Epigenomic profiling of human tissues at single-cell resolution
| dc.contributor.advisor | Henikoff, Steven | |
| dc.contributor.author | Wu, Steven | |
| dc.date.accessioned | 2022-04-19T23:41:49Z | |
| dc.date.available | 2022-04-19T23:41:49Z | |
| dc.date.issued | 2022-04-19 | |
| dc.date.submitted | 2022 | |
| dc.description | Thesis (Ph.D.)--University of Washington, 2022 | |
| dc.description.abstract | Traditional methods for profiling DNA-protein binding interactions have been limited by low signalto-noise, false positives, and high costs. To overcome these barriers we developed a simple assay, Cleavage Under Targets & Tagmentation (CUT&Tag), that leverages a transposon based fusion enzyme to map in situ DNA-protein interactions in small samples of cells at high resolution. We then automated CUT&Tag to generate hundreds of chromatin profiles for a multitude of histone modifications across different diseases. Furthermore, we are able to model their cell-type specific gene expression by integrating the data across multiple histone modifications. CUT&Tag is characterized by an exceptionally high signal-to-noise ratio and we reasoned that the method could be used to resolve single-cell chromatin profiles. As a proof-of-concept we demonstrated that single-cell CUT&Tag resolves both active and repressive chromatin marks in cell lines. We then leveraged single-cell CUT&Tag to profile thousands of single cells to uncover the heterogeneity in stem cell development, primary liquid, and solid tumors pre- and post-treatment. Our work is part of a large-scale effort to build a comprehensive map of all cell types to better understand human health and improve disease diagnosis and treatment. | |
| dc.embargo.terms | Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | Wu_washington_0250E_23834.pdf | |
| dc.identifier.uri | http://hdl.handle.net/1773/48426 | |
| dc.language.iso | en_US | |
| dc.rights | CC BY | |
| dc.subject | ||
| dc.subject | Bioinformatics | |
| dc.subject.other | Molecular engineering | |
| dc.title | Epigenomic profiling of human tissues at single-cell resolution | |
| dc.type | Thesis |
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