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Record W2885933710 · doi:10.1101/232405

Coalescence and linkage disequilibrium in facultatively sexual diploids

2017· preprint· en· W2885933710 on OpenAlexaff
Matthew Hartfield, Stephen Wright, Aneil F. Agrawal

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyGene conversionCoalescent theoryMeiosisLinkage disequilibriumGeneticsPseudoautosomal regionPopulationEvolutionary biologyFacultativeMitotic crossoverEctopic recombinationChromosomal crossoverRecombinationAlleleGenetic recombinationGeneHaplotypePhylogeneticsEcology

Abstract

fetched live from OpenAlex

Abstract Under neutrality, linkage disequilibrium (LD) results from physically linked sites having non-independent coalescent histories. In obligately sexual organisms, meiotic recombination is the dominant force separating linked variants from one another, and thus in determining the decay of LD with physical distance. In facultatively sexual diploid organisms that principally reproduce clonally, mechanisms of mitotic exchange are expected to become relatively more important in shaping LD. Here we outline mathematical and computational models of a facultative-sex coalescent process that includes meiotic and mitotic recombination, via both crossovers and gene conversion, to determine how LD is affected with facultative sex. We demonstrate that the degree to which LD is broken down by meiotic recombination simply scales with the probability of sex if it is sufficiently high (much greater than 1/ N for N the population size). However, with very rare sex (occurring with frequency on the order of 1/ N ), mitotic gene conversion plays a particularly important and complicated role because it both breaks down associations between sites and removes within-individual diversity. Strong population structure under rare sex leads to lower average LD values than in panmictic populations, due to the influence of low-frequency polymorphisms created by allelic sequence divergence acting in individual subpopulations. These analyses provide information on how to interpret observed LD patterns in facultative sexuals, and determine what genomic forces are likely to shape them.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 designSimulation or modeling
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

Citations0
Published2017
Admission routes1
Has abstractyes

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