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

Descripción del proyecto

Una plataforma de análisis innovadora para la detección de ARN celular recién transcrito

El proyecto T-GRAND-SLAM, financiado con fondos europeos, presenta su nueva plataforma de análisis para métodos de secuenciación de ARN de células individuales y métodos de secuenciación de ARN recién desarrollados, que facilita la detección directa de ARN recién transcrito en la reserva de ARN celular total en un espacio de tiempo definido. Anteriormente, los investigadores desarrollaron un algoritmo informático para definir de forma fiable las contribuciones relativas de ARN recién transcrito empleando secuenciación de ARN. El algoritmo calcula directamente la contribución del nuevo ARN y permite realizar una estimación precisa de las proporciones obtenidas de cada gen, de forma que brinda la oportunidad de identificar perturbaciones en la síntesis de ARN. El proyecto actual preparará la plataforma para la comercialización a posibles clientes y desarrollará una estrategia de negocio.

Objetivo

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.

Régimen de financiación

ERC-POC - Proof of Concept Grant

Institución de acogida

JULIUS-MAXIMILIANS-UNIVERSITAT WURZBURG
Aportación neta de la UEn
€ 149 564,00
Dirección
SANDERRING 2
97070 Wuerzburg
Alemania

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Región
Bayern Unterfranken Würzburg, Kreisfreie Stadt
Tipo de actividad
Higher or Secondary Education Establishments
Enlaces
Coste total
€ 149 564,00

Beneficiarios (1)