Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Fangming Xie; Ethan J Armand; Zizhen Yao; Hanqing Liu; Anna Bartlett; M Margarita Behrens; Yang Eric Li; Jacinta D Lucero; Chongyuan Luo; Joseph R Nery; Antonio Pinto-Duarte; Olivier B Poirion; Sebastian Preissl; Angeline C Rivkin; Bosiljka Tasic; Hongkui Zeng; Bing Ren; Joseph R Ecker; Eran A Mukamel

doi:10.1016/j.xgen.2023.100342

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Cell Genom. 2023 Jun 19;3(7):100342. doi: 10.1016/j.xgen.2023.100342. eCollection 2023 Jul 12.

Authors

Fangming Xie^{1

2}, Ethan J Armand³, Zizhen Yao⁴, Hanqing Liu⁵, Anna Bartlett⁵, M Margarita Behrens⁶, Yang Eric Li⁷, Jacinta D Lucero⁶, Chongyuan Luo⁸, Joseph R Nery⁵, Antonio Pinto-Duarte⁶, Olivier B Poirion^{7

9}, Sebastian Preissl^{7

10}, Angeline C Rivkin⁵, Bosiljka Tasic⁴, Hongkui Zeng⁴, Bing Ren⁷, Joseph R Ecker^{5

11}, Eran A Mukamel³

Affiliations

¹ Department of Physics, University of California San Diego, La Jolla, CA 92037, USA.
² Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA 90095, USA.
³ Department of Cognitive Science, University of California San Diego, La Jolla, CA 92037, USA.
⁴ Allen Institute for Brain Science, Seattle, WA 98109, USA.
⁵ Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
⁶ Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
⁷ Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA 92037, USA.
⁸ Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA.
⁹ The Jackson Laboratory, Farmington, CT, USA.
¹⁰ Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
¹¹ Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.

Abstract

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.

Keywords: DNA methylation; brain; chromatin accessibility; enhancer; epigenome.

Abstract

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