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Artificial intelligence for synthetic functional genomics of blood

Project description

AI: the future of biological engineering

Cells can switch genes on and off in response to a changing environment. This is possible thanks to a complex group of regulators, known as gene regulatory networks (GRNs). Gene regulatory elements (GREs), such as promoters and enhancers, are key components of these networks and determine which genes are expressed at a given time. Funded by the European Research Council, the AI4SYN project will use haematopoietic stem cell differentiation as a paradigm to construct predictive models of GRNs and GREs. Researchers will combine deep learning with genetic screens at the single-cell level to predict the outcome of potential network perturbations.

Objective

Our abilities to predict and engineer complex biological systems are in their infancy. In the context of gene regulation, we cannot design artificial promoters with specificity to arbitrary cell states, and we cannot arbitrarily trans- and de-differentiate somatic cells, although such abilities would be of high biotechnological and biomedical value. To achieve these ambitious goals, we require quantitative, predictive models of gene regulatory elements (GREs) and gene regulatory networks (GRNs), respectively. Here I propose that the combination of deep learning and single-cell genetic screens is ideally suited to obtain such models, and, in particular, the amounts of highly informative data required for their training. Working with an ex vivo model of hematopoietic stem cell differentiation, we will first screen the activity of hundreds of thousands of synthetic GREs throughout the hematopoietic differentiation landscape. Thereby, we will obtain models of cell type specific GRE activity that can predict new, synthetic GREs with activity in any cell state of interest. Second, we will screen hundreds of thousands of combinatorial GRN perturbations and their effect on cell state. Thereby, we will derive models of GRNs that can predict combinatorial perturbation strategies to achieve arbitrary de- or trans-differentiation events. In sum, work on this project will yield a quantitative model of gene regulation in hematopoiesis at various scales of complexity while introducing a novel, AI-guided concept for biological engineering.

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2021-STG

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Host institution

FUNDACIO CENTRE DE REGULACIO GENOMICA
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.

€ 1 499 653,00
Address
CARRER DOCTOR AIGUADER 88
08003 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 499 653,00

Beneficiaries (1)

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