UC San Diego

In the field of functional genomics, understanding the 1D sequence elements and 3D interactions of chromatin is of utmost importance. Previous studies have identified hubs as crucial nodes in the 3D chromatin landscape, and demonstrated their essentiality even in quiescent regions without any known 1D epigenetic annotations. These findings have shed light on the interplay between the linear genome and 3D contacts in cellular functions. However, a comprehensive comparison between hubs and a clear mechanism explaining their phenotypic consequences are still lacking.

In this dissertation, our primary objective was to address these gaps in knowledge. Initially, we utilized machine learning to guide a CRISPR screening of hubs, resulting in an improved candidate pool and a significantly higher discovery rate. Next, we employed statistical tests and machine learning algorithms to classify hub essentiality, revealing no discernible genetic or epigenetic differences between essential and nonessential hubs. However, we observed distinct spatial contacts and opposing effects on cell growth for neighboring hubs in the linear genome. Subsequently, we selected a pair of such hubs located in an epigenetically quiescent region and conducted in-depth analyses using single-cell experiments.

Our investigations validated the differential impacts of these hubs on gene expression, chromatin accessibility, and chromatin organization. Furthermore, we discovered that deletion of the essential hub resulted in alterations in genetic network activity and increased Shannon entropy of chromatin accessibility, exceeding the effects caused by deletion of the nonessential hub. These findings suggest the critical role of hubs in maintaining an orderly chromatin structure. By providing novel insights into the systemic functions of non-coding regions in the human genome, our study enhances our understanding of gene regulation at a broader scale.