We will pioneer a suite of interrelated methods that will enable genomic localizations of hundreds of trans-acting regulators to be enumerated from minute samples on a rapid timescale suitable for clinical decision-making. These include (i) a new transposase-based method to map open chromatin, transcription factor binding, nucleosome position, and chromatin compaction; (ii) comprehensive maps of long noncoding RNA-chromatin interactions These technologies will yields 10,000 to 1 million-fold improvement in input requirement and speed, or deliver new regulatory information with unprecedented precision and comprehensiveness. We designed methods that will cross-fertilize one another, such that success with one method makes the others easier to solve.

Genome regulation occurs in the context of variations in DNA sequence, modification, and structure, which reflect a person’s genetic heritage and accumulated epigenetic changes over life. We will develop novel methods to reveal (i) phased allele-specific DNA copy number and structural variations; (ii) phased and strand-specific DNA methylomes; (iii) higher order chromosome interactions; (iv) long RNA reads for allelic and isoform assignment. Multi-dimensional allelic interrogation will uniquely enable robust calls and causal linkage between cis variants in the DNA template to transcriptional output.

We will create methods for extracting functional gene regulatory elements, their cognate regulators, and target genes from the massive amounts of novel data types. We will devise methods to integrate the diverse epigenomic measurements to infer (i) causal regulators and specific regulatory elements affecting gene expression; (ii) key dynamic and disease-specific features based on temporal data of the same individuals. We will validate these regulatory insights by perturbing specific elements and regulators and repeating the regulome analysis, iteratively refining the model to ensure comprehensiveness and accuracy.

We will collect multidimensional and cell type specific regulomic data from human biopsies of blood, skin, and brain, representing a liquid tissue and two complex solid tissues. These driving biological projects will motivate the optimization of experimental and analytical pipeline all the way from clinical sample collection to data output. For each tissue type, we aim to derive cell-type specific and intercellular regulatory networks, predicting key regulators and the cis-elements. These experiments will provide an excellent cross section of challenges and solutions for applying personalized regulomics broadly on all tissue types and disease states. 

We and our Training Core will broadly disseminate technologies and concepts developed at the Center to our local and the entire biomedical community.