Epigenomic profiling of complex tissues with single-cell CUT&RUN

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Summary Human genetic regulatory elements remain poorly defined, in large part owing to technical limitations of methods that have been used to map specific components of the chromatin landscape. By far the most popular of these methods is ChIP-seq, which is used in thousands of laboratories and is a staple of large infrastructural projects such as NIH's ENCODE and Epigenomic Roadmap consortia. However, in 1½ years since its introduction, our novel Cleavage Under Targets & Release Using Nuclease (CUT&RUN) antibody-tethered nuclease method has surpassed standard ChIP-seq in efficiency and resolution by orders of magnitude. We have developed extensions to CUT&RUN that make it more generally applicable to biological problems, and have introduced a high- throughput automated format for research and clinical applications. To extend the utility of CUT&RUN to heterogeneous cells and tissues, we propose to develop two single-cell CUT&RUN strategies with distinct advantages. In both cases, we apply in situ ligation to CUT&RUN fragments in bulk, for which we present preliminary proof-of-concept data. One strategy uses direct barcoded amplification of CUT&RUN fragments in nanowell chip arrays and the other uses split-pool combinatorial barcoding. To help guide technology development and to further our understanding of important developmental pathways, we will apply single-cell CUT&RUN to human CD34+ primary hematopoietic cells and Drosophila germline tissues. We will also develop novel computational tools customized for CUT&RUN data that take advantage of the base-pair precision of cleavages by using fragment length and position for peak-calling and for identification of active genetic regulatory elements. We will use standard computational tools that have been developed for single-cell RNA-seq data to delineate cell-type, and we will develop software for simultaneous mapping of adjacent transcription factors, histone marks and RNA Polymerase II within single cells to deduce enhancer-promoter-gene combinations. Finally, we will exploit the ability of CUT&RUN to detect a new general nucleosome feature that we recently discovered in which regulatory elements are marked by asymmetrically unwrapped nucleosomes. Taken together, our proposal will introduce a low-cost high-throughput single-cell epigenome characterization strategy that applies to the wide variety of basic research and clinical applications that require information from the activity of genetic regulatory elements.