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Record W4221102080 · doi:10.1021/jacs.2c00670

PhOxi-Seq: Single-Nucleotide Resolution Sequencing of <i>N</i> <sup>2</sup> -Methylation at Guanosine in RNA by Photoredox Catalysis

2022· article· en· W4221102080 on OpenAlexafffund
Kimberley Chung Kim Chung, Yasaman Mahdavi‐Amiri, Christopher Korfmann, Ryan Hili

Bibliographic record

VenueJournal of the American Chemical Society · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Foundation for InnovationYork University
KeywordsChemistryRNAMethylationGuanosineRNA methylationTransfer RNANucleotideDeep sequencingDNA methylationComputational biologyDNABiochemistryGeneGenomeBiologyMethyltransferaseGene expression

Abstract

fetched live from OpenAlex

Chemical modifications regulate the fate and function of cellular RNAs. Newly developed sequencing methods have allowed a deeper understanding of the biological role of RNA modifications; however, the vast majority of post-transcriptional modifications lack a well-defined sequencing method. Here, we report a photo-oxidative sequencing (PhOxi-seq) approach for guanosine N2-methylation, a common methylation mark seen in N2-methylguanosine (m2G) and N2,N2-dimethylguanosine (m22G). Using visible light-mediated organic photoredox catalysis, m2G and m22G are chemoselectively oxidized in the presence of canonical RNA nucleosides, which results in a strong mutation signature observed during sequencing. PhOxi-seq was demonstrated on various tRNAs and rRNA to reveal N2-methylation with excellent response and markedly improved read-through at m22G sites.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.352

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations10
Published2022
Admission routes2
Has abstractyes

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