Evidence map›Paper›PMID 24465911›Full record

ArticlePloS one2014

The interaction between selection, demography and selfing and how it affects population viability.

Diala Abu Awad, Diala Abu Awad, Sophie Gallina, Cyrille Bonamy, Sylvain Billiard

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Stochasticity in cultural evolution: a revolution yet to happen.History and philosophy of the life sciences · 2017
    Article
  4. Article
4 · The record

Corrections and comments

  • Erratum issued
    Awad, Diala Abu [corrected to Abu Awad, Diala]
5 · Who and what money

Authors and funding

5 authors.

Diala Abu Awad
Diala Abu AwadUMR-CNRS 8198, Laboratoire Génétique et Évolution des Populations Végétales, Université Lille 1, Villeneuve d'Ascq, France.
Sophie GallinaUMR-CNRS 8198, Laboratoire Génétique et Évolution des Populations Végétales, Université Lille 1, Villeneuve d'Ascq, France.
Cyrille BonamyCentre de Ressources Informatiques (CRI), Université Lille 1, Villeneuve d'Ascq, France.
Sylvain BilliardUMR-CNRS 8198, Laboratoire Génétique et Évolution des Populations Végétales, Université Lille 1, Villeneuve d'Ascq, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population extinction due to the accumulation of deleterious mutations has only been considered to occur at small population sizes, large sexual populations being expected to efficiently purge these mutations. However, little is known about how the mutation load generated by segregating mutations affects population size and, eventually, population extinction. We propose a simple analytical model that takes into account both the demographic and genetic evolution of populations, linking population size, density dependence, the mutation load, and self-fertilisation. Analytical predictions were found to be relatively good predictors of population size and probability of population viability when verified using an explicit individual based stochastic model. We show that initially large populations do not always reach mutation-selection balance and can go extinct due to the accumulation of segregating deleterious mutations. Population survival depends not only on the relative fitness and demographic stochasticity, but also on the interaction between the two. When deleterious mutations are recessive, self-fertilisation affects viability non-monotonically and genomic cold-spots could favour the viability of outcrossing populations.

Indexed as

Selection, GeneticSelf-FertilizationEvolution, MolecularExtinction, BiologicalMutationPopulation DynamicsTime Factors

Identifiers

PMID24465911
PMCPMC3897648

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.