Summary
How did the current biodiversity emerge? How does a single fertilised egg develop into a functioning organism? Which factors govern the spread of a pathogen during an epidemic? The answers to these questions depend on the underlying population dynamic processes, i.e. the replication and change of individuals. I will establish fundamental rules of population dynamic processes within the project PhyCogy.
I hypothesize that applying statistical tools to phylogenetic trees uncovers these fundamental rules. Such statistical phylodynamic inference is possible since trees display replication events together with the genotypes and phenotypes of individuals. However, the phylodynamic technique has only been widely applied in the disciplines of macroevolution and epidemiology.
In Part I of the PhyCogy project, I will lay generalizable mathematical, statistical, and computational foundations for phylodynamics. In particular, I will formulate, explore, and apply novel phylodynamic models that are appropriate for neutral as well as selective or developmental processes. I will then investigate whether the newly proposed phylodynamic models allow us to reconcile competing theories within macroevolution and real-time epidemiology.
In Part II, the proposed phylodynamic models are then used to investigate the development of multicellular organisms. I will quantify brain development based on human stem-cell derived organoids as well as zebrafish using single cell data obtained both via CRISPR-Cas9-based lineage tracing and transcriptome sequencing.
The project PhyCogy establishes a phylodynamic foundation, quantifying core population dynamic processes in macroevolution, epidemiology, and development. Importantly, the generalizability of the framework allows for future application across biological scales, leading to the rules of population dynamic processes in disciplines as diverse as microbiology, virology, ecology, immunology, or cancer.
I hypothesize that applying statistical tools to phylogenetic trees uncovers these fundamental rules. Such statistical phylodynamic inference is possible since trees display replication events together with the genotypes and phenotypes of individuals. However, the phylodynamic technique has only been widely applied in the disciplines of macroevolution and epidemiology.
In Part I of the PhyCogy project, I will lay generalizable mathematical, statistical, and computational foundations for phylodynamics. In particular, I will formulate, explore, and apply novel phylodynamic models that are appropriate for neutral as well as selective or developmental processes. I will then investigate whether the newly proposed phylodynamic models allow us to reconcile competing theories within macroevolution and real-time epidemiology.
In Part II, the proposed phylodynamic models are then used to investigate the development of multicellular organisms. I will quantify brain development based on human stem-cell derived organoids as well as zebrafish using single cell data obtained both via CRISPR-Cas9-based lineage tracing and transcriptome sequencing.
The project PhyCogy establishes a phylodynamic foundation, quantifying core population dynamic processes in macroevolution, epidemiology, and development. Importantly, the generalizability of the framework allows for future application across biological scales, leading to the rules of population dynamic processes in disciplines as diverse as microbiology, virology, ecology, immunology, or cancer.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101001077 |
| Start date: | 01-06-2021 |
| End date: | 31-05-2026 |
| Total budget - Public funding: | 1 999 540,00 Euro - 1 999 540,00 Euro |
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Original description
How did the current biodiversity emerge? How does a single fertilised egg develop into a functioning organism? Which factors govern the spread of a pathogen during an epidemic? The answers to these questions depend on the underlying population dynamic processes, i.e. the replication and change of individuals. I will establish fundamental rules of population dynamic processes within the project PhyCogy.I hypothesize that applying statistical tools to phylogenetic trees uncovers these fundamental rules. Such statistical phylodynamic inference is possible since trees display replication events together with the genotypes and phenotypes of individuals. However, the phylodynamic technique has only been widely applied in the disciplines of macroevolution and epidemiology.
In Part I of the PhyCogy project, I will lay generalizable mathematical, statistical, and computational foundations for phylodynamics. In particular, I will formulate, explore, and apply novel phylodynamic models that are appropriate for neutral as well as selective or developmental processes. I will then investigate whether the newly proposed phylodynamic models allow us to reconcile competing theories within macroevolution and real-time epidemiology.
In Part II, the proposed phylodynamic models are then used to investigate the development of multicellular organisms. I will quantify brain development based on human stem-cell derived organoids as well as zebrafish using single cell data obtained both via CRISPR-Cas9-based lineage tracing and transcriptome sequencing.
The project PhyCogy establishes a phylodynamic foundation, quantifying core population dynamic processes in macroevolution, epidemiology, and development. Importantly, the generalizability of the framework allows for future application across biological scales, leading to the rules of population dynamic processes in disciplines as diverse as microbiology, virology, ecology, immunology, or cancer.
Status
SIGNEDCall topic
ERC-2020-COGUpdate Date
27-04-2024
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