151
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Wang A. Distinctive functional regime of endogenous lncRNAs in dark regions of human genome. Comput Struct Biotechnol J 2022; 20:2381-2390. [PMID: 35664234 PMCID: PMC9127114 DOI: 10.1016/j.csbj.2022.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 05/10/2022] [Accepted: 05/12/2022] [Indexed: 11/03/2022] Open
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152
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Pratt BM, Won H. Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders. Semin Cell Dev Biol 2022; 121:153-160. [PMID: 34483043 PMCID: PMC8761161 DOI: 10.1016/j.semcdb.2021.08.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 08/18/2021] [Accepted: 08/23/2021] [Indexed: 01/03/2023]
Abstract
Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.
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Affiliation(s)
- Brandon M Pratt
- Department of Pharmacology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA.
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153
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Yu F, Cato LD, Weng C, Liggett LA, Jeon S, Xu K, Chiang CWK, Wiemels JL, Weissman JS, de Smith AJ, Sankaran VG. Variant to function mapping at single-cell resolution through network propagation. Nat Biotechnol 2022; 40:1644-1653. [PMID: 35668323 PMCID: PMC9646486 DOI: 10.1038/s41587-022-01341-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/29/2022] [Indexed: 12/30/2022]
Abstract
Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.
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Affiliation(s)
- Fulong Yu
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Liam D. Cato
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Chen Weng
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.270301.70000 0001 2292 6283Whitehead Institute for Biomedical Research, Cambridge, MA USA
| | - L. Alexander Liggett
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Soyoung Jeon
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Keren Xu
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Charleston W. K. Chiang
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA USA
| | - Joseph L. Wiemels
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Jonathan S. Weissman
- grid.270301.70000 0001 2292 6283Whitehead Institute for Biomedical Research, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Adam J. de Smith
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Vijay G. Sankaran
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.511171.2Harvard Stem Cell Institute, Cambridge, MA USA
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154
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Chien P, Xi H, Pyle AD. Recapitulating human myogenesis ex vivo using human pluripotent stem cells. Exp Cell Res 2021; 411:112990. [PMID: 34973262 DOI: 10.1016/j.yexcr.2021.112990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 12/15/2021] [Accepted: 12/22/2021] [Indexed: 11/25/2022]
Abstract
Human pluripotent stem cells (hPSCs) provide a human model for developmental myogenesis, disease modeling and development of therapeutics. Differentiation of hPSCs into muscle stem cells has the potential to provide a cell-based therapy for many skeletal muscle wasting diseases. This review describes the current state of hPSCs towards recapitulating human myogenesis ex vivo, considerations of stem cell and progenitor cell state as well as function for future use of hPSC-derived muscle cells in regenerative medicine.
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Affiliation(s)
- Peggie Chien
- Department of Microbiology, Immunology and Molecular Genetics, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
| | - Haibin Xi
- Department of Microbiology, Immunology and Molecular Genetics, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
| | - April D Pyle
- Department of Microbiology, Immunology and Molecular Genetics, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA.
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155
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Ruff GL, Murphy KE, Smith ZR, Vertino PM, Murphy PJ. Subtype-Independent ANP32E Reduction During Breast Cancer Progression in Accordance with Chromatin Relaxation. BMC Cancer 2021; 21:1342. [PMID: 34922480 PMCID: PMC8684129 DOI: 10.1186/s12885-021-09077-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/30/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Chromatin state provides a clear decipherable blueprint for maintenance of transcriptional patterns, exemplifying a mitotically stable form of cellular programming in dividing cells. In this regard, genomic studies of chromatin states within cancerous tissues have the potential to uncover novel aspects of tumor biology and unique mechanisms associated with disease phenotypes and outcomes. The degree to which chromatin state differences occur in accordance with breast cancer features has not been established. METHODS We applied a series of unsupervised computational methods to identify chromatin and molecular differences associated with discrete physiologies across human breast cancer tumors. RESULTS Chromatin patterns alone are capable of stratifying tumors in association with cancer subtype and disease progression. Major differences occur at DNA motifs for the transcription factor FOXA1, in hormone receptor-positive tumors, and motifs for SOX9 in Basal-like tumors. We find that one potential driver of this effect, the histone chaperone ANP32E, is inversely correlated with tumor progression and relaxation of chromatin at FOXA1 binding sites. Tumors with high levels of ANP32E exhibit an immune response and proliferative gene expression signature, whereas tumors with low ANP32E levels appear programmed for differentiation. CONCLUSIONS Our results indicate that ANP32E may function through chromatin state regulation to control breast cancer differentiation and tumor plasticity. This study sets a precedent for future computational studies of chromatin changes in carcinogenesis.
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Affiliation(s)
- Garrett L Ruff
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Kristin E Murphy
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Zachary R Smith
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Wilmot Cancer Institute, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY, 14624, USA
| | - Paula M Vertino
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Wilmot Cancer Institute, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY, 14624, USA
| | - Patrick J Murphy
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, 14642, USA.
- Wilmot Cancer Institute, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY, 14624, USA.
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156
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Eksi SE, Chitsazan A, Sayar Z, Thomas GV, Fields AJ, Kopp RP, Spellman PT, Adey AC. Epigenetic loss of heterogeneity from low to high grade localized prostate tumours. Nat Commun 2021; 12:7292. [PMID: 34911933 PMCID: PMC8674326 DOI: 10.1038/s41467-021-27615-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 11/30/2021] [Indexed: 12/13/2022] Open
Abstract
Identifying precise molecular subtypes attributable to specific stages of localized prostate cancer has proven difficult due to high levels of heterogeneity. Bulk assays represent a population-average, which mask the heterogeneity that exists at the single-cell level. In this work, we sequence the accessible chromatin regions of 14,424 single-cells from 18 flash-frozen prostate tumours. We observe shared chromatin features among low-grade prostate cancer cells are lost in high-grade tumours. Despite this loss, high-grade tumours exhibit an enrichment for FOXA1, HOXB13 and CDX2 transcription factor binding sites, indicating a shared trans-regulatory programme. We identify two unique genes encoding neuronal adhesion molecules that are highly accessible in high-grade prostate tumours. We show NRXN1 and NLGN1 expression in epithelial, endothelial, immune and neuronal cells in prostate cancer using cyclic immunofluorescence. Our results provide a deeper understanding of the active gene regulatory networks in primary prostate tumours, critical for molecular stratification of the disease.
