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Broman MT, Nadadur RD, Perez-Cervantes C, Burnicka-Turek O, Lazarevic S, Gams A, Laforest B, Steimle JD, Iddir S, Wang Z, Smith L, Mazurek SR, Olivey HE, Zhou P, Gadek M, Shen KM, Khan Z, Theisen JW, Yang XH, Ikegami K, Efimov IR, Pu WT, Weber CR, McNally EM, Svensson EC, Moskowitz IP. A Genomic Link From Heart Failure to Atrial Fibrillation Risk: FOG2 Modulates a TBX5/GATA4-Dependent Atrial Gene Regulatory Network. Circulation 2024; 149:1205-1230. [PMID: 38189150 PMCID: PMC11152454 DOI: 10.1161/circulationaha.123.066804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024]
Abstract
BACKGROUND The relationship between heart failure (HF) and atrial fibrillation (AF) is clear, with up to half of patients with HF progressing to AF. The pathophysiological basis of AF in the context of HF is presumed to result from atrial remodeling. Upregulation of the transcription factor FOG2 (friend of GATA2; encoded by ZFPM2) is observed in human ventricles during HF and causes HF in mice. METHODS FOG2 expression was assessed in human atria. The effect of adult-specific FOG2 overexpression in the mouse heart was evaluated by whole animal electrophysiology, in vivo organ electrophysiology, cellular electrophysiology, calcium flux, mouse genetic interactions, gene expression, and genomic function, including a novel approach for defining functional transcription factor interactions based on overlapping effects on enhancer noncoding transcription. RESULTS FOG2 is significantly upregulated in the human atria during HF. Adult cardiomyocyte-specific FOG2 overexpression in mice caused primary spontaneous AF before the development of HF or atrial remodeling. FOG2 overexpression generated arrhythmia substrate and trigger in cardiomyocytes, including calcium cycling defects. We found that FOG2 repressed atrial gene expression promoted by TBX5. FOG2 bound a subset of GATA4 and TBX5 co-bound genomic locations, defining a shared atrial gene regulatory network. FOG2 repressed TBX5-dependent transcription from a subset of co-bound enhancers, including a conserved enhancer at the Atp2a2 locus. Atrial rhythm abnormalities in mice caused by Tbx5 haploinsufficiency were rescued by Zfpm2 haploinsufficiency. CONCLUSIONS Transcriptional changes in the atria observed in human HF directly antagonize the atrial rhythm gene regulatory network, providing a genomic link between HF and AF risk independent of atrial remodeling.
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Affiliation(s)
- Michael T. Broman
- Department of Medicine, Section of Cardiology, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637
| | - Rangarajan D. Nadadur
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Carlos Perez-Cervantes
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Ozanna Burnicka-Turek
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Sonja Lazarevic
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Anna Gams
- Department of Biomedical Engineering, George Washington University
| | - Brigitte Laforest
- Department of Medicine, Section of Cardiology, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637
| | - Jeffrey D. Steimle
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Sabrina Iddir
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Zhezhen Wang
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Linsin Smith
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Stefan R. Mazurek
- Department of Medicine, Section of Cardiology, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637
| | - Harold E. Olivey
- Department of Biology, Indiana University Northwest, Gary, IN 46408
| | | | - Margaret Gadek
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Kaitlyn M. Shen
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Zoheb Khan
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Joshua W.M. Theisen
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Xinan H. Yang
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
| | - Kohta Ikegami
- Division of Molecular and Cardiovascular Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229
| | - Igor R. Efimov
- Department of Biomedical Engineering, George Washington University
| | - William T. Pu
- Harvard Stem Cell Institute, Harvard University, Cambridge, MA, 02138
- Department of Cardiology, Boston Children’s Hospital, Boston, MA, 02115
| | | | - Elizabeth M. McNally
- Center for Genetic Medicine, Northwestern University, 303 E. Superior, SQ5-516, Chicago, IL 60611
| | | | - Ivan P. Moskowitz
- Department of Pediatrics, University of Chicago, Chicago, IL 60637
- Department of Pathology, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60637
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2
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Wang C, Chen C, Lei B, Qin S, Zhang Y, Li K, Zhang S, Liu Y. Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs. Genet Sel Evol 2024; 56:28. [PMID: 38594607 PMCID: PMC11003151 DOI: 10.1186/s12711-024-00897-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 04/03/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking. RESULTS Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model. CONCLUSIONS Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.
