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Record W1999187910 · doi:10.1098/rspb.2014.1932

On the origin of sex chromosomes from meiotic drive

2014· article· en· W1999187910 on OpenAlexaff
Francisco Úbeda, Manus M. Patten, Geoff Wild

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsWestern University
Fundersnot available
KeywordsBiologyEvolution of sexual reproductionGeneticsMeiotic driveMeiosisSex linkageAlleleOutbreeding depressionPopulationChromosomeEvolutionary biologyHeterogametic sexDosage compensationInbreedingGeneDemography

Abstract

fetched live from OpenAlex

Most animals and many plants make use of specialized chromosomes (sex chromosomes) to determine an individual's sex. Best known are the XY and ZW sex-determination systems. Despite having evolved numerous times, sex chromosomes present something of an evolutionary puzzle. At their origin, alleles that dictate development as one sex or the other (primitive sex chromosomes) face a selective penalty, as they will be found more often in the more abundant sex. How is it possible that primitive sex chromosomes overcome this disadvantage? Any theory for the origin of sex chromosomes must identify the benefit that outweighs this cost and enables a sex-determining mutation to establish in the population. Here we show that a new sex-determining allele succeeds when linked to a sex-specific meiotic driver. The new sex-determining allele benefits from confining the driving allele to the sex in which it gains the benefit of drive. Our model requires few special assumptions and is sufficiently general to apply to the evolution of sex chromosomes in outbreeding cosexual or dioecious species. We highlight predictions of the model that can discriminate between this and previous theories of sex-chromosome origins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.294
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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 teacher head, 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

Citations66
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicGenetic and Clinical Aspects of Sex Determination and Chromosomal AbnormalitiesFrench-language works237,207