MétaCan
Menu
Back to cohort
Record W4221074155 · doi:10.1093/g3journal/jkac067

Hnrnpul1 controls transcription, splicing, and modulates skeletal and limb development in vivo

2022· article· en· W4221074155 on OpenAlexafffund
Danielle Blackwell, Sherri D. Fraser, Oana Caluseriu, Claudia Vivori, Amanda V. Tyndall, Ryan E. Lamont, Jillian S. Parboosingh, A. Micheil Innes, François P. Bernier, Sarah J. Childs

Bibliographic record

VenueG3 Genes Genomes Genetics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsBiologyZebrafishGeneticsRNA splicingGeneCell biologyRNA

Abstract

fetched live from OpenAlex

Mutations in RNA-binding proteins can lead to pleiotropic phenotypes including craniofacial, skeletal, limb, and neurological symptoms. Heterogeneous nuclear ribonucleoproteins (hnRNPs) are involved in nucleic acid binding, transcription, and splicing through direct binding to DNA and RNA, or through interaction with other proteins in the spliceosome. We show a developmental role for Hnrnpul1 in zebrafish, resulting in reduced body and fin growth and missing bones. Defects in craniofacial tendon growth and adult-onset caudal scoliosis are also seen. We demonstrate a role for Hnrnpul1 in alternative splicing and transcriptional regulation using RNA-sequencing, particularly of genes involved in translation, ubiquitination, and DNA damage. Given its cross-species conservation and role in splicing, it would not be surprising if it had a role in human development. Whole-exome sequencing detected a homozygous frameshift variant in HNRNPUL1 in 2 siblings with congenital limb malformations, which is a candidate gene for their limb malformations. Zebrafish Hnrnpul1 mutants suggest an important developmental role of hnRNPUL1 and provide motivation for exploring the potential conservation of ancient regulatory circuits involving hnRNPUL1 in human development.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.812

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 head0.237
Teacher spread0.227 · 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

Citations9
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueG3 Genes Genomes GeneticsSame topicRNA Research and SplicingFrench-language works237,207