# Multiplexed Analysis of the Epitranscriptome

> **NIH NIH R43** · ALIDA BIOSCIENCES, INC. · 2021 · $255,035

## Abstract

Project Summary/Abstract
More than 170 naturally occurring chemical modifications to RNA are known, more than 100 of which are found
in human RNA of all types: mRNA, tRNA, rRNA, lncRNA, and the others. These modifications play a central role
in nearly all aspects of RNA function, such as translation initiation and termination, translation fidelity, alternative
splicing, trafficking between cellular compartments, and regulating RNA degradation. Proteins that install, read,
and remove modifications are promising drug targets of high current interest to pharma. Currently available
analytical methods either do not report on sequence context or provide sequence information but at the expense
of multiplexing capability. Despite these limitations, it is now known that modifications are dynamically tied to
phenotypic changes in cancer progression, drug resistance, and viral infection. The focus of this application is
to de-risk a new approach to RNA modification analysis capable of reading any set of RNA modifications in a
multiplexed reaction, approaching single base resolution. This technology will be significant because it will
provide the first method for profiling and correlating changes of multiple RNA modification types across the entire
transcriptome in a given sample.

## Key facts

- **NIH application ID:** 10325454
- **Project number:** 1R43HG012170-01
- **Recipient organization:** ALIDA BIOSCIENCES, INC.
- **Principal Investigator:** Gudrun Stengel
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $255,035
- **Award type:** 1
- **Project period:** 2021-08-17 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10325454

## Citation

> US National Institutes of Health, RePORTER application 10325454, Multiplexed Analysis of the Epitranscriptome (1R43HG012170-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10325454. Licensed CC0.

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