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Record W2016295170 · doi:10.1371/journal.pone.0041152

Promoters Are Differentially Sensitive to N-Terminal Mutant Huntingtin-Mediated Transcriptional Repression

2012· article· en· W2016295170 on OpenAlexafffund
Matthew Hogel, Robert B. Laprairie, Eileen M. Denovan‐Wright

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchNova Scotia Health Research FoundationHuntington Society of Canada
KeywordsHuntingtinPromoterBiologyTranscription factorHuntingtin ProteinPsychological repressionMutantGeneticsTranscription (linguistics)Regulation of gene expressionGeneMolecular biologyCell biologyGene expression

Abstract

fetched live from OpenAlex

Huntington's disease (HD) is a neurodegenerative disorder caused by the inheritance of one mutant copy of the huntingtin gene. Mutant huntingtin protein (mHtt) contains an expanded polyglutamine repeat region near the N-terminus. Cleavage of mHtt releases an N-terminal fragment (N-mHtt) which accumulates in the nucleus. Nuclear accumulation of N-mHtt has been directly associated with cellular toxicity. Decreased transcription is among the earliest detected changes that occur in the brains of HD patients, animal and cellular models of HD. Transcriptional dysregulation may trigger many of the perturbations that occur later in disease progression. An understanding of the effects of mHtt may lead to strategies to slow the progression of HD. Current models of N-mHtt-mediated transcriptional dysregulation suggest that abnormal interactions between N-mHtt and transcription factors impair the ability of these transcription factors to associate at N-mHtt-affected promoters and properly regulate gene expression. We tested various aspects of the current models using two N-mHtt-affected promoters in two cell models of HD using overexpression of known N-mHtt-interacting transcription factors, promoter deletion and mutation analyses and in vitro promoter binding assays. Consequently, we proposed a new model of N-mHtt-mediated transcriptional dysregulation centered on the presence of N-mHtt at promoters. In this model, N-mHtt interacts with multiple partners whose presence and affinity for N-mHtt influence the severity of gene dysregulation. We concluded that simultaneous interaction of N-mHtt with multiple binding partners within the transcriptional machinery would explain the gene-specificity of N-mHtt-mediated transcriptional dysregulation, as well as why some genes are affected early in disease progression while others are affected later. Our model explains why alleviating N-mHtt-mediated transcriptional dysregulation through overexpression of N-mHtt-interacting proteins has proven to be difficult and suggests that the most realistic strategy for restoring gene expression across the spectrum of N-mHtt affected genes is by reducing the amount of soluble nuclear N-mHtt.

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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.254
Teacher spread0.182 · 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

Citations13
Published2012
Admission routes2
Has abstractyes

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