Periodic Reporting for period 2 - PhyCogy (From Foundations of Phylodynamics to New Applications in Cell Biology)
Berichtszeitraum: 2022-12-01 bis 2024-05-31
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. The PhyCogy project formulates and characterises models describing the replication and change of individuals. The obtained so-called phylodynamic modelling framework is applied to genomic data to answer the above-mentioned and related questions spanning the fields of macroevolution, epidemiology, and development. The generalisability of the developed framework allows for future application across biological scales such as microbiology, virology, ecology, immunology, and cancer.
Thus far, the phylodynamic technique has only been widely applied in the disciplines of macroevolution and epidemiology. While major insights have been generated in these fields, one highlight being the rapid insights gained into COVID-19 spread during the recent and ongoing pandemic, different modelling frameworks result in different and conflicting answers to core questions, such as dinosaur evolution prior to their extinction or the spatial spread of pathogens.
In the theoretical part, namely Part I of the PhyCogy project, we have started to explore in detail the assumptions of the different frameworks. In particular, we have first results on birth-death models where many assumptions – in particular on sampling – match the alternative coalescent framework.
In Part II, where the proposed phylodynamic models are used to investigate the development of multicellular organisms, we have showcased how phylodynamic models applied to single cell sequencing data from lineage tracing experiments can lead to insights into the development of organs and whole organisms.
In the theoretical part, namely Part I of the PhyCogy project, we have started to explore in detail the assumptions of the different frameworks. In particular, we have first results on birth-death models where many assumptions – in particular on sampling – match the alternative coalescent framework.
In Part II, where the proposed phylodynamic models are used to investigate the development of multicellular organisms, we have showcased how phylodynamic models applied to single cell sequencing data from lineage tracing experiments can lead to insights into the development of organs and whole organisms.
On the theoretical side, I envision that by the end of the project, we have formulated and analysed a general mathematical, statistical, and computational modelling framework for phylodynamics, unifying existing frameworks. This will allow the community to perform phylodynamic analyses of genomic sequencing data in a coherent way across biological scales, in particular beyond the classic and successful areas of macroevolution and epidemiology.
On the applied side, I envision that the generalized framework will allow us to reconcile competing theories within macroevolution (e.g. what were the speciation dynamics of dinosaurs prior to their extinction) and real-time epidemiology (e.g. what are the spatial dynamics of a spreading pathogen).
Finally, the general phylodynamic framework will allow us to contribute core biological results in the field of developmental biology by applying phylodynamic tools to single cell sequencing data from lineage tracing experiments.
On the applied side, I envision that the generalized framework will allow us to reconcile competing theories within macroevolution (e.g. what were the speciation dynamics of dinosaurs prior to their extinction) and real-time epidemiology (e.g. what are the spatial dynamics of a spreading pathogen).
Finally, the general phylodynamic framework will allow us to contribute core biological results in the field of developmental biology by applying phylodynamic tools to single cell sequencing data from lineage tracing experiments.