# Direct sequencing of nascent RNA to uncover the functional impact of genetic variants on RNA processing

> **NIH NIH R21** · HARVARD MEDICAL SCHOOL · 2021 · $454,545

## Abstract

The majority of genetic variants associated with a disease or trait do not lie in coding regions, impeding their
interpretation. Many non-coding variants map to introns and may impact steps in RNA processing, such as
intron splicing, 3’-end cleavage and polyadenylation, leading to alternative splicing (AS) or polyadenylation
(APA). Population-wide transcriptome studies and quantitative trait loci (QTL) analyses have revealed an
unappreciated role for common genetic variants in regulating allele-specific RNA processing (sQTLs and
apaQTLs). However, the mechanisms by which these genetic variants impact AS and how they lead to disease
susceptibility remain unclear. Thus, there is a critical need to understand how genetic variants impact RNA
processing during the production and maturation of RNA transcripts, which can in turn prioritize variants for
functional analyses and help understand their potential role in disease susceptibility. Our group recently
developed nanopore analysis of co-transcriptional processing (nano-COP), which simultaneously assays a
variety of molecular phenotypes for single long RNAs, including Pol II position, splicing across multiple introns,
transcription termination, 3’-end cleavage and poly(A) tail length. We will use nano-COP to uncover how
splicing kinetics and 3’ end processing are altered in the context of genetic variants. In turn, these data will
reveal how long variants persist in nascent RNA during which time they are capable of exerting an effect.
Our rationale is that an understanding of how genetic variants impact RNA processing mechanisms and vice
versa will help efforts to identify causal variants that contribute to disease risk. Specific Aim 1: Analyze how
genetic variants influence splicing dynamics. To determine how genetic variants impact splicing dynamics, we
will perform nano-COP in human LCLs from 20 individuals using a targeted panel of 20 genes known to
contain sQTLs in these cells. At the completion of this Aim, we will understand when and how genetic variants
exert their effect during the splicing process, illuminating possible mechanisms underlying genetic control of
AS. Specific Aim 2: Analyze the impact of genetic variants on 3’-end processing. Splicing of terminal introns is
functionally linked to transcription termination and 3’-end processing. We aim to establish how variants in
terminal introns, exons and 3’UTRs affect allele-specific 3’-end cleavage and poly(A) tails. Additionally, we will
investigate how 3’-end processing steps relate to one another and to terminal intron splicing. At the end of this
Aim, we will have learned how genetic variants influence major RNA processing steps to yield the final steady-
state isoforms. The expected outcomes of this grant are a demonstration of how nano-COP can dissect the
role of genetic variants in altering mRNA isoforms and determine whether sQTLs and apaQTLs exert their
influence in part through their locations in longer-lived introns. These resul...

## Key facts

- **NIH application ID:** 10372582
- **Project number:** 1R21HG011682-01A1
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Lee Stirling Churchman
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $454,545
- **Award type:** 1
- **Project period:** 2021-09-24 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10372582

## Citation

> US National Institutes of Health, RePORTER application 10372582, Direct sequencing of nascent RNA to uncover the functional impact of genetic variants on RNA processing (1R21HG011682-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10372582. Licensed CC0.

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