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Affiliation(s)
- Chao Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Choulin Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Bowen Lei
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Shenghua Qin
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Yuanyuan Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- School of Life Sciences, Henan University, Kaifeng, 475004, People's Republic of China
- Shenzhen Research Institute of Henan University, Shenzhen, 518000, People's Republic of China
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Song Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China.
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan, 528226, People's Republic of China.
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3
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Kim SS, Truong B, Jagadeesh K, Dey KK, Shen AZ, Raychaudhuri S, Kellis M, Price AL. Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types. Nat Commun 2024; 15:563. [PMID: 38233398 PMCID: PMC10794712 DOI: 10.1038/s41467-024-44742-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 01/02/2024] [Indexed: 01/19/2024] Open
Abstract
Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.
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Affiliation(s)
- Samuel S Kim
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, UK.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK.
| | - Buu Truong
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, UK.
| | - Karthik Jagadeesh
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK
| | - Kushal K Dey
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Amber Z Shen
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Soumya Raychaudhuri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, UK
| | - Alkes L Price
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, UK.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, UK.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, UK.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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4
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Zhu X, Ma S, Wong WH. Genetic effects of sequence-conserved enhancer-like elements on human complex traits. Genome Biol 2024; 25:1. [PMID: 38167462 PMCID: PMC10759394 DOI: 10.1186/s13059-023-03142-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits. RESULTS Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes. CONCLUSIONS Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.
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Affiliation(s)
- Xiang Zhu
- Department of Statistics, The Pennsylvania State University, 326 Thomas Building, University Park, 16802, PA, USA.
- Huck Institutes of the Life Sciences, The Pennsylvania State University, 201 Huck Life Sciences Building, University Park, 16802, PA, USA.
- Department of Statistics, Stanford University, 390 Jane Stanford Way, Stanford, 94305, CA, USA.
| | - Shining Ma
- Department of Statistics, Stanford University, 390 Jane Stanford Way, Stanford, 94305, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road MC5464, Stanford, 94305, CA, USA
| | - Wing Hung Wong
- Department of Statistics, Stanford University, 390 Jane Stanford Way, Stanford, 94305, CA, USA.
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road MC5464, Stanford, 94305, CA, USA.
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5
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Guo MG, Reynolds DL, Ang CE, Liu Y, Zhao Y, Donohue LKH, Siprashvili Z, Yang X, Yoo Y, Mondal S, Hong A, Kain J, Meservey L, Fabo T, Elfaki I, Kellman LN, Abell NS, Pershad Y, Bayat V, Etminani P, Holodniy M, Geschwind DH, Montgomery SB, Duncan LE, Urban AE, Altman RB, Wernig M, Khavari PA. Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases. Nat Genet 2023; 55:1876-1891. [PMID: 37857935 PMCID: PMC10859123 DOI: 10.1038/s41588-023-01533-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/15/2023] [Indexed: 10/21/2023]
Abstract
Noncoding variants of presumed regulatory function contribute to the heritability of neuropsychiatric disease. A total of 2,221 noncoding variants connected to risk for ten neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, borderline personality disorder, major depression, generalized anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder and schizophrenia, were studied in developing human neural cells. Integrating epigenomic and transcriptomic data with massively parallel reporter assays identified differentially-active single-nucleotide variants (daSNVs) in specific neural cell types. Expression-gene mapping, network analyses and chromatin looping nominated candidate disease-relevant target genes modulated by these daSNVs. Follow-up integration of daSNV gene editing with clinical cohort analyses suggested that magnesium transport dysfunction may increase neuropsychiatric disease risk and indicated that common genetic pathomechanisms may mediate specific symptoms that are shared across multiple neuropsychiatric diseases.
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Affiliation(s)
- Margaret G Guo
- Stanford Program in Biomedical Informatics, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - David L Reynolds
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - Cheen E Ang
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Yingfei Liu
- Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA, USA
- Institute of Neurobiology, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yang Zhao
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - Laura K H Donohue
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Zurab Siprashvili
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - Xue Yang
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Stanford Program in Cancer Biology, Stanford University, Stanford, CA, USA
| | - Yongjin Yoo
- Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Smarajit Mondal
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - Audrey Hong
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | - Jessica Kain
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Tania Fabo
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Ibtihal Elfaki
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Laura N Kellman
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Stanford Program in Cancer Biology, Stanford University, Stanford, CA, USA
| | - Nathan S Abell
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Yash Pershad
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | | | - Mark Holodniy
- Public Health Surveillance and Research, Department of Veterans Affairs, Washington, DC, USA
- Division of Infectious Disease & Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Daniel H Geschwind
- Program in Neurobehavioral Genetics, Semel Institute, UCLA, Los Angeles, CA, USA
| | - Stephen B Montgomery
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Laramie E Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Alexander E Urban
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Russ B Altman
- Stanford Program in Biomedical Informatics, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Marius Wernig
- Department of Pathology, Stanford University, Stanford, CA, USA
- Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA, USA
| | - Paul A Khavari
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA.
