PhOxi-Seq: Single-Nucleotide Resolution Sequencing of <i>N</i> <sup>2</sup> -Methylation at Guanosine in RNA by Photoredox Catalysis
Bibliographic record
Abstract
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 N 2 -methylation, a common methylation mark seen in N 2 -methylguanosine (m 2 G) and N 2, N 2 -dimethylguanosine (m 2 2 G). Using visible light-mediated organic photoredox catalysis, m 2 G and m 2 2 G 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 N 2 -methylation with excellent response and markedly improved read-through at m 2 2 G sites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".