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Record W2778853949 · doi:10.1172/jci.insight.96560

Targeting and silencing of rhodopsin by ectopic expression of the transcription factor KLF15

2017· article· en· W2778853949 on OpenAlexfundno aff
Salvatore Botta, Nicola de Prisco, Elena Marrocco, Mario Renda, Martina Sofia, Fabiola Curion, Maria Laura Bacci, Domenico Ventrella, Cathal Wilson, Carlo Gesualdo, Settimio Rossi, Francesca Simonelli, Enrico Maria Surace

Bibliographic record

VenueJCI Insight · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersInstitute of GeneticsEuropean Research CouncilFondazione Telethon
KeywordsEctopic expressionBiologyGene silencingTranscription factorGeneGeneticsGene expressionRetinitis pigmentosaCell biologyRegulation of gene expression

Abstract

fetched live from OpenAlex

The genome-wide activity of transcription factors (TFs) on multiple regulatory elements precludes their use as gene-specific regulators. Here we show that ectopic expression of a TF in a cell-specific context can be used to silence the expression of a specific gene as a therapeutic approach to regulate gene expression in human disease. We selected the TF Krüppel-like factor 15 (KLF15) based on its putative ability to recognize a specific DNA sequence motif present in the rhodopsin (RHO) promoter and its lack of expression in terminally differentiated rod photoreceptors (the RHO-expressing cells). Adeno-associated virus (AAV) vector-mediated ectopic expression of KLF15 in rod photoreceptors of pigs enables Rho silencing with limited genome-wide transcriptional perturbations. Suppression of a RHO mutant allele by KLF15 corrects the phenotype of a mouse model of retinitis pigmentosa with no observed toxicity. Cell-specific-context conditioning of TF activity may prove a novel mode for somatic gene-targeted manipulation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.173

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 studies0.0000.000
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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 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

Citations22
Published2017
Admission routes1
Has abstractyes

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