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Control of human papillomavirus gene expression by alternative splicing

2016· review· en· W2550557415 on OpenAlexaff
Sheila V. Graham, Arwa A. Faizo

Bibliographic record

VenueVirus Research · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsInstitute of Infection and Immunity
FundersMedical Research CouncilKing Abdulaziz UniversityUniversity of GlasgowWellcome TrustWellcome
KeywordsBiologyRNA splicingAlternative splicingPolyadenylationViral replicationGeneTranscription (linguistics)Splicing factorViral life cycleGene expressionCell biologyGeneticsSR proteinMessenger RNAVirologyGenomeVirusRNA

Abstract

fetched live from OpenAlex

Human papillomaviruses possess circular double stranded DNA genomes of around 8kb in size from which multiple mRNAs are synthesized during an infectious life cycle. Although at least three viral promoters are used to initiate transcription, viral mRNAs are largely the product of processing of pre-mRNAs by alternative splicing and polyadenylation. The HPV life cycle and viral gene expression are tightly linked to differentiation of the epithelium the virus infects: there is an orchestrated production of viral mRNAs and proteins. In this review we describe viral mRNA expression and the roles of the SR and hnRNP proteins that respectively positively and negatively regulate splicing. We discuss HPV regulation of splicing factors and detail the evidence that the papillomavirus E2 protein has splicing-related activities. We highlight the possibility that HPV-mediated control of splicing in differentiating epithelial cells may be necessary to accomplish the viral replication cycle.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.088
GPT teacher head0.445
Teacher spread0.357 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations119
Published2016
Admission routes1
Has abstractyes

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