Anna Poetsch

The genome encodes different layers of information, including the encoding for proteins and the regulations of their expression in different tissues. At the same time, the DNA sequence is also very relevant for its own stability and repair, as well as for the probability of accumulating mutagenesis. Over time, the somatic genome is losing its balance and gets increasingly disordered in its gene regulation, organization, and replication. It accumulates damage and mutations. Interestingly, all these processes are very much dependent on the underlying DNA sequence, it’s physicochemical properties, other processes it is exposed to. All this is dependent on the cell type and other external stimuli. 

Using a combination of deep learning models for sequence data, machine learning, computational biology, clinical and experimental data, we try to understand the underlying mechanisms of how the DNA sequence determines its own stability and what this means in the ageing process. Why do some cells accumulate damage and mutations at specific positions in the genome, while others don’t? Why do some cells age healthily despite the damage and mutations they accumulate, while others develop cancerous properties? What does that mean for the ageing process in the organism and can we do something about it?