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Record W2163019054 · doi:10.1093/genetics/160.2.649

Sex-Specific Recombination Rates in Zebrafish (<i>Danio rerio</i>)

2002· article· en· W2163019054 on OpenAlexaff
Amy Singer, Hodel Perlman, Yi‐Lin Yan, Charlene Walker, Graham E. Corley-Smith, Bruce P. Brandhorst, John H. Postlethwait

Bibliographic record

VenueGenetics · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsSimon Fraser University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Research Resources
KeywordsMeiosisBiologyGeneticsGenetic recombinationRecombinationPloidyDanioHomologous recombinationChromosomal crossoverGenetic linkageCentromereAlleleZebrafishMeiosis IIChromosomeGene

Abstract

fetched live from OpenAlex

In many organisms, the rate of genetic recombination is not uniform along the length of chromosomes or between sexes. To compare the relative recombination rates during meiosis in male and female zebrafish, we constructed a genetic map based on male meiosis. We developed a meiotic mapping panel of 94 androgenetic haploid embryos that were scored for genetic polymorphisms. The resulting male map was compared to female and sex-average maps. We found that the recombination rate in male meiosis is dramatically suppressed relative to that of female meiosis, especially near the centromere. These findings have practical applications for experimental design. The use of exclusively female meiosis in a positional cloning project maximizes the ratio of genetic map distance to physical distance. Alternatively, the use of exclusively male meiosis to localize a mutation initially to a linkage group or to maintain relationships of linked alleles minimizes recombination, thereby facilitating some types of analysis.

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 score0.003
Threshold uncertainty score0.005

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 head0.020
GPT teacher head0.250
Teacher spread0.229 · 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

Citations179
Published2002
Admission routes1
Has abstractyes

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