Decoding animal genomes into cell types
This project aims to decode how genome sequences translate into cell types using Drosophila, employing deep learning and multi-omics to understand regulatory programs and their evolutionary changes.
Projectdetails
Introduction
The genome of an animal encodes a large set of regulatory programs that give rise to the thousands of cell types that make up its tissues and organs. Despite recent progress in single-cell omics, our knowledge about the regulatory programs that control the establishment and maintenance of cell type identity remains limited. Moreover, methods are lacking to infer regulatory programs directly from the genome sequence.
Project Overview
In this project, which lies at the interface between the genome and single-cell atlases, we ask how the genome sequence “translates” into cell types. We start with Drosophila as a model organism. Its compactness allows sampling of all its cell types and developmental trajectories from egg to adult, using whole-organism single-cell multi-omics. This approach captures the spectrum of “activation states” that emerge from the regulatory genome.
Methodology
Deep learning models will be trained on regulatory sequences to predict and explain gene regulatory networks (GRN) and GRN transitions between cell states. These are encoded by:
- Enhancers
- Promoters
- Transcription factors (TF)
- Effector genes
- Feedback loops
Based on a better mechanistic understanding, we will translate this framework to other animals, including octopus, birds, and mammals. We will investigate how regulatory programs evolve, with a focus on neuronal diversity in the brain.
Innovative Approaches
Using new algorithms for cross-species deep learning and combinatorial optimization, we will study how combinations of expressed TFs co-evolve with genomic enhancer logic.
We are unique in our approach because we will:
- Develop and use new technological assays
- Implement deep learning and massively parallel reporter assays
- Combine these with perturbation experiments and synthetic biology to test our hypotheses
Goals
After iteratively improving our regulatory models, we ultimately aim to predict which regulatory programs, and thus which cell types, are encoded in an animal’s genome. Additionally, we will explore how changes in these programs underlie changes in cell types during evolution.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.500.000 |
Totale projectbegroting | € 2.500.000 |
Tijdlijn
Startdatum | 1-6-2023 |
Einddatum | 31-5-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- VIB VZWpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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The impact of 3D regulatory landscapes on the evolution of developmental programsThe 3D-REVOLUTION project aims to explore how changes in 3D regulatory landscapes influence gonadal sex determination and evolutionary gene regulation using advanced genomic techniques. | ERC Consolid... | € 1.998.217 | 2023 | Details |
Genetic Engineering of Regulatory EvolutionGenRevo aims to uncover how regulatory sequences influence gene expression and phenotypes by re-engineering bat wing genetics in mice, advancing understanding of non-coding DNA's role in evolution and disease. | ERC Advanced... | € 2.490.354 | 2022 | Details |
Animal cell types across evolutionary timescales: from regulatory characters to cell phylogeniesThis project aims to elucidate the evolutionary processes of cell type diversity in Cnidaria through comparative genomics and phylogenetic analysis, enhancing our understanding of animal adaptation and evolution. | ERC Consolid... | € 1.999.960 | 2025 | Details |
Deciphering the Regulatory Logic of Cortical DevelopmentEpiCortex aims to map the regulatory landscape of mouse cortical development across timepoints to understand neuronal lineage specification and improve therapeutic strategies for neuropsychiatric diseases. | ERC Consolid... | € 1.999.643 | 2023 | Details |
Designing synthetic regulatory domains to understand gene expression
This project aims to uncover gene regulation mechanisms by systematically altering and analyzing synthetic gene regulatory domains in mouse stem cells to reveal insights into non-coding genome organization.
The impact of 3D regulatory landscapes on the evolution of developmental programs
The 3D-REVOLUTION project aims to explore how changes in 3D regulatory landscapes influence gonadal sex determination and evolutionary gene regulation using advanced genomic techniques.
Genetic Engineering of Regulatory Evolution
GenRevo aims to uncover how regulatory sequences influence gene expression and phenotypes by re-engineering bat wing genetics in mice, advancing understanding of non-coding DNA's role in evolution and disease.
Animal cell types across evolutionary timescales: from regulatory characters to cell phylogenies
This project aims to elucidate the evolutionary processes of cell type diversity in Cnidaria through comparative genomics and phylogenetic analysis, enhancing our understanding of animal adaptation and evolution.
Deciphering the Regulatory Logic of Cortical Development
EpiCortex aims to map the regulatory landscape of mouse cortical development across timepoints to understand neuronal lineage specification and improve therapeutic strategies for neuropsychiatric diseases.