Abstract

My overarching research question deals with the epigenetic inheritance of disease risk. Numerous multi-generational studies across species have shown that DNA sequence variation only explains a part of the heritability of disease risk. Molecular traits like DNA methylation, histone modifications and small non-coding RNAs have been shown to propagate phenotypes of obesity and metabolic disease to the next generation. However, epigenetically inherited phenotypes tend to manifest in a noisy, probabilistic, partially-penetrant manner with low effect sizes, making them challenging to model using standard analytical approaches that make assumptions of linearity. Deep learning approaches are better suited to model the presentation of epigenetic inheritance, but the methods developed in this domain suffer from a lack of context-specificity and interpretability.

In this talk, I will discuss my work during my PhD on microbiome-mediated epigenetic inheritance of disease risk in mice, specifically on our attempts to model its presentation in embryonic development and offspring physiology, with an eye towards future perspectives.

This talk can also be followed online using the following link: https://meet.google.com/osj-hyjc-yyr