- Stanford Program in Cancer Biology, Stanford University, Stanford, CA, USA.
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA.
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6
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Dong C, Shen S, Keleş S. AdaLiftOver: high-resolution identification of orthologous regulatory elements with Adaptive liftOver. Bioinformatics 2023; 39:btad149. [PMID: 37004197 PMCID: PMC10085516 DOI: 10.1093/bioinformatics/btad149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 03/02/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023] Open
Abstract
MOTIVATION Elucidating functionally similar orthologous regulatory regions for human and model organism genomes is critical for exploiting model organism research and advancing our understanding of results from genome-wide association studies (GWAS). Sequence conservation is the de facto approach for finding orthologous non-coding regions between human and model organism genomes. However, existing methods for mapping non-coding genomic regions across species are challenged by the multi-mapping, low precision, and low mapping rate issues. RESULTS We develop Adaptive liftOver (AdaLiftOver), a large-scale computational tool for identifying functionally similar orthologous non-coding regions across species. AdaLiftOver builds on the UCSC liftOver framework to extend the query regions and prioritizes the resulting candidate target regions based on the conservation of the epigenomic and the sequence grammar features. Evaluations of AdaLiftOver with multiple case studies, spanning both genomic intervals from epigenome datasets across a wide range of model organisms and GWAS SNPs, yield AdaLiftOver as a versatile method for deriving hard-to-obtain human epigenome datasets as well as reliably identifying orthologous loci for GWAS SNPs. AVAILABILITY AND IMPLEMENTATION The R package and the data for AdaLiftOver is available from https://github.com/keleslab/AdaLiftOver.
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Affiliation(s)
- Chenyang Dong
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA
| | - Siqi Shen
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI 53706, USA
| | - Sündüz Keleş
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI 53706, USA
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7
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Ardesch DJ, Libedinsky I, Scholtens LH, Wei Y, van den Heuvel MP. Convergence of brain transcriptomic and neuroimaging patterns in schizophrenia, bipolar disorder, autism spectrum disorder and major depression disorder. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023. [DOI: 10.1016/j.bpsc.2022.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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8
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Ibarra IL, Ratnu VS, Gordillo L, Hwang I, Mariani L, Weinand K, Hammarén HM, Heck J, Bulyk ML, Savitski MM, Zaugg JB, Noh K. Comparative chromatin accessibility upon BDNF stimulation delineates neuronal regulatory elements. Mol Syst Biol 2022; 18:e10473. [PMID: 35996956 PMCID: PMC9396287 DOI: 10.15252/msb.202110473] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/28/2022] [Accepted: 08/01/2022] [Indexed: 12/30/2022] Open
Abstract
Neuronal stimulation induced by the brain-derived neurotrophic factor (BDNF) triggers gene expression, which is crucial for neuronal survival, differentiation, synaptic plasticity, memory formation, and neurocognitive health. However, its role in chromatin regulation is unclear. Here, using temporal profiling of chromatin accessibility and transcription in mouse primary cortical neurons upon either BDNF stimulation or depolarization (KCl), we identify features that define BDNF-specific chromatin-to-gene expression programs. Enhancer activation is an early event in the regulatory control of BDNF-treated neurons, where the bZIP motif-binding Fos protein pioneered chromatin opening and cooperated with co-regulatory transcription factors (Homeobox, EGRs, and CTCF) to induce transcription. Deleting cis-regulatory sequences affect BDNF-mediated Arc expression, a regulator of synaptic plasticity. BDNF-induced accessible regions are linked to preferential exon usage by neurodevelopmental disorder-related genes and the heritability of neuronal complex traits, which were validated in human iPSC-derived neurons. Thus, we provide a comprehensive view of BDNF-mediated genome regulatory features using comparative genomic approaches to dissect mammalian neuronal stimulation.