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Affiliation(s)
- Sebnem Ece Eksi
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA.
- Department of Biomedical Engineering, School of Medicine, OHSU, Portland, OR, 97209, USA.
| | - Alex Chitsazan
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA
| | - Zeynep Sayar
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA
- Department of Biomedical Engineering, School of Medicine, OHSU, Portland, OR, 97209, USA
| | - George V Thomas
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA
- Department of Pathology & Laboratory Medicine, School of Medicine, OHSU, Portland, OR, 97239, USA
| | - Andrew J Fields
- Department of Molecular and Medical Genetics, School of Medicine, OHSU, Portland, OR, 97239, USA
| | - Ryan P Kopp
- Department of Urology, School of Medicine, OHSU, Portland, OR, 97239, USA
| | - Paul T Spellman
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA
- Department of Molecular and Medical Genetics, School of Medicine, OHSU, Portland, OR, 97239, USA
| | - Andrew C Adey
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, OHSU, Portland, OR, 97239, USA.
- Department of Molecular and Medical Genetics, School of Medicine, OHSU, Portland, OR, 97239, USA.
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157
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Lam DD, Nikolic AA, Zhao C, Mirza-Schreiber N, Krężel W, Oexle K, Winkelmann J. Intronic elements associated with insomnia and restless legs syndrome exhibit cell type-specific epigenetic features contributing to MEIS1 regulation. Hum Mol Genet 2021; 31:1733-1746. [PMID: 34888668 DOI: 10.1093/hmg/ddab355] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/25/2021] [Accepted: 12/05/2021] [Indexed: 12/13/2022] Open
Abstract
A highly evolutionarily conserved MEIS1 intronic region is strongly associated with restless legs syndrome (RLS) and insomnia. To understand its regulatory function, we dissected the region by analyzing chromatin accessibility, enhancer-promoter contacts, DNA methylation, and eQTLs in different human neural cell types and tissues. We observed specific activity with respect to cell type and developmental maturation, indicating a prominent role for distinct highly conserved intronic elements in forebrain inhibitory neuron differentiation. Two elements were hypomethylated in neural cells with higher MEIS1 expression, suggesting a role of enhancer demethylation in gene regulation. MEIS1 eQTLs showed a striking modular chromosomal distribution, with forebrain eQTLs clustering in intron 8/9. CRISPR interference targeting of individual elements in this region attenuated MEIS1 expression, revealing a complex regulatory interplay of distinct elements. In summary, we found that MEIS1 regulation is organized in a modular pattern. Disease-associated intronic regulatory elements control MEIS1 expression with cell type and maturation stage specificity, particularly in the inhibitory neuron lineage. The precise spatiotemporal activity of these elements likely contributes to the pathogenesis of insomnia and RLS.
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Affiliation(s)
- Daniel D Lam
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Ana Antic Nikolic
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Chen Zhao
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Nazanin Mirza-Schreiber
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wojciech Krężel
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.,Institut de la Santé et de la Recherche Médicale, U964, Illkirch, France.,Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France.,Université de Strasbourg, Illkirch, France
| | - Konrad Oexle
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany.,Chair of Neurogenetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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158
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Schilder BM, Navarro E, Raj T. Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms. Neurobiol Dis 2021; 163:105580. [PMID: 34871738 PMCID: PMC10101343 DOI: 10.1016/j.nbd.2021.105580] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 11/17/2021] [Accepted: 12/02/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.
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Affiliation(s)
- Brian M Schilder
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; UK Dementia Research Institute at Imperial College London, London, United Kingdom.
| | - Elisa Navarro
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Sección Departamental de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
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159
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Gao W, Gallardo-Dodd CJ, Kutter C. Cell type-specific analysis by single-cell profiling identifies a stable mammalian tRNA-mRNA interface and increased translation efficiency in neurons. Genome Res 2021; 32:97-110. [PMID: 34857654 PMCID: PMC8744671 DOI: 10.1101/gr.275944.121] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 11/24/2021] [Indexed: 11/24/2022]
Abstract
The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using available mouse and human single-cell RNA-sequencing atlases. After showing the robustness of ATAC-sequencing measurements for the analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in both mouse and human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons, which clustered separately from other cell types. Integration of these data sets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of tRNAAla (AGC) anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell type–specific ribosome profiling, suggesting that the reduction of tRNAAla (AGC) anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency resolved at the cell-type level with single-cell information, identifies a conserved landscape of translation elongation across mammalian cellular diversity and evolution.
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Affiliation(s)
- William Gao
- Department of Microbiology, Tumor, and Cell Biology, Karolinska Institute, Science for Life Laboratory, 171 77, Stockholm, Sweden
| | - Carlos J Gallardo-Dodd
- Department of Microbiology, Tumor, and Cell Biology, Karolinska Institute, Science for Life Laboratory, 171 77, Stockholm, Sweden
| | - Claudia Kutter
- Department of Microbiology, Tumor, and Cell Biology, Karolinska Institute, Science for Life Laboratory, 171 77, Stockholm, Sweden
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160
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Marcel SS