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Unraveling the regulatory code of gene expression in plants

Project description

xAI helps decipher the regulatory code of context-specific gene expression in plants

Plants coordinate the activity of thousands of genes during growth, development and response to environmental cues. Deciphering the regulatory code is critical to engineering greater resilience in plants. The ERC-funded multiCODE project will address this using single-cell genomics, ‘explainable artificial intelligence’ (xAI) and synthetic promoter engineering. Unlike AI’s black box, xAI provides explanations for how an AI model reaches a conclusion. Single-cell gene expression profiling in plants will inform xAI models. The models will predict gene expression under certain conditions while identifying the underlying regulatory DNA sequences. The code will then be experimentally verified in plants via a synthetic promoter containing it, enabling precise control of plant gene expression.

Objective

Multicellular plants control the fine-grained expression of thousands of genes during growth, development, and in response to external stimuli. While gene expression varies strongly between different organs and tissues, how this specificity is encoded in the genome is largely unknown. Although various regulatory DNA sequences and sequence-specific transcription factors controlling diverse transcriptional responses have been described, the combinatorial nature of the regulatory code makes the application of rational approaches to learn and predict context-specific gene expression challenging. This is a major obstacle towards engineering plant promoters with predictable and tuneable expression.

multiCODE’s aim is uniting single-cell genomics, explainable artificial intelligence (xAI), and synthetic promoter engineering, to efficiently learn and validate regulatory sequences controlling gene expression in plants. Based on high-resolution single-cell gene expression profiling in the model Arabidopsis and the crop Brassica rapa, xAI models will be built to predict gene expression in leaves under control and stress conditions while at the same time identifying the underlying regulatory DNA sequences and syntax. The power of these predictive models will be validated by exploiting inter- and intra-species sequence variation, revealing the evolutionary conservation of the regulatory code. Furthermore, a novel multi-tier synthetic promoter engineering approach will be used to experimentally validate, directly in plants, the learned regulatory code in a high-throughput manner.

By combining the power of advanced computational and experimental methods, I will identify novel regulatory sequences and design novel synthetic promoters controlling gene expression in complex cellular contexts. This represents a crucial step towards a comprehensive understanding of gene regulation and will significantly contribute to developing stress-resilient crops.

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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-2024-ADG

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Host institution

VIB VZW
Net EU contribution

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€ 2 498 937,00
Address
SUZANNE TASSIERSTRAAT 1
9052 ZWIJNAARDE - GENT
Belgium

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Region
Vlaams Gewest Prov. Oost-Vlaanderen Arr. Gent
Activity type
Research Organisations
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