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CORDIS

Translating the Global Refined Analysis of Newly transcribed RNA and Decay rates by SLAM-seq

Project description

Innovative analysis platform for the detection of newly transcribed cellular RNA

The EU-funded T-GRAND-SLAM project is introducing a novel analysis platform for recently developed RNA sequencing (RNA-seq) and single cell RNA-seq (scRNA-seq) methods, enabling the direct detection of newly transcribed RNA within the pool of total cellular RNA in a defined window of time. Previously, the researchers developed a computational algorithm to reliably define the relative contributions of newly transcribed RNA using RNA-seq. The algorithm directly computes the contribution of the new RNA and allows precise estimation of the obtained ratios for each gene, creating a novel opportunity to identify perturbations in RNA synthesis. The current project will prepare the platform for market introduction with prospective customers and develop a business strategy.

Objective

I propose to introduce novel analysis tools via a platform for three recently developed RNA sequencing (RNA-seq) mI propose to introduce novel analysis tools via a platform for three recently developed RNA sequencing (RNA-seq) methods (SLAM-seq, TimeLapse-seq and TUC-seq). All three methods enable the direct detection of new RNA transcribed by cells in a defined window of time within the pool of total cellular RNA. This is achieved by the introduction and subsequent detection of base-mismatches in newly transcribed RNA using RNA-seq. The ability to differentiate “new” from “old” RNA greatly increases the temporal resolution of RNA-seq experiments.
In the frame of my ERC CoG grant “HERPES”, we developed a computational approach (an algorithm) termed GRAND-SLAM (Globally Refined Analysis of Newly transcribed RNA and Decay rates using SLAM-seq; patent application filed) to reliably define the relative contributions of “new” and “old” RNA. GRAND-SLAM not only directly computes the contribution of “new” and “old” RNA but also provides credible intervals that allow to judge the precision of the obtained ratios for each gene. GRAND-SLAM thereby provides novel means to identify perturbations in RNA synthesis and decay. Furthermore, GRAND-SLAM directly reduces experiment costs by eliminating the need for control samples to determine sequencing error rates.
In conclusion, SLAM-seq will become the new standard for gene expression profiling worldwide and GRAND-SLAM the computational tool to analyze the respective data. Within this PoC-project, we will present the GRAND-SLAM analysis platform and prepare its introduction on the market with prospective customers in three areas: next-generation-sequencing companies, pharmaceutical industry, and research institutes. We will validate the analysis platform, improve its usability via direct testing with pilot customers, and develop our envisaged business strategy according to the feedback we will gain in the course of the project.

Host institution

JULIUS-MAXIMILIANS-UNIVERSITAT WURZBURG
Net EU contribution
€ 149 564,00
Address
SANDERRING 2
97070 Wuerzburg
Germany

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Region
Bayern Unterfranken Würzburg, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 149 564,00

Beneficiaries (1)