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Record W4411488082 · doi:10.1261/rna.080460.125

RNA aptamers as tools for the purification and analysis of in vivo assembled ribonucleoproteins

2025· review· en· W4411488082 on OpenAlexaff
Daniel Rocca, Ute Kothe

Bibliographic record

VenueRNA · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAptamerRibonucleoproteinRNABiologyComputational biologyRibonucleoprotein particleRibosomeNucleic acid structureRNA-binding proteinCell biologyBiochemistryMolecular biologyGene

Abstract

fetched live from OpenAlex

A large number of ribonucleoprotein (RNP) complexes are being discovered mediating numerous cellular functions. To investigate the composition, structure, and functional mechanism of RNP complexes, it is advantageous to isolate an RNP that was assembled in vivo. This review provides a systematic overview of a versatile and highly effective method to accomplish this task, namely, the purification of RNPs from cells using genetically encoded RNA aptamers. Inserting an RNA aptamer into the RNA of an RNP enables binding of the tagged RNP with high affinity and specificity to a ligand as an effective affinity chromatography purification strategy. Therefore, the purification of RNPs using aptamers has been used successfully to identify heterogenous populations of RNPs forming around a single RNA as well as to characterize intermediates in the formation of complex RNPs such as the ribosome. Here, we discuss in detail the selection of an appropriate RNA aptamer based on the properties of both the aptamer and its ligand, and we describe critical considerations in designing RNP purifications.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.319
Teacher spread0.288 · 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 designOther design
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

Citations0
Published2025
Admission routes1
Has abstractyes

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