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Affiliation(s)
- Ignacio L Ibarra
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL)HeidelbergGermany
- Faculty of BiosciencesCollaboration for Joint PhD Degree between EMBL and Heidelberg UniversityHeidelbergGermany
- Institute of Computational BiologyHelmholtz Center MunichOberschleißheimGermany
| | - Vikram S Ratnu
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Lucia Gordillo
- Faculty of BiosciencesCollaboration for Joint PhD Degree between EMBL and Heidelberg UniversityHeidelbergGermany
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - In‐Young Hwang
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL)HeidelbergGermany
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Luca Mariani
- Division of Genetics, Department of MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMAUSA
| | - Kathryn Weinand
- Division of Genetics, Department of MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMAUSA
| | - Henrik M Hammarén
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL)HeidelbergGermany
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Jennifer Heck
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Martha L Bulyk
- Division of Genetics, Department of MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMAUSA
- Department of PathologyBrigham and Women's Hospital and Harvard Medical SchoolBostonMAUSA
| | - Mikhail M Savitski
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Judith B Zaugg
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Kyung‐Min Noh
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
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9
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Fan CC, Loughnan R, Makowski C, Pecheva D, Chen CH, Hagler DJ, Thompson WK, Parker N, van der Meer D, Frei O, Andreassen OA, Dale AM. Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain. Nat Commun 2022; 13:2423. [PMID: 35505052 PMCID: PMC9065144 DOI: 10.1038/s41467-022-30110-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 04/12/2022] [Indexed: 11/12/2022] Open
Abstract
The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.
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Affiliation(s)
- Chun Chieh Fan
- Population Neuroscience and Genetics Lab, University of California, San Diego, La Jolla, CA, USA. .,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA. .,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
| | - Robert Loughnan
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Diliana Pecheva
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Chi-Hua Chen
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Donald J Hagler
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Wesley K Thompson
- Population Neuroscience and Genetics Lab, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA.,Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA.,Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA
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10
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Powell G, Long H, Zolkiewski L, Dumbell R, Mallon AM, Lindgren CM, Simon MM. Modelling the genetic aetiology of complex disease: human-mouse conservation of noncoding features and disease-associated loci. Biol Lett 2022; 18:20210630. [PMID: 35317627 PMCID: PMC8941414 DOI: 10.1098/rsbl.2021.0630] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Understanding the genetic aetiology of loci associated with a disease is crucial for developing preventative measures and effective treatments. Mouse models are used extensively to understand human pathobiology and mechanistic functions of disease-associated loci. However, the utility of mouse models is limited in part by evolutionary divergence in transcription regulation for pathways of interest. Here, we summarize the alignment of genomic (exonic and multi-cell regulatory) annotations alongside Mendelian and complex disease-associated variant sites between humans and mice. Our results highlight the importance of understanding evolutionary divergence in transcription regulation when interpreting functional studies using mice as models for human disease variants.
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Affiliation(s)
- George Powell
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.,MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK
| | - Helen Long
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.,MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK
| | - Louisa Zolkiewski
- MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK.,Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Rebecca Dumbell
- Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK
| | - Ann-Marie Mallon
- MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.,Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK.,Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michelle M Simon
- MRC Harwell Institute, Mammalian Genetics Unit, Oxfordshire OX11 0RD, UK
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11
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Dong C, Simonett SP, Shin S, Stapleton DS, Schueler KL, Churchill GA, Lu L, Liu X, Jin F, Li Y, Attie AD, Keller MP, Keleş S. INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants. Genome Biol 2021; 22:241. [PMID: 34425882 PMCID: PMC8381555 DOI: 10.1186/s13059-021-02450-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 08/02/2021] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies reveal many non-coding variants associated with complex traits. However, model organism studies largely remain as an untapped resource for unveiling the effector genes of non-coding variants. We develop INFIMA, Integrative Fine-Mapping, to pinpoint causal SNPs for diversity outbred (DO) mice eQTL by integrating founder mice multi-omics data including ATAC-seq, RNA-seq, footprinting, and in silico mutation analysis. We demonstrate INFIMA's superior performance compared to alternatives with human and mouse chromatin conformation capture datasets. We apply INFIMA to identify novel effector genes for GWAS variants associated with diabetes. The results of the application are available at http://www.statlab.wisc.edu/shiny/INFIMA/ .
