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Record W2978389059 · doi:10.1098/rspb.2019.1474

No evidence of positive assortative mating for genetic quality in fruit flies

2019· article· en· W2978389059 on OpenAlexafffund
Nathaniel P. Sharp, Michael C. Whitlock

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAssortative matingBiologyInbreedingMatingSelection (genetic algorithm)Sexual selectionEvolutionary biologyGenetic variationInbreeding depressionAdaptation (eye)GeneticsMate choiceGenetic modelPopulationGeneDemography

Abstract

fetched live from OpenAlex

In sexual populations, the effectiveness of selection will depend on how gametes combine with respect to genetic quality. If gametes with deleterious alleles are likely to combine with one another, deleterious genetic variation can be more easily purged by selection. Assortative mating, where there is a positive correlation between parents in a phenotype of interest such as body size, is often observed in nature, but does not necessarily reveal how gametes ultimately combine with respect to genetic quality itself. We manipulated genetic quality in fruit fly populations using an inbreeding scheme designed to provide an unbiased measure of mating patterns. While inbred flies had substantially reduced reproductive success, their gametes did not combine with those of other inbred flies more often than expected by chance, indicating a lack of positive assortative mating. Instead, we detected a negative correlation in genetic quality between parents, i.e. disassortative mating, which diminished with age. This pattern is expected to reduce the genetic variance for fitness, diminishing the effectiveness of selection. We discuss how mechanisms of sexual selection could produce a pattern of disassortative mating. Our study highlights that sexual selection has the potential to either increase or decrease genetic load.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.303
Teacher spread0.252 · 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 designObservational
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

Citations3
Published2019
Admission routes2
Has abstractyes

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Same venueProceedings of the Royal Society B Biological SciencesSame topicInsect behavior and control techniquesFrench-language works237,207