An integrative deep learning framework reveals a dynamic, combinatorial cis-regulatory lexicon in epidermal differentiation
Abstract/Contents
- Abstract
- Transcription factors (TFs) bind DNA sequence motif vocabularies in cis-regulatory elements (CREs) to modulate chromatin state and gene expression during cell state transitions. A quantitative understanding of how motif lexicons influence dynamic regulatory activity has been elusive due to the combinatorial nature of the cis-regulatory code. To address this, we undertook multi-omic data profiling of chromatin and expression dynamics across epidermal differentiation to identify 40,103 dynamic CREs associated with 3,609 dynamically expressed genes, then applied an interpretable deep learning framework to model the cis-regulatory logic of chromatin accessibility. This analysis framework identified cooperative DNA sequence rules in dynamic CREs regulating synchronous gene modules with diverse roles in skin differentiation. Massively parallel reporter analysis validated temporal dynamics and cooperative cis-regulatory logic. Variants linked to human polygenic skin disease were enriched in these time-dependent combinatorial motif rules. This integrative approach reveals the combinatorial cis-regulatory lexicon of epidermal differentiation and represents a general framework for deciphering the organizational principles of the cis-regulatory code of dynamic gene regulation.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Kim, Daniel Sunwook |
|---|---|
| Degree supervisor | Khavari, Paul A |
| Degree supervisor | Kundaje, Anshul, 1980- |
| Thesis advisor | Khavari, Paul A |
| Thesis advisor | Kundaje, Anshul, 1980- |
| Thesis advisor | Chang, Howard Y. (Howard Yuan-Hao), 1972- |
| Thesis advisor | Greenleaf, William James |
| Degree committee member | Chang, Howard Y. (Howard Yuan-Hao), 1972- |
| Degree committee member | Greenleaf, William James |
| Associated with | Stanford University, Program in Biomedical Informatics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Daniel Sunwook Kim. |
|---|---|
| Note | Submitted to the program in Biomedical Informatics. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/qj364xb4083 |
Access conditions
- Copyright
- © 2021 by Daniel Sunwook Kim
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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