# Dissecting epitranscriptomic signal from complex tissues

> **NIH NIH R01** · EMORY UNIVERSITY · 2021 · $341,702

## Abstract

Title: Dissecting epitranscriptomic signal from complex tissues
PROJECT SUMMARY:
“RNA epigenetics” or “epitranscriptomics” has emerged in recent years as an exciting and active research
field to study post-transcriptional regulation of gene expressions. The RNA modifications play important roles
in gene expression regulation, and are involved in neurodevelopment and a number of neurological diseases.
Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) is a newly developed technology for
transcriptome-wise profiling of the RNA epigenetic modifications. MeRIP-seq leads to an expansion of
applications in both basic and clinical research, but faces a number of challenges in analysis with its unique
data characteristics, including 1) the presence of technical artifacts due to sequence content and sample
preparation procedures unique to MeRIP; 2) lack of appropriate methods for identification and comparison of
RNA methylated regions; and 3) lack of methods to account for the heterogeneity of tissue samples.
In this proposal, we will address these challenges and develop a series of novel statistical methods for
MeRIP-seq data preprocessing and analyses. They include a data normalization procedure to remove
technical bias, accurate and efficient methods for RNA methylation site detection and comparison, and signal
deconvolution methods to draw cell type specific inferences based on data from tissue samples. All methods
developed in this project will be implemented and released as free, open source software to benefit the
epigenomics research community, including basic scientists working on genetics, epigenetics, gene
regulation and cell development, as well as clinicians looking for disease biomarkers.

## Key facts

- **NIH application ID:** 10184935
- **Project number:** 1R01GM141392-01
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Hao Wu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $341,702
- **Award type:** 1
- **Project period:** 2021-09-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10184935

## Citation

> US National Institutes of Health, RePORTER application 10184935, Dissecting epitranscriptomic signal from complex tissues (1R01GM141392-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10184935. Licensed CC0.

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