Every cell in the human body carries the same DNA, yet a skin cell and a liver cell behave completely differently because different genes are switched on or off in each. The instructions for which genes to activate come from DNA regions called enhancers, but these are hard to locate because they lack a fixed sequence and can sit far from the genes they control. This project focuses on two chemical tags on histone proteins—H3K14ac and H3K18ac—that the researchers’ earlier machine-learning models identified as key markers for enhancer activity. The team will create mutant cell lines lacking these tags and use molecular techniques to see how their loss alters enhancer function, gene expression, and genome organisation. They will also develop user-friendly artificial intelligence software to help other scientists annotate enhancers in different cell types. This is fundamental science. It addresses a gap in understanding how these understudied epigenetic modifications actually drive gene regulation. If successful, the work will clarify a basic mechanism of cell identity, and the open-source software could become a standard tool for labs worldwide studying gene control and cellular differentiation.
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Although the cells in our body possess distinct features, they all contain identical genetic material stored in DNA. The diversity of mammalian tissues is mediated by the unique set of active genes in each cell type. Such unique gene expression patterns are established by the regions of the DNA known as enhancers. Enhancers do not have a specific sequence code and are often located far away from the genes they control, making predicting their location difficult. Previous studies have found that certain chemical tags on histones, the proteins that package DNA, correlate with enhancer activity. We have used advanced computational methods (machine learning and explainable artificial intelligence) to predict the location of enhancers in flies, humans and mice based on the combinations of different histone modifications. We found that two such marks, H3K14ac and H3K18ac, are important for identifying enhancers. However, how these modifications contribute to the function of enhancers is currently unknown. To study the role of H3K14ac and H3K18ac in gene regulation, we will combine molecular and cell biology approaches with advanced computational analysis, merging expertise from two research institutions. Particularly, we plan to create mutant cell lines lacking H3K14ac and H3K18ac and use a range of advanced molecular techniques to understand how their loss affects enhancer function, gene expression, and genome organisation. In addition, our cellular assays will show how these modifications influence cell behaviour and allow us to link molecular and cellular changes mechanistically. To support these experiments, we will develop novel user-friendly artificial intelligence software to annotate and characterise enhancers in different cell types. With its unique focus on the understudied epigenetic modifications H3K14ac and H3K18ac in mammalian cells, this research project promises to provide new insights into gene expression regulation. Moreover, its methodological advancements will offer valuable and easily adaptable tools for researchers worldwide studying gene regulation and cellular differentiation.
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