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Record W2586212337 · doi:10.1093/gbe/evx020

The Evolution and Functional Diversification of the Deubiquitinating Enzyme Superfamily

2017· article· en· W2586212337 on OpenAlexaff
Caitlyn Vlasschaert, David P. Cook, Xuhua Xia, Douglas A. Gray

Bibliographic record

VenueGenome Biology and Evolution · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsDeubiquitinating enzymeNeofunctionalizationSubfunctionalizationBiologyFunctional divergenceGene duplicationGeneticsGeneUbiquitinComputational biologyGene familyGene expression

Abstract

fetched live from OpenAlex

Ubiquitin and ubiquitin-like molecules are attached to and removed from cellular proteins in a dynamic and highly regulated manner. Deubiquitinating enzymes are critical to this process, and the genetic catalogue of deubiquitinating enzymes expanded greatly over the course of evolution. Extensive functional redundancy has been noted among the 93 members of the human deubiquitinating enzyme (DUB) superfamily. This is especially true of genes that were generated by duplication (termed paralogs) as they often retain considerable sequence similarity. Because complete redundancy in systems should be eliminated by selective pressure, we theorized that many overlapping DUBs must have significant and unique spatiotemporal roles that can be evaluated in an evolutionary context. We have determined the evolutionary history of the entire class of deubiquitinating enzymes, including the sequence and means of duplication for all paralogous pairs. To establish their uniqueness, we have investigated cell-type specificity in developmental and adult contexts, and have investigated the coemergence of substrates from the same duplication events. Our analysis has revealed examples of DUB gene subfunctionalization, neofunctionalization, and nonfunctionalization.

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 score0.828
Threshold uncertainty score0.996

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 studies0.0010.001
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 head0.016
GPT teacher head0.233
Teacher spread0.216 · 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

Citations40
Published2017
Admission routes1
Has abstractyes

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