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Record W2900176138 · doi:10.1111/jeb.13397

Strikingly high levels of heterozygosity despite 20 years of inbreeding in a clonal honey bee

2018· article· en· W2900176138 on OpenAlexaff
Nicholas M. A. Smith, Claire M. Wade, Michael H. Allsopp, Brock A. Harpur, Amro Zayed, Stephen A. Rose, Jan Engelstädter, Nadine C. Chapman, Boris Yagound, Benjamin P. Oldroyd

Bibliographic record

VenueJournal of Evolutionary Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsYork University
FundersAustralian Research Council
KeywordsBiologyLoss of heterozygosityInbreedingGeneticsPopulationParthenogenesisHeterozygote advantageAlleleHoney beeEvolutionary biologyGeneZoology

Abstract

fetched live from OpenAlex

Inbreeding (the mating between closely related individuals) often has detrimental effects that are associated with loss of heterozygosity at overdominant loci, and the expression of deleterious recessive alleles. However, determining which loci are detrimental when homozygous, and the extent of their phenotypic effects, remains poorly understood. Here, we utilize a unique inbred population of clonal (thelytokous) honey bees, Apis mellifera capensis, to determine which loci reduce individual fitness when homozygous. This asexual population arose from a single worker ancestor approximately 20 years ago and has persisted for at least 100 generations. Thelytokous parthenogenesis results in a 1/3 of loss of heterozygosity with each generation. Yet, this population retains heterozygosity throughout its genome due to selection against homozygotes. Deep sequencing of one bee from each of the three known sub-lineages of the population revealed that 3,766 of 10,884 genes (34%) have retained heterozygosity across all sub-lineages, suggesting that these genes have heterozygote advantage. The maintenance of heterozygosity in the same genes and genomic regions in all three sub-lineages suggests that nearly every chromosome carries genes that show sufficient heterozygote advantage to be selectively detrimental when homozygous.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.124

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.058
GPT teacher head0.244
Teacher spread0.186 · 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 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

Citations23
Published2018
Admission routes1
Has abstractyes

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