MétaCan
Menu
Back to cohort
Record W2969023520 · doi:10.1371/journal.pone.0221371

Beyond sequence homology: Cellular biology limits the potential of XIST to act as a miRNA sponge

2019· article· en· W2969023520 on OpenAlexafffund
Erin A. Marshall, Greg L. Stewart, Adam P. Sage, Wan L. Lam, Carolyn J. Brown

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchUniversity of British Columbia
KeywordsXISTBiologymicroRNAComputational biologyGene silencingGeneticsLong non-coding RNARegulation of gene expressionGeneX-inactivationNon-coding RNARNAX chromosome

Abstract

fetched live from OpenAlex

INTRODUCTION: The sponging of microRNAs by a long non-coding RNA (lncRNA) away from their coding gene targets is a conceptually-simple, yet biologically-complex method of lncRNA-mediated gene regulation. Currently, predictions of genes that participate in sponge-based regulation are largely based on sequence homology alone, which may not adequately reflect the cellular environment in which lncRNA:miRNA pairs interact. The vast number of potential interactions generated by these predictions impedes the identification of functional gene regulatory relationships, which necessitates an approach that considers biological context. XIST, the female-specific lncRNA canonically involved in silencing the X chromosome, has been suggested by many studies to act as a miRNA sponge. The sex-specificity of XIST provides the opportunity to study the biological feasibility of proposed XIST-miRNA interactions. Here we take a comprehensive approach by considering factors that affect possible regulation through XIST-miRNA sponging. RESULTS: To identify the most feasible candidates in a particular tissue (lung adenocarcinomas), we considered protein-coding genes that (1) were positively correlated with XIST expression within sexes, (2) were targeted by miRNAs shared with XIST, and (3) expressed in lung adenocarcinoma. This revealed a robust set of 124 genes potentially positively regulated by XIST through the sequestration of 804 shared miRNAs. We then used the basic sex-specific nature of XIST to compare the changes in miRNA-target gene relationships in endogenously high-XIST and low-XIST systems to discover a high-confidence set of only 13 miRNA-gene pairs. As XIST is expressed exclusively in the nucleus, we validated the nuclear presence of several of these high-confidence miRNAs using RT-qPCR, confirming the co-localization required for XIST to interact with these species. CONCLUSIONS: We use a biology-driven approach to identify genes defended from miRNA-based inhibition by the lncRNA XIST. Importantly, we identify that only a small subset of miRNAs predicted by sequence homology alone have the capacity to mediate the XIST-target gene axis, as they are enriched in the nucleus and able to co-localize with XIST for sponging. Our results reinforce the necessary consideration of biological features in future studies of lncRNA:miRNA interactions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicCancer-related molecular mechanisms researchFrench-language works237,207