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Computational multiplexing to optimise next-generation sequencing

Project description

Democratising next-generation sequencing with a novel computational framework

Next-generation sequencing (NGS) has done for medicine and biology what transistors did for electronic circuits and computational power. The number of sequenced samples of nucleic acids is doubling every 2 years. However, although throughput has increased dramatically, the preparation of sequence libraries has hardly been addressed and limited methods to do so are cost- and time-intensive. The ERC-funded MultiSeq project aims to advance its bioinformatics solution to these problems to democratise NGS. The solution consists of a multiplexing strategy to reduce the number of libraries followed by computational demultiplexing. The algorithms will be integrated into a computing framework and piloted in an industrial environment, and commercialisation requirements will be investigated.

Objective

Recent advances in Next-Generation Sequencing (NGS) of nucleic acids (i.e. DNA or RNA) have transformed biology and medicine. Today NGS is one of the main pillars of research in various biological disciplines, and it has already pervaded numerous fields of applications ranging from clinics to the biotechnological industry. Given its versatility and high demand, the global market for NGS is rapidly expanding, with the number of sequenced samples doubling every two years. However, while major advances in NGS were mainly related to a rapid increase in sequencing throughput per machine, the preparation of sequencing libraries - the other
integral step of NGS, has largely remained unchanged. Currently, this step is the major financial and operational bottleneck for sequencing projects, limiting the widespread adoption and utility of NGS. Current state-of-the-art solutions for overcoming these problems either require high upfront costs and/or are laborious. We are developing a bioinformatics solution to these problems, which minimizes the cost and time of library preparation. Our approach, called MultiSeq, allows designing a multiplexing strategy to reduce the number of libraries followed by computational demultiplexing. We plan to extend the experimental proof of concept of our method by applying it to broadly sequenced species. In addition, we will integrate our algorithms into a versatile computing framework and develop a pilot project in an industrially relevant context. In parallel, we will perform market analysis and evaluate the most suitable IP protection and commercialization strategies of our technology. If successful, MultiSeq will be a game-changing approach that will impact sequencing technology and related industries by further democratizing the field of NGS and benefiting both the scientific community and society.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2023-POC

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Host institution

BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 80 000,00
Address
CALLE JORDI GIRONA 31
08034 BARCELONA
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
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Total cost

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Beneficiaries (2)

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