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Record W2570669030 · doi:10.1371/journal.pgen.1006550

Mutation Accumulation in an Asexual Relative of Arabidopsis

2017· article· en· W2570669030 on OpenAlexaff
John T. Lovell, R. Williamson, Stephen Wright, John McKay, Timothy F. Sharbel

Bibliographic record

VenuePLoS Genetics · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsUniversity of Toronto
FundersDeutsche Forschungsgemeinschaft
KeywordsBiologyApomixisGeneticsSympatric speciationAsexual reproductionMutationNegative selectionMutation AccumulationNatural selectionPseudogeneEvolutionary biologyAlleleGeneSelection (genetic algorithm)PloidyMutation rateGenome

Abstract

fetched live from OpenAlex

Asexual populations experience weaker responses to natural selection, which causes deleterious mutations to accumulate over time. Additionally, stochastic loss of individuals free of deleterious mutations can lead to an irreversible increase in mutational load in asexuals (the "click" in Muller's Ratchet). Here we report on the genomic divergence and distribution of mutations across eight sympatric pairs of sexual and apomictic (asexual) Boechera (Brassicaceae) genotypes. We show that apomicts harbor a greater number of derived mutations than sympatric sexual genotypes. Furthermore, in phylogenetically constrained sites that are subject to contemporary purifying selection, the ancestral, conserved allele is more likely to be retained in sexuals than apomicts. These results indicate that apomictic lineages accumulate mutations at otherwise conserved sites more often than sexuals, and support the conclusion that deleterious mutation accumulation can be a powerful force in the evolution of asexual higher plants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.136
GPT teacher head0.296
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations68
Published2017
Admission routes1
Has abstractyes

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