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Turner AW, Hu SE, Verdezoto Mosquera JE, Ma WF, Hodonsky CJ, Wong D, Auguste GE, sol-church K, Farber E, Kundu S, Kundaje AB, Lopez NG, Ma L, Ghosh S, Onengut-Gumuscu S, Ashley EA, Quertermous T, Finn A, Leeper NJ, Kovacic JC, Bjorkegren JL, Zang C, Miller CL. Abstract 113: Cell-specific Chromatin Landscape Of Human Coronary Artery Resolves Mechanisms Of Disease Risk. Arterioscler Thromb Vasc Biol 2021. [DOI: 10.1161/atvb.41.suppl_1.113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting
cis
-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped over 320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. Using differential peak analyses we identified a number of candidate mechanisms for smooth muscle cell transition states (e.g. fibromyocytes). By integrating these profiles with GWAS meta-analysis summary data we resolved cell type-specific putative binding sites for the majority of CAD risk variants. In particular, we prioritized functional variants predicted to alter MEF2 binding in smooth muscle cells at the MRAS locus. We also identify variants predicted to alter macrophage-specific regulation of LIPA. We further employed DNA to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. Together, this single cell atlas provides a critical step towards interpreting
cis
-regulatory mechanisms in the vessel wall across the continuum of CAD risk.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Lijiang Ma
- Icahn Sch of Medicine at Mount Sinai, New York, NY
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Sazonova O, Zhao Y, Nürnberg S, Miller C, Pjanic M, Castano VG, Kim JB, Salfati EL, Kundaje AB, Bejerano G, Assimes T, Yang X, Quertermous T. Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci. PLoS Genet 2015; 11:e1005202. [PMID: 26020271 PMCID: PMC4447360 DOI: 10.1371/journal.pgen.1005202] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2014] [Accepted: 04/09/2015] [Indexed: 01/18/2023] Open
Abstract
To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction.” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology. While coronary artery disease (CAD) is due in part to environmental and metabolic factors, about half of the risk is genetically predetermined. Genome-wide association studies in human populations have identified approximately 150 sites in the genome that appear to be associated with CAD. The mechanisms by which mutations in these regions are responsible for predisposition to CAD remain largely unknown. To begin to explore how disease-specific gene sequences and disease gene function promotes pathology, we have mapped the loci and genes that are downstream of the transcription factor TCF21, which is strongly associated with CAD. By identifying genes that are regulated by TCF21 we have been able to link together multiple other CAD associated genes and begin to identify the critical molecular processes that mediate atherosclerosis in the blood vessel wall and contribute to the genesis of ischemic cardiovascular events.
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Affiliation(s)
- Olga Sazonova
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Sylvia Nürnberg
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Clint Miller
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Milos Pjanic
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Victor G. Castano
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Juyong B. Kim
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Elias L. Salfati
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Anshul B. Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Gill Bejerano
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Computer Science, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Themistocles Assimes
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America
- * E-mail:
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Benayoun BA, Pollina EA, Ucar D, Mahmoudi S, Karra K, Wong ED, Devarajan K, Daugherty AC, Kundaje AB, Mancini E, Hitz BC, Gupta R, Rando TA, Baker JC, Snyder MP, Cherry JM, Brunet A. H3K4me3 breadth is linked to cell identity and transcriptional consistency. Cell 2014; 158:673-88. [PMID: 25083876 PMCID: PMC4137894 DOI: 10.1016/j.cell.2014.06.027] [Citation(s) in RCA: 327] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2013] [Revised: 04/03/2014] [Accepted: 06/10/2014] [Indexed: 12/15/2022]
Abstract
Trimethylation of histone H3 at lysine 4 (H3K4me3) is a chromatin modification known to mark the transcription start sites of active genes. Here, we show that H3K4me3 domains that spread more broadly over genes in a given cell type preferentially mark genes that are essential for the identity and function of that cell type. Using the broadest H3K4me3 domains as a discovery tool in neural progenitor cells, we identify novel regulators of these cells. Machine learning models reveal that the broadest H3K4me3 domains represent a distinct entity, characterized by increased marks of elongation. The broadest H3K4me3 domains also have more paused polymerase at their promoters, suggesting a unique transcriptional output. Indeed, genes marked by the broadest H3K4me3 domains exhibit enhanced transcriptional consistency and [corrected] increased transcriptional levels, and perturbation of H3K4me3 breadth leads to changes in transcriptional consistency. Thus, H3K4me3 breadth contains information that could ensure transcriptional precision at key cell identity/function genes.
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Affiliation(s)
- Bérénice A Benayoun
- Department of Genetics, Stanford University, Stanford CA 94305, USA; Paul F. Glenn Laboratories for the Biology of Aging, Stanford University, Stanford CA 94305, USA
| | - Elizabeth A Pollina
- Department of Genetics, Stanford University, Stanford CA 94305, USA; Cancer Biology Program, Stanford University, Stanford CA 94305, USA
| | - Duygu Ucar
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Salah Mahmoudi
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Kalpana Karra
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Edith D Wong
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | | | | | - Anshul B Kundaje
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Elena Mancini
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Benjamin C Hitz
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Rakhi Gupta
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Thomas A Rando
- Paul F. Glenn Laboratories for the Biology of Aging, Stanford University, Stanford CA 94305, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford CA 94305, USA; RR&D REAP, VA Palo Alto Health Care Systems, Palo Alto, CA 94304,USA
| | - Julie C Baker
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - J Michael Cherry
- Department of Genetics, Stanford University, Stanford CA 94305, USA
| | - Anne Brunet
- Department of Genetics, Stanford University, Stanford CA 94305, USA; Paul F. Glenn Laboratories for the Biology of Aging, Stanford University, Stanford CA 94305, USA; Cancer Biology Program, Stanford University, Stanford CA 94305, USA.
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