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Record W3010322897 · doi:10.1074/mcp.ra119.001909

Human Hepatocyte Nuclear Factor 4-α Encodes Isoforms with Distinct Transcriptional Functions

2020· article· en· W3010322897 on OpenAlexafffund
Élie Lambert, Jean‐Philippe Babeu, Joël Simoneau, Jennifer Raisch, Laurie Lavergne, Dominique Lévesque, Émilie Jolibois, Mariano Avino, Michelle S. Scott, François Boudreau, François‐Michel Boisvert

Bibliographic record

VenueMolecular & Cellular Proteomics · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversité de Sherbrooke
FundersInstitute of Nutrition, Metabolism and DiabetesInstitute of Cancer ResearchCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsGene isoformAlternative splicingBiologyExonProteomeTranscription factorPromoterRNA splicingTranscriptomeNuclear receptorHepatocyte nuclear factor 4Cell biologyGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

HNF4α is a nuclear receptor produced as 12 isoforms from two promoters by alternative splicing. To characterize the transcriptional capacities of all 12 HNF4α isoforms, stable lines expressing each isoform were generated. The entire transcriptome associated with each isoform was analyzed as well as their respective interacting proteome. Major differences were noted in the transcriptional function of these isoforms. The α1 and α2 isoforms were the strongest regulators of gene expression whereas the α3 isoform exhibited significantly reduced activity. The α4, α5, and α6 isoforms, which use an alternative first exon, were characterized for the first time, and showed a greatly reduced transcriptional potential with an inability to recognize the consensus response element of HNF4α. Several transcription factors and coregulators were identified as potential specific partners for certain HNF4α isoforms. An analysis integrating the vast amount of omics data enabled the identification of transcriptional regulatory mechanisms specific to certain HNF4α isoforms, hence demonstrating the importance of considering all isoforms given their seemingly diverse functions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.202
Teacher spread0.187 · 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 designBench or experimental
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

Citations50
Published2020
Admission routes2
Has abstractyes

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