SBIR/STTR Research Award

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

Award identifier de0cbde791e3fb5aaeb1edf592d874bfa1a26ca069bcfe9456725728bfa6cea3Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$2,600,409

Program and phase

SBIR · Phase II

Award year

2019

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
REALSEQ BIOSCIENCES, INC.
Proposal award date
2019-09-20
Contract end date
2021-06-30
UEI
F8F5KUUPFG29
Solicitation number
PA18-574
Topic code
172

Research 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).Health relatedness narrative Transcriptomic analysis of single cells has shown that there is a high cell-to-cell variability in gene expression among apparently identical cells in a population. However, a similar analysis is not currently possible for levels of small RNAs, which play key roles in regulating gene expression. The goal of this grant application is to develop the first commercially available library preparation kit for profiling microRNAs from single cells that enables detection of very early changes in development of individual tumor cells and eventually could be used for early-stage cancer diagnostics and for more effective, personalized therapeutic development.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2018–2025). Reported award amounts total $5,941,882. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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