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Record W2149459654 · doi:10.1093/nar/gki504

Retropseudogenes derived from the human Ro/SS-A autoantigen-associated hY RNAs

2005· article· en· W2149459654 on OpenAlexafffund
Jonathan Perreault

Bibliographic record

VenueNucleic Acids Research · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsPseudogeneRetrotransposonBiologyGeneticsGeneGenomeNegative selectionHuman genomeRNAAlu elementTransposable element

Abstract

fetched live from OpenAlex

We report the characterization in the human genome of 966 pseudogenes derived from the four human Y (hY) RNAs, components of the Ro/SS-A autoantigen. About 95% of the Y RNA pseudogenes are found in corresponding locations on the chimpanzee and human chromosomes. On the contrary, Y pseudogenes in mice are both infrequent and found in different genomic regions. In addition to this rodent/primate discrepancy, the conservation of hY pseudogenes relative to hY genes suggests that they occurred after rodent/primate divergence. Flanking regions of hY pseudogenes contain convincing evidence for involvement of the L1 retrotransposition machinery. Although Alu elements are found in close proximity to most hY pseudogenes, these are not chimeric retrogenes. Point mutations in hY RNA transcripts specifically affecting binding of Ro60 protein likely contributed to their selection for direct trans retrotransposition. This represents a novel requirement for the selection of specific RNAs for their genomic integration by the L1 retrotransposition machinery. Over 40% of the hY pseudogenes are found in intronic regions of protein-coding genes. Considering the functions of proteins known to bind subsets of hY RNAs, hY pseudogenes constitute a new class of L1-dependent non-autonomous retroelements, potentially involved in post-transcriptional regulation of gene expression.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.089
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.327
Teacher spread0.280 · 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

Citations65
Published2005
Admission routes2
Has abstractyes

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