ArticleNature methods2022
Direct identification of A-to-I editing sites with nanopore native RNA sequencing.
Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
80 citing papers in PubMed, 132 citations in OpenAlex.
- Epitranscriptomic Analysis of A-to-I RNA Editing and mInternational journal of molecular sciences · 2026Review
- VeloRM: disentangling pre- and post-splicing RNA modification dynamics at single-cell resolution.Nucleic acids research · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- Systematic assessment of diverse RNA modifications using nanopore direct RNA sequencing.Nucleic acids research · 2026Article
- Multimodal profiling reveals cell type-specific pseudouridine modification and density-dependent translational regulation.Nucleic acids research · 2026Article
- Elucidating the coordination of RNA processing using short-read and long-read RNA-sequencing methods.Nature reviews. Molecular cell biology · 2026Review
- Systematic evaluation of computational tools for multitype RNA modification detection using nanopore direct RNA sequencing.Nature methods · 2026Article
- Ab initio detection of multiple epitranscriptomic modifications from Oxford nanopore technology direct RNA sequencing data.Briefings in bioinformatics · 2026Article
- The new era of single-molecule RNA modification detection through nanopore base-calling models.Nature reviews. Molecular cell biology · 2026Review
- Endoplasmic reticulum stress-related genes play a role in the prognosis of lung adenocarcinoma.Discover oncology · 2025Article
- Advances in Detecting RNA Modifications Using Direct RNA Nanopore Sequencing.Advanced genetics (Hoboken, N.J.) · 2025Review
- Direct RNA sequencing enables improved transcriptome assessment and tracking of RNA modifications for medical applications.Nucleic acids research · 2025Article
- Long-read sequencing-based analyses of the adult Drosophila brain transcriptome in physiological and pathological settings.BMC genomics · 2025Article
- A reference-guided iterative approach to polish the nanopore sequencing basecalling for therapeutic RNA quality control.Communications biology · 2025Article
- Accurate interpretation of inosines in RNAs: recognized as G is more than basepairing with C.Epigenomics · 2025Article
- Direct high-throughput deconvolution of non-canonical bases via nanopore sequencing and bootstrapped learning.Nature communications · 2025Article
- ModiDeC: a multi-RNA modification classifier for direct nanopore sequencing.Nucleic acids research · 2025Article
- ADARs: pleiotropy in function, versatility in application.Nucleic acids research · 2025Review
- Tripartite motif 47 promotes the development of thyroid carcinoma through ADAR ubiquitination.Molecular medicine (Cambridge, Mass.) · 2025Article
- Nanopore direct RNA sequencing of human transcriptomes reveals the complexity of mRNA modifications and crosstalk between regulatory features.Cell genomics · 2025Article
20 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors at 2 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inosine is a prevalent RNA modification in animals and is formed when an adenosine is deaminated by the ADAR family of enzymes. Traditionally, inosines are identified indirectly as variants from Illumina RNA-sequencing data because they are interpreted as guanosines by cellular machineries. However, this indirect method performs poorly in protein-coding regions where exons are typically short, in non-model organisms with sparsely annotated single-nucleotide polymorphisms, or in disease contexts where unknown DNA mutations are pervasive. Here, we show that Oxford Nanopore direct RNA sequencing can be used to identify inosine-containing sites in native transcriptomes with high accuracy. We trained convolutional neural network models to distinguish inosine from adenosine and guanosine, and to estimate the modification rate at each editing site. Furthermore, we demonstrated their utility on the transcriptomes of human, mouse and Xenopus. Our approach expands the toolkit for studying adenosine-to-inosine editing and can be further extended to investigate other RNA modifications.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.