Deep genetics to study and uncover ‘hidden’ biology
DeepGenetics aims to enhance understanding of genetic regulation in human cells by linking cellular phenotypes to protein domains and amino acids, revealing hidden biological processes.
Projectdetails
Introduction
Human genes are organized in complex networks to produce thousands of proteins that perform a myriad of functions. Whereas we have detailed maps for most biochemical pathways, the wiring of genetic networks in human cells is poorly understood.
Development of Genetic Tools
The development of powerful human genetic tools such as CRISPR, RNAi, and haploid cells, to which I made crucial contributions, has proven invaluable for studying genetic networks. However, these tools face two major limitations:
- They provide information at the gene level, whereas it would be much more informative to understand genetic regulation at the level of protein domains or individual amino acids.
- Important biology can be masked, for example, by the cell state or the interfering activity of other genes.
Objectives of DeepGenetics
With DeepGenetics, we aim to bring our understanding of the genetic regulation of cellular phenotypes to the next level and mine ‘hidden biology’ that even impacts well-studied cellular traits. Our specific objectives include:
- Counterbalancing the use of loss-of-function and gain-of-function genetics to obtain a solid gene-level inventory on the regulation of cellular phenotypes.
- Identifying genes that ‘mask’ unknown biology and using modifier screens to expose and define these processes, as we have recently exemplified in my group, leading to the discovery of important new cellular pathways.
- Connecting phenotypes to the functional protein domains and ultimately to the amino acid level.
Conclusion
Thus, DeepGenetics will provide precise views on the regulation of key cellular phenotypes at the amino acid level and will cross the boundaries of our knowledge by exposing ‘hidden biology’.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.451.625 |
Totale projectbegroting | € 2.451.625 |
Tijdlijn
Startdatum | 1-9-2024 |
Einddatum | 31-8-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- STICHTING HET NEDERLANDS KANKER INSTITUUT-ANTONI VAN LEEUWENHOEK ZIEKENHUISpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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Learning and modeling the molecular response of single cells to drug perturbationsDeepCell aims to model cellular responses to drug perturbations using multiomics and deep learning, facilitating optimal treatment design and expediting drug discovery in clinical settings. | ERC Advanced... | € 2.497.298 | 2023 | Details |
Shedding light on three-dimensional gene regulationThis project aims to elucidate gene expression regulation during differentiation using an ultra-fast optogenetic system and high-resolution genomic tools to study 3D chromatin interactions. | ERC Starting... | € 1.500.000 | 2024 | Details |
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 |
Designing synthetic regulatory domains to understand gene expressionThis 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. | ERC Starting... | € 1.500.000 | 2023 | Details |
Systematically Dissecting the Regulatory Logic of Chromatin ModificationsThis project aims to systematically investigate the functional impact of chromatin modifications on gene expression using a novel editing platform to enhance precision medicine and understand epigenomic profiles. | ERC Consolid... | € 1.999.565 | 2023 | Details |
Learning and modeling the molecular response of single cells to drug perturbations
DeepCell aims to model cellular responses to drug perturbations using multiomics and deep learning, facilitating optimal treatment design and expediting drug discovery in clinical settings.
Shedding light on three-dimensional gene regulation
This project aims to elucidate gene expression regulation during differentiation using an ultra-fast optogenetic system and high-resolution genomic tools to study 3D chromatin interactions.
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.
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.
Systematically Dissecting the Regulatory Logic of Chromatin Modifications
This project aims to systematically investigate the functional impact of chromatin modifications on gene expression using a novel editing platform to enhance precision medicine and understand epigenomic profiles.