SBIR/STTR Research Award

A method for preparing unbiased miRNA sequencing libraries miR ACS

Award identifier 8e8d897314ecf0d67b72c61759c303628a6bfc73f4419789811298ef9af60dd7Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,794,024

Program and phase

SBIR · Phase II

Award year

2016

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Somagenics, Inc.
Proposal award date
2016-09-28
Contract end date
2019-02-28
UEI
NWMCAECH9RX7
Solicitation number
PA15-269
Topic code
172

Research abstract

ABSTRACT This proposal addresses the problem of sequence bias in next generation sequencing NGS of small RNAs such as microRNAs miRNAs as well as fragments of larger RNAs Because dysregulation of miRNA expression has been implicated in cancer and other diseases accurate expression profiling of all miRNA sequences is important for understanding miRNA biology and for development of new biomarkers and therapeutic targets NGS is currently the most comprehensive approach for discovery and expression profiling of small RNA sequences However NGS expression profiling data underestimate the abundance of most miRNAs in a sample some by as much as fold Knowledge of the true abundances in samples and not just the relative changes between samples is important for reliable identification of miRNAs as biomarkers or drug target candidates Other advantages of unbiased detection include the ability to discover novel RNAs and detect low abundance RNAs that cannot be detected by current NGS methods especially in samples with a low concentration of RNA The source of bias in currently available methods of preparation RNA sequencing libraries for NGS is inefficient and sequence dependent ligation of the two sequencing adapters to the sample RNAs The major factors contributing to this ligation bias are intramolecular folding of the miRNAs and intermolecular folding between miRNAs and adapters which affect the ability of the ligase to access and ligate the miRNA ends Thus there is a need for new more accurate methods and most previous small RNA profiling experiments should be re evaluated To address these problems we are developing a new approach miR ACS miRNA Adapter Circularization and Sequencing for preparing unbiased sequencing libraries that is applicable to miRNAs and other small RNAs as well as small fragments of large RNAs used in general RNA Seq Key features of miR ACS include i ligation of miRNAs with only a single combo adapter CAD that combines sequences of the standard andapos and andapos adapters used for Illumina sequencing producing miRNA CAD ligation products ii circularization of the miRNA CAD products iii blocking of free CAD species that are not ligated to miRNAs and iv RT PCR amplification of the circular miRNA CAD products to produce standard sequencing amplicons containing a single RNA specific sequence insert flanked by the andapos and andapos adapter sequences In Phase I we have demonstrated the feasibility of the miR ACS approach proof of concept by greatly reducing the miRNA sequencing bias in comparison to the best current library prep methods In Phase II we will thoroughly optimize miR ACS to maximize bias reduction and to allow sequencing of a larger variety of RNAs up to nt in size with very low RNA inputs In addition we will streamline the protocol to facilitate its adoption by users and for commercial viability HEALTH RELATEDNESS NARRATIVE MicroRNAs miRNAs are promising candidates as biomarkers of cancer and other diseases that could allow early diagnosis sub typing choice of targeted treatments and monitoring of the progress of therapy Although next generation sequencing NGS is the method of choice for discovering and expression profiling of miRNAs it underestimates the abundance of most miRNAs some by as much as fold because of sequence bias The goal of this grant application is to eliminate this bias to allow discovery of new RNA species and determination of the true abundance of RNAs in biological samples

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

39 SBIR/STTR records share this UEI (1994–2020). Reported award amounts total $23,258,381. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.