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No evidence for accumulation of deleterious mutations and fitness degradation in clonal fish hybrids: Abandoning sex without regrets

Molecular Ecology(2020)10.1111/mec.15539Source: DataRank Database

No evidence for accumulation of deleterious mutations and fitness degradation in clonal fish hybrids: Abandoning sex without regrets is a research paper published in Molecular Ecology (2020). On theSindex it has a DataRank of 0.911. It has been cited 35 times, with 26 citing works in its 1-hop citation network.

N/A
0.911DataRank · unranked
0.911
35 citations · base score 3.6
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

AbstractDespite its inherent costs, sexual reproduction is ubiquitous in nature, and the mechanisms to protect it from a competitive displacement by asexuality remain unclear. Popular mutation‐based explanations, like the Muller's ratchet and the Kondrashov's hatchet, assume that purifying selection may not halt the accumulation of deleterious mutations in the nonrecombining genomes, ultimately leading to their degeneration. However, empirical evidence is scarce and it remains particularly unclear whether mutational degradation proceeds fast enough to ensure the decay of clonal organisms and to prevent them from outcompeting their sexual counterparts. To test this hypothesis, we jointly analysed the exome sequences and the fitness‐related phenotypic traits of the sexually reproducing fish species and their clonal hybrids, whose evolutionary ages ranged from F1 generations to 300 ky. As expected, mutations tended to accumulate in the clonal genomes in a time‐dependent manner. However, contrary to the predictions, we found no trend towards increased nonsynonymity of mutations acquired by clones, nor higher radicality of their amino acid substitutions. Moreover, there was no evidence for fitness degeneration in the old clones compared with that in the younger ones. In summary, although an efficacy of purifying selection may still be reduced in the asexual genomes, our data indicate that its efficiency is not drastically decreased. Even the oldest investigated clone was found to be too young to suffer fitness consequences from a mutation accumulation. This suggests that mechanisms other than mutation accumulation may be needed to explain the competitive advantage of sex in the short term.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 59%Citation Network 41%

        Base Score Contribution

        0.538

        From this paper's citation signal

        Citation Network Contribution

        0.374

        From 17 citing papers with measurable signal

        Learn more about DataRank methodology →

        Top 5 citers driving the network score

        Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 59% comes from its base citations and 41% from the citation network (17 citing papers contributed measurable signal).

        Base score B(p)
        log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
        Network N(p)
        Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
        Damping factor d = 0.85
        DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
        Self-citations excluded
        Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

        Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

        Read the full methodology →

        Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

        Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

        Authors (9)

        Jan Röslein,Jan PačesORCID,Jan Kotusz,Karel Halačka,Ján Koščo

        Related Papers (10)

        bioRxiv (Cold Spring Harbor Laboratory)(2020)
        OpenAlex related
        10.1101/2020.12.23.424202