Effective purifying selection in ancient asexual oribatid mites
Effective purifying selection in ancient asexual oribatid mites is a research paper published in Nature Communications (2017). On theSindex it has a DataRank of 1.3. It has been cited 59 times, with 45 citing works in its 1-hop citation network.
Abstract
Abstract Sex is beneficial in the long term because it can prevent mutational meltdown through increased effectiveness of selection. This idea is supported by empirical evidence of deleterious mutation accumulation in species with a recent transition to asexuality. Here, we study the effectiveness of purifying selection in oribatid mites which have lost sex millions of years ago and diversified into different families and species while reproducing asexually. We compare the accumulation of deleterious nonsynonymous and synonymous mutations between three asexual and three sexual lineages using transcriptome data. Contrasting studies of young asexual lineages, we find evidence for strong purifying selection that is more effective in asexual as compared to sexual oribatid mite lineages. Our results suggest that large populations likely sustain effective purifying selection and facilitate the escape of mutational meltdown in the absence of sex. Thus, sex per se is not a prerequisite for the long-term persistence of animal lineages.
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FAIR Checklist
Context only (not used in score)- Has DOI
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
0.614
From this paper's citation signal
Citation Network Contribution
0.670
From 36 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- MUSCLE: multiple sequence alignment with high accuracy and high throughputNucleic Acids Research200446,160 citationsDataRank 1.6
- RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogeniesBioinformatics201433,987 citationsDataRank 1.6
- Full-length transcriptome assembly from RNA-Seq data without a reference genomeNature Biotechnology201122,458 citationsDataRank 1.5
- PAML 4: Phylogenetic Analysis by Maximum LikelihoodMolecular Biology and Evolution200714,689 citationsDataRank 1.4
- BUSCO: assessing genome assembly and annotation completeness with single-copy orthologsBioinformatics201514,298 citationsDataRank 1.4
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 48% comes from its base citations and 52% from the citation network (36 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.
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