# Platform for transcriptome-wide RNA modification identification in long reads

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA SANTA CRUZ · 2021 · $38,613

## Abstract

Project Summary
RNA modifications are pervasive throughout the human transcriptome and affect transcript stability,
localization, and function. In particular, ADAR-mediated adenosine-to-inosine (A-to-I) edits in RNA have been
shown to affect pre-mRNA splicing and alter codon sequence. Amino acid changes caused by inosines have
been implicated in various deleterious conditions, which include cancer and diseases of the brain. However,
previous literature mapping inosine positions in high-throughput were only able to do so inside the limited
context provided by short RNA-Seq reads. As modifications can be transcript-specific, elucidating the
association of inosines with full mRNA isoforms is crucial for a more rigorous understanding of the role of
inosine modifications in the tissues of our body and, more broadly, disease. Therefore, I propose to investiate
A-to-I editing in the context of diseased and non-diseased systems using full-length mRNA nanopore
sequencing. The nanopore is able to sequence whole RNA strands by converting changes in electrical current
caused by RNA translocating through the pore into nucleotide sequence. ​Aim 1 leverages high-accuracy
nanopore cDNA sequencing of cellular systems with and without ADAR knockdown to interrogate ADAR
function and A-to-I-induced changes to transcript expression changes. To accomplish the latter, I will develop
workflows to determine isoform structure from noisy, long reads. In addition to sequencing full-length
transcripts, nanopore native RNA (nvRNA) sequencing informs on RNA modifications, as modified nucleotides
appear as subtle alteration in current signal with respect to canonical nucleotides. As such, ​Aim 2 ​employs a
generalizable approach to producing cost-effective training data for systematically understanding how inosines
alter current signals in nanopores. I will use a Cas13b-ADAR fusion protein (REPAIRv2) to create site-specific
edits and then perform nvRNA sequencing on the edited transcriptome. Site-specific A-to-I editing allows this
approach to create a labelled inosine dataset in nvRNA signal from which I can develop computational
algorithms to reliably identify inosines in nvRNA data. The REPAIRv2 approach to can be generalized to
eventually identify any RNA modification with nanopores. ​Aim 3 will elucidate how A-to-I editing differs
between tissues. I will sequence 4 normal tissue types with nvRNA sequencing, generating a map of A-to-I
edits in conjunction with isoform usage using the software I am developing. Taken together, the fulfillment of
these aims will not only provide further insights on elusive ADAR mechanism, but also create workflows for
nanopore data analysis and a platform for the study of any modification. As I work toward my Ph.D. with this
interdisciplinary project, I will gain invaluable skills in experimental and computational biology that will prepare
me for a career in science.

## Key facts

- **NIH application ID:** 10168450
- **Project number:** 5F31HG010999-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA SANTA CRUZ
- **Principal Investigator:** Alison Tang
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $38,613
- **Award type:** 5
- **Project period:** 2020-01-24 → 2023-01-23

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10168450

## Citation

> US National Institutes of Health, RePORTER application 10168450, Platform for transcriptome-wide RNA modification identification in long reads (5F31HG010999-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10168450. Licensed CC0.

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