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Affiliation(s)
- Chenyang Dong
- Department of Statistics, University of Wisconsin-Madison, Madison, WI USA
| | - Shane P. Simonett
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Sunyoung Shin
- Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX USA
| | - Donnie S. Stapleton
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Kathryn L. Schueler
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | | | - Leina Lu
- Case Western University, Cleveland, OH USA
| | | | - Fulai Jin
- Case Western University, Cleveland, OH USA
| | - Yan Li
- Case Western University, Cleveland, OH USA
| | - Alan D. Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Mark P. Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Sündüz Keleş
- Department of Statistics, University of Wisconsin-Madison, Madison, WI USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI USA
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12
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Zhao H, Tu Z, Liu Y, Zong Z, Li J, Liu H, Xiong F, Zhan J, Hu X, Xie W. PlantDeepSEA, a deep learning-based web service to predict the regulatory effects of genomic variants in plants. Nucleic Acids Res 2021; 49:W523-W529. [PMID: 34037796 PMCID: PMC8262748 DOI: 10.1093/nar/gkab383] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/09/2021] [Accepted: 04/28/2021] [Indexed: 12/13/2022] Open
Abstract
Characterizing regulatory effects of genomic variants in plants remains a challenge. Although several tools based on deep-learning models and large-scale chromatin-profiling data have been available to predict regulatory elements and variant effects, no dedicated tools or web services have been reported in plants. Here, we present PlantDeepSEA as a deep learning-based web service to predict regulatory effects of genomic variants in multiple tissues of six plant species (including four crops). PlantDeepSEA provides two main functions. One is called Variant Effector, which aims to predict the effects of sequence variants on chromatin accessibility. Another is Sequence Profiler, a utility that performs 'in silico saturated mutagenesis' analysis to discover high-impact sites (e.g., cis-regulatory elements) within a sequence. When validated on independent test sets, the area under receiver operating characteristic curve of deep learning models in PlantDeepSEA ranges from 0.93 to 0.99. We demonstrate the usability of the web service with two examples. PlantDeepSEA could help to prioritize regulatory causal variants and might improve our understanding of their mechanisms of action in different tissues in plants. PlantDeepSEA is available at http://plantdeepsea.ncpgr.cn/.
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Affiliation(s)
- Hu Zhao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zhuo Tu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yinmeng Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zhanxiang Zong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jiacheng Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Hao Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Feng Xiong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jinling Zhan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xuehai Hu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.,Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China
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13
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Hocker JD, Poirion OB, Zhu F, Buchanan J, Zhang K, Chiou J, Wang TM, Zhang Q, Hou X, Li YE, Zhang Y, Farah EN, Wang A, McCulloch AD, Gaulton KJ, Ren B, Chi NC, Preissl S. Cardiac cell type-specific gene regulatory programs and disease risk association. SCIENCE ADVANCES 2021; 7:eabf1444. [PMID: 33990324 PMCID: PMC8121433 DOI: 10.1126/sciadv.abf1444] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 03/25/2021] [Indexed: 05/07/2023]
Abstract
Misregulated gene expression in human hearts can result in cardiovascular diseases that are leading causes of mortality worldwide. However, the limited information on the genomic location of candidate cis-regulatory elements (cCREs) such as enhancers and promoters in distinct cardiac cell types has restricted the understanding of these diseases. Here, we defined >287,000 cCREs in the four chambers of the human heart at single-cell resolution, which revealed cCREs and candidate transcription factors associated with cardiac cell types in a region-dependent manner and during heart failure. We further found cardiovascular disease-associated genetic variants enriched within these cCREs including 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Additional functional studies revealed that two of these variants affect a cCRE controlling KCNH2/HERG expression and action potential repolarization. Overall, this atlas of human cardiac cCREs provides the foundation for illuminating cell type-specific gene regulation in human hearts during health and disease.
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Affiliation(s)
- James D Hocker
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Olivier B Poirion
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA
| | - Fugui Zhu
- Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Justin Buchanan
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA
| | - Kai Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Joshua Chiou
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Tsui-Min Wang
- Departments of Bioengineering and Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Qingquan Zhang
- Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA
| | - Yang E Li
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Elie N Farah
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA
| | - Andrew D McCulloch
- Departments of Bioengineering and Medicine, University of California, San Diego, La Jolla, CA, USA
- Institute for Engineering in Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Neil C Chi
- Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California, San Diego, La Jolla, CA, USA.
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