# Highly accurate small-RNA sequencing of single cells (RealSeq-SC)

> **NIH NIH R44** · REALSEQ BIOSCIENCES, INC. · 2020 · $765,766

## Abstract

Abstract
The goal of this grant application is to develop the first commercially available library preparation
kit for profiling small RNAs from single cells using NGS methods. Single-cell analyses of mRNA
have allowed the identification of crucial differences between cells that were otherwise considered
identical. These findings have shown that there is intrinsic “noise” in the regulation of gene
expression within a population of cells that plays an important role in determining cell fates.
Unfortunately, there is currently a lack of information about the cell-to-cell variability of levels of
microRNAs that as gene expression regulators may also play a critical role. Indeed, there is no
commercially available library preparation kit for miRNAs and other small RNAs that can profile
single cells. We propose to quantify miRNAs from single cells using an advanced, proprietary “low
input single adapter and circularization” technology that allows sensitive and unbiased detection.
The core single adapter and circularization technology, for higher input quantities, demonstrated
unbiased detection of over 70% of all miRNAs in a benchmark Universal miRNA pool, compared
to ~35% from the best competitor kit. We have further developed this technology for single-cell
analysis by creating a novel “low input version” that retains the detection accuracy even at single-
cell levels. Data from our Phase I studies show that this “low input adapter” minimizes dropout
events (a critical and common problem in single cell analysis) by increasing the efficiency of
miRNA detection. Another major obstacle for single-cell miRNA sequencing is formation of
adapter-dimers lacking miRNA inserts during library preparation that critically reduces the amount
of useful miRNA sequencing reads. We employ three separate strategies to dramatically reduce
the presence of adapter-dimers in the library. Also, our protocol performs all steps from cell lysis
to final purification of amplified libraries in a single tube to reduce loss of miRNA from single-cells
and to reduce the possibility of contamination of single-cell samples by environmental RNA. In
Phase I we demonstrated proof-of-principle by detecting small RNAs from single-cells for three
different cell lines. In Phase II, we will further develop and optimize our technology to significantly
increase sensitivity and detection accuracy of miRNAs and other small RNAs from single cells for
commercial viability. We will also develop a kit for single-cell small RNA-seq library preparation
(RealSeq-SC).

## Key facts

- **NIH application ID:** 10021698
- **Project number:** 5R44HG009863-04
- **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:** $765,766
- **Award type:** 5
- **Project period:** 2019-12-05 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10021698

## Citation

> US National Institutes of Health, RePORTER application 10021698, Highly accurate small-RNA sequencing of single cells (RealSeq-SC) (5R44HG009863-04). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10021698. Licensed CC0.

---

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