BIOO SCIENTIFIC CORPORATION — Department of Health and Human Services STTR Phase I: 172

BIOO SCIENTIFIC CORPORATION — STTR Phase I award from Department of Health and Human Services.

Amount
$270,000
Agency
Department of Health and Human Services · National Institutes of Health
Program / Phase
STTR · Phase I
Topic
172
Solicitation
PA14-072
NAICS
Place of performance
TX
Period
2016-04-01 → 2018-03-31

Description

DESCRIPTION provided by applicant A key application of deep sequencing is gene expression analysis at the RNA level commonly known as RNA seq Reads from RNA seq cover all regions of an mRNA sequence However sequences derived from the andapos end region are sufficient to indicate gene expression levels All andapos end sequencing methods have revealed that most eukaryotic genes display alternative cleavage and polyadenylation APA where RNA isoforms using different cleavage and polyadenylation sites pAs can be generated from a gene Importantly different APA isoforms have been shown to have different metabolisms including stability localization and translation APA clearly poses a challenge for gene expression analysis Current RNA seq methods cannot capture this information second false pA identification due to internal priming leads to inaccurate APA information third complete analysis of gene expression needs to take into consideration all APA isoforms We have proposed a new method that completely addresses false priming incomplete andapos end annotation and significantly propels research on single cell RNA expression and poly A tail length which have so far been elusive The final goal of this proposal is to develop a commercial kit allowing non specialized labs the ability to examine andapos ends in an accurate and sensitive manner PUBLIC HEALTH RELEVANCE Deep sequencing a k a next generation sequencing technologies have revolutionized biology and medicine in recent years We plan to develop a kit that solves mis priming issues that commonly plague andapos end sequencing methods and provides sensitive and robust analysis of gene expression