Gene regulation is central for life to function in a wide range of earth’s environments. The long-term goal of this research project is to understand at single bp resolution the molecular organization (architecture) of proteins assembled on the Saccharomyces (budding yeast) genome. Budding yeast represent an ideal model cellular system due to its simple genome, ease of genetic manipulation, and conservation of transcription and chromatin regulators with human cells. By understanding the precise molecular architecture of epigenomes, we gain a holistic view of genome regulation mechanisms. This project will build on our published set of genome-wide ChIP-exo data that comprehensively measures the yeast epigenome consisting of over 400 different proteins and has revealed distinct architectures for inducible versus constitutive gene expression. This expansion will involve understanding how epigenomes are reprogrammed by environmental signals.

Two broad classes of reprogramming will be examined: acute stress responses (e.g., heat shock and oxidative stress) and long-term unfolding of developmental pathways (e.g., starvation responses) brought on by chronic stress. Responses to acute stress reveal molecular architectures that pre-exist in the cell and then re-organize within a few minutes of sensing extracellular signaling. These events are typically transient and so must be captured upon reaching their temporal maxima. In contrast, developmental pathways unfold over hours in yeast and typically rely on de novo synthesis of gene-specific transcription factors. This project will map the precise positional organization of hundreds of epigenomic components in response to heat shock and oxidative stress, and smaller set of components in response to a much broader array of acute stresses and developmental pathways.

This project will define the functional interdependencies of epigenomic factors, with particular focus on the gene induction cofactors Mediator and SAGA. Relevant components of induced transcription will be rapidly depleted, then their impact on Mediator and SAGA binding to promoters examined. Other interdependencies, informed by the organization of epigenomes that will be defined during reprogramming/induction will also be examined. This research will also continue with its previous biochemical reconstitution of chromatin organization across entire genomes, but now adding in components of the transcription machinery and their regulatory factors. A biochemical system will provide greater control over the experimental parameters and therefore provide greater insight into molecular mechanisms of gene control. Together this research will help provide a more thorough understanding of the protein architecture of gene regulation that should allow computational prediction of novel gene-environment interactions.

Knowledge of where proteins bind along a genome informs us of how that genome including its genes are regulated. Such regulation forms the nexus of gene-environment interactions, and is therefore tied to cell fate, including mis-regulation that underlies cancer and other maladies. This project will build on our prior work to precisely measure thousands of protein-DNA interactions for many hundreds of different proteins in many different human and mouse cell types. This will be done at single base resolution using ChIP-exo, a method that uses antibodies to purify specific proteins bound to DNA, an exonuclease to mark the 5’ end at the edge of where the protein directly or indirectly contacts DNA, then followed by DNA sequencing to identify its precise genomic binding location.

The resulting positional organization of proteins (epigenomic architectures) will reveal fundamental mechanisms of gene regulation in different cell types. The proposed work will also measure relevant protein-DNA architectures in diseased medical specimens (e.g., patient-derived tumors and their in vitro organoid derivatives), with the goal of identifying specific epigenomic configurations that are predictive of treatment outcomes. In this way, more effective therapeutic treatment decisions can be made. Biological and medical discoveries from the thousands of resulting datasets will require a powerful computational data management and discovery platform, which will be built so that the scientific community can distill knowledge from data. This project is expected to define epigenomic protein-DNA architectures comprehensively at such high resolution that gene regulatory mechanisms become clear. These architectures will feed into pipelines for biomarker discovery that will help inform physicians and patients on therapeutic choices.

Genomic projects are slowed by a general lack of end-to-end computational infrastructure support. This project will continue to develop our Platform for (Epi)Genomic Regulation (PEGR) for broad community use in facilitating epigenomic discovery. Key components include: 1) a secure metadata development and management system that instills best practices of experimental rigor, reproducibility, and data sharing; 2) automated Galaxy-based epigenomic data processing pipelines with version control; 3) an interactive web-based data analysis portal that provides easy “wizards” and real-time stream-of-consciousness custom analyses; and 4) a means to disseminate data, tools, discoveries, and the platform. Other parts of the PEGR suit include graphically friendly interfaces for custom data analysis (ScriptManager) , and means to disseminate and visualize large-scale analyses through STENCIL .