MétaCan
Menu
Back to cohort
Record W4414162033 · doi:10.1186/s13059-025-03754-9

Diverse short tandem repeat sequences influence gene regulation in human populations

2025· article· en· W4414162033 on OpenAlexafffund
Aleksandra Mitina, Worrawat Engchuan, Brett Trost, Giovanna Pellecchia, Stephen W. Scherer, Ryan K. C. Yuen

Bibliographic record

VenueGenome biology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsHuman geneticsGeneRegulation of gene expressionPhenotypeSequence (biology)Gene expressionTandem repeatRegulatory sequenceHuman genome

Abstract

fetched live from OpenAlex

BACKGROUND: Short tandem repeat (STR) length is a known determinant of pathogenicity in a variety of human disorders. The repeat sequence itself can modulate disease severity and penetrance; however, the broader impact of STR sequence variation on gene expression in the general population remains poorly understood. RESULTS: Here, we analyze the sequence composition of STRs across two general population cohorts of unrelated individuals (n = 3,150) and report that ~ 7% of STRs exhibit sequence variability, with distinct patterns observed among different ethnic groups. These variable repeats are more prone to expansion and are frequently found in proximity to Alu elements. Notably, STRs with variable motifs are often found near splice junctions of genes involved in brain and neuronal functions. This is supported by the differential expression of genes associated with neuron and cellular projection functions, driven by the presence of distinct STR sequences. CONCLUSIONS: Our findings underscore the previously unrecognized role of STR sequence variability in modulating gene expression and contributing to human phenotypic diversity.

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 score0.481
Threshold uncertainty score0.525

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 head0.065
GPT teacher head0.337
Teacher spread0.272 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueGenome biologySame topicGenetic Neurodegenerative DiseasesFrench-language works237,207