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Nonparametric Interrogation of Transcriptional Regulation in Single-Cell RNA and Chromatin Accessibility Multiomic Data

Yuriko Harigaya, Zhaojun Zhang, Hongpan Zhang, Chongzhi Zang, Nancy R Zhang, Yuchao Jiang
doi: https://doi.org/10.1101/2021.09.22.461437
Yuriko Harigaya
1Curriculum in Bioinformatics and Computational Biology, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
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Zhaojun Zhang
2Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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Hongpan Zhang
3Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
4Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
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Chongzhi Zang
3Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
4Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
5Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
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Nancy R Zhang
2Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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  • For correspondence: nzh@wharton.upenn.edu yuchaoj@email.unc.edu
Yuchao Jiang
6Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, NC 27599, USA
7Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
8Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
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  • For correspondence: nzh@wharton.upenn.edu yuchaoj@email.unc.edu
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Abstract

Epigenetic control of gene expression is highly cell-type- and context-specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the expression of a target gene through its binding to a cis-regulatory region. Recent advances in joint profiling of transcription and chromatin accessibility with single-cell resolution offer unprecedented opportunities to interrogate such regulatory logic. Here, we propose a nonparametric approach, TRIPOD, to detect and characterize three-way relationships between a TF, its target gene, and the accessibility of the TF’s binding site, using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data during neurogenesis and gliogenesis and identified known and novel putative regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks for gene activation and super-enhancer annotations.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 24, 2021.
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Nonparametric Interrogation of Transcriptional Regulation in Single-Cell RNA and Chromatin Accessibility Multiomic Data
Yuriko Harigaya, Zhaojun Zhang, Hongpan Zhang, Chongzhi Zang, Nancy R Zhang, Yuchao Jiang
bioRxiv 2021.09.22.461437; doi: https://doi.org/10.1101/2021.09.22.461437
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Nonparametric Interrogation of Transcriptional Regulation in Single-Cell RNA and Chromatin Accessibility Multiomic Data
Yuriko Harigaya, Zhaojun Zhang, Hongpan Zhang, Chongzhi Zang, Nancy R Zhang, Yuchao Jiang
bioRxiv 2021.09.22.461437; doi: https://doi.org/10.1101/2021.09.22.461437

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