# miR-SEQ: Highly efficient targeted quantification of extracellular miRNAs by Next Generation Sequencing

> **NIH NIH R44** · REALSEQ BIOSCIENCES, INC. · 2020 · $526,093

## Abstract

Abstract:
Recent discoveries highlight the importance of cell-free miRNAs (cf-miRNAs) as promising diagnostic and
prognostic biomarkers for cancer and many other diseases. Biofluids such as plasma can be accessed with
minimal invasiveness, unlike tissue biopsies. This, together with the high stability of cf-miRNAs in biofluids,
makes them attractive for use in molecular diagnostics compared to other, more labile biomolecules. However,
current techniques are inadequate for sensitive, specific and reliable quantification of miRNAs in biofluids.
Microarrays and RT-qPCR are currently the preferred tools for expression profiling of cf-miRNAs, although
each has major drawbacks. Microarrays suffer from low sensitivity, low dynamic range, and the inability to
distinguish closely related miRNA sequences, while RT-qPCR has limited multiplexing capability and
amplification biases. While next-generation sequencing (NGS) is superior in many of these respects, its
reliability for cf-miRNA profiling in biofluids is limited due to bias (under- and over-detection) towards particular
miRNA sequences, overwhelming amounts of unrelated sequencing data, the need for gel-purification of
amplicons, and its high cost. Here we propose a new approach for constructing cf-miRNA sequencing libraries
that addresses these problems. Called miR-SEQ, it incorporates a new combination of hybridization and
enzymatic steps to simplify the preparation of miRNA sequencing libraries while significantly decreasing the
sequencing bias. It involves a targeted sequencing approach allowing the quantification of all miRNAs of
interest including rare tissue- (e.g., cancer-) derived miRNA species and their isomiRs representing the highest
interest as biomarkers that would otherwise be represented by none or low numbers of sequencing reads,
making their quantification problematic and expensive. In Phase I we demonstrated the feasibility of our
approach by accurately detecting more than 100 cf-miRNAs with a targeted sequencing approach. In Phase II
we will thoroughly optimize miR-SEQ to maximize its sensitivity and to allow sequencing of a larger variety of
cf-miRNAs for commercial viability. In addition, we will streamline the protocol to facilitate its adoption by end
users including academic labs, contract research facilities, corporate R&D and molecular diagnostic labs.

## Key facts

- **NIH application ID:** 9850981
- **Project number:** 5R44GM115124-06
- **Recipient organization:** REALSEQ BIOSCIENCES, INC.
- **Principal Investigator:** Sergio Barberan-Soler
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $526,093
- **Award type:** 5
- **Project period:** 2015-03-15 → 2021-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9850981

## Citation

> US National Institutes of Health, RePORTER application 9850981, miR-SEQ: Highly efficient targeted quantification of extracellular miRNAs by Next Generation Sequencing (5R44GM115124-06). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9850981. Licensed CC0.

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