# Development of chimeric read amplification into a robust method for profiling targets of specific microRNAs and global amplification of all microRNA:mRNA pairings transcriptome-wide

> **NIH NIH R44** · ECLIPSE BIOINNOVATIONS INC · 2021 · $1,137,682

## Abstract

PROJECT SUMMARY
 Post-transcriptional regulation by microRNAs is fundamental for cellular homeostasis. MicroRNAs are
small non-coding RNAs that fine tune gene expression by base pairing to complementary sequences in target
messenger RNA (mRNA) molecules. A single microRNA can have multiple targets allowing for coordinated
regulation of mRNA networks. The importance of microRNA regulation is evidenced not only by their
evolutionary conservation but also by the involvement of microRNAs in nearly every biological process
including proliferation, inflammation, development, and metabolism. Misregulation of individual microRNAs or
global microRNA processing has important consequences for development, physiology, and disease.
Aberrant microRNA expression has been linked to many diseases ranging from cancer to cardiac failure, and
microRNAs have become attractive targets and tools for therapeutic approaches. Precise target identification
of microRNAs is essential to understand their functional role. Current methods to identify microRNA targets
are limited, as they have high false-positive rates, are unable to definitively distinguish direct from indirect
microRNA-target interactions or are unable to profile low-abundance microRNAs. To this end we have applied
our previously developed enhanced crosslinking and immunoprecipitation (eCLIP) technology to develop a
specialized alternative, chimeric-eCLIP, to unambiguously identify microRNA targets in a transcriptome-wide
manner. Chimeric-eCLIP is based on AGO2 eCLIP and includes a ligation step where microRNA and mRNA
fragments are ligated to each other forming chimeric RNA molecules that can then be sequenced. Direct
targets of individual microRNAs are easily identifiable from chimeric-eCLIP data using microRNA:mRNA
chimeric reads. The work proposed here will expand the previously developed chimeric-eCLIP technology to
include microRNA- and gene-specific read enrichment methods, and a user-friendly analysis package
resulting in a robust and versatile chimeric-eCLIP kit for wide-spread use by academic and biotechnology
industries, as outlined in the following aims:
 1. Expand direct profiling of microRNA targets with probe-based chimeric-eCLIP
 2. Refine software tools for analysis of chimeric-eCLIP data to strengthen key customer-facing features
 3. Conduct expanded beta testing and finalize commercialization of the all-inclusive chimeric-eCLIP kit
Eclipse Bio is an ideal candidate to perform the aims described above due to our expertise in genomics, RNA
processing, and computational biology. The above aims will enable robust microRNA target mapping to be
performed using a standard method by all biomedical researchers and will allow for rigorous validation of
microRNA specificity. The ability to properly assess therapeutic microRNA-like molecules will provide
significant benefit to researchers studying microRNA regulation and companies developing RNA therapies.

## Key facts

- **NIH application ID:** 10326159
- **Project number:** 2R44HG010603-02
- **Recipient organization:** ECLIPSE BIOINNOVATIONS INC
- **Principal Investigator:** Alexander A Shishkin
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,137,682
- **Award type:** 2
- **Project period:** 2019-09-17 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10326159

## Citation

> US National Institutes of Health, RePORTER application 10326159, Development of chimeric read amplification into a robust method for profiling targets of specific microRNAs and global amplification of all microRNA:mRNA pairings transcriptome-wide (2R44HG010603-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10326159. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*