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Record W2897648990 · doi:10.1111/jeb.13391

Divergent subgenome evolution after allopolyploidization in African clawed frogs (<i>Xenopus</i>)

2018· article· en· W2897648990 on OpenAlexafffund
Benjamin L. S. Furman, Utkarsh J. Dang, Ben J. Evans, G. Brian Golding

Bibliographic record

VenueJournal of Evolutionary Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyXenopusEvolutionary biologyAfrican clawed frogZoologyGeneticsGene

Abstract

fetched live from OpenAlex

Whole genome duplication (WGD), the doubling of the nuclear DNA of a species, contributes to biological innovation by creating genetic redundancy. One mode of WGD is allopolyploidization, wherein each genome from two ancestral species becomes a 'subgenome' of a polyploid descendant species. The evolutionary trajectory of a duplicated gene that arises from WGD is influenced both by natural selection that may favour redundant, new or partitioned functions, and by gene silencing (pseudogenization). Here, we explored how these two phenomena varied over time and within allopolyploid genomes in several allotetraploid clawed frog species (Xenopus). Our analysis demonstrates that, across these polyploid genomes, purifying selection was greatly relaxed compared to a diploid outgroup, was asymmetric between each subgenome, and that coding regions are shorter in the subgenome with more relaxed purifying selection. As well, we found that the rate of gene loss was higher in the subgenome under weaker purifying selection and that this rate has remained relatively consistent over time after WGD. Our findings provide perspective from recently evolved vertebrates on the evolutionary forces that likely shape allopolyploid genomes on other branches of the tree of life.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.213
Teacher spread0.204 · 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

Citations17
Published2018
Admission routes2
Has abstractyes

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