Biologie Intégrative et des Systèmes (IBIS) Université Laval Québec QC Canada.ORCID 0000-0002-9577-5508
Martin LaporteInstitut de Biologie Intégrative et des Systèmes (IBIS) Université Laval Québec QC Canada.
Charles PerrierCentre d'Écologie Fonctionnelle et Évolutive Unité Mixte de Recherche CNRS 5175 Montpellier Cedex 5 France.
Louis BernatchezInstitut de Biologie Intégrative et des Systèmes (IBIS) Université Laval Québec QC Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deleterious mutations have important implications for the evolutionary trajectories of populations. While several studies recently investigated the dynamics of deleterious mutations in wild populations, no study has yet explored the fate of deleterious mutations in a context of populations managed by supplementation. Here, based on a dataset of nine wild and 15 supplemented Lake Trout populations genotyped at 4,982 single nucleotide polymorphisms (SNP)s by means of genotype by sequencing (GBS), we explored the effect of supplementation on the frequency of putatively deleterious variants. Three main findings are consequential for the management of fish populations. First, an increase in neutral genetic diversity in stocked populations compared with unstocked ones was observed. Second, putatively deleterious mutations were more likely to be found in unstocked than in stocked populations, suggesting a lower efficiency to purge deleterious mutations in unstocked lakes. Third, a population currently used as a major source for supplementation is characterized by several fixed putatively deleterious alleles. Therefore, other source populations with lower abundance of putatively deleterious mutations should be favored as sources of supplementation. We discuss management implications of our results, especially pertaining to the joint identification of neutral and deleterious mutations that could help refining the choice of source and sink populations for supplementation in order to maximize their evolutionary potential and to limit their mutation load.

Indexed as

conservation managementdeleterious mutationsgenetic diversityLake Trout (Salvelinus namaycush)stocking

Identifiers

PMID30026797
PMCPMC6050184

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Registered trials

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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.