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Record W3090875426 · doi:10.3390/cells9102195

snR30/U17 Small Nucleolar Ribonucleoprotein: A Critical Player during Ribosome Biogenesis

2020· review· en· W3090875426 on OpenAlexafffund
Timothy John Vos, Ute Kothe

Bibliographic record

VenueCells · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsSmall nucleolar RNARibosome biogenesisRibonucleoproteinRibosomal RNARibosomeBiologyRNACell biologyBiogenesis5.8S ribosomal RNANon-coding RNAComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

The small nucleolar RNA snR30 (U17 in humans) plays a unique role during ribosome synthesis. Unlike most members of the H/ACA class of guide RNAs, the small nucleolar ribonucleoprotein (snoRNP) complex assembled on snR30 does not direct pseudouridylation of ribosomal RNA (rRNA), but instead snR30 is critical for 18S rRNA processing during formation of the small subunit (SSU) of the ribosome. Specifically, snR30 is essential for three pre-rRNA cleavages at the A0/01, A1/1, and A2/2a sites in yeast and humans, respectively. Accordingly, snR30 is the only essential H/ACA guide RNA in yeast. Here, we summarize our current knowledge about the interactions and functions of snR30, discuss what remains to be elucidated, and present two non-exclusive hypotheses on the possible molecular function of snR30 during ribosome biogenesis. First, snR30 might be responsible for recruiting other proteins including endonucleases to the SSU processome. Second, snR30 may contribute to the refolding of pre-rRNA into a required conformation that serves as a checkpoint during ribosome biogenesis facilitating pre-rRNA cleavage. In both scenarios, the snR30 snoRNP may have scaffolding and RNA chaperoning activity. In conclusion, the snR30 snoRNP is a crucial player with an unknown molecular mechanism during ribosome synthesis, posing many interesting future research questions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.035
GPT teacher head0.298
Teacher spread0.263 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2020
Admission routes2
Has abstractyes

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