MétaCan
Menu
Back to cohort
Record W2977809893 · doi:10.1101/788778

Regulation of transcription termination by FUS and TDP-43

2019· preprint· en· W2977809893 on OpenAlexafffund
Dorothy Yanling Zhao, Zuyao Ni, Shuye Pu, Guoqing Zhong, Frank W. Schmitges, Ulrich Braunschweig, Benjamin J. Blencowe, Jack Greenblatt

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsRNA polymerase IITARDBPBiologyTranscription (linguistics)ChromatinCell biologyGeneticsFrontotemporal dementiaGeneGene expressionMedicinePromoterSOD1Mutant

Abstract

fetched live from OpenAlex

ABSTRACT The carboxy-terminal domain (CTD) of the RNA polymerase II (RNAPII) subunit POLR2A is a platform for modifications specifying the recruitment of factors that regulate transcription, mRNA processing, and chromatin remodelling. We previously found that symmetrical dimethylation (me2s) of a CTD Arginine residue (R1810 in human) causes recruitment of the Tudor domain of SMN, which interacts with Senataxin. SMN is mutated in spinal muscular atrophy (SMA), and Senataxin is sometimes mutated in Amyotrophic Lateral Sclerosis (ALS). R1810me2s and SMN, like Senataxin, are important for resolving R-loops (DNA:RNA hybrids) at transcription terminators. FUS and TDP-43 (TARDBP) are DNA/RNA binding proteins that are sometimes mutated in ALS and FTD (Frontotemporal dementia). Here we show that TDP-43 and, to some extent, FUS are recruited by the R1810me2s-SMN pathway. Defects in FUS and TDP-43 recruitment influence RNAPII termination and R-loop accumulation, leading to elevated DNA damage at terminators that may contribute to neurodegenerative disorders like ALS and FTD.

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 categoriesMeta-epidemiology (narrow)
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 score0.417
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.243
Teacher spread0.230 · 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.

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

Citations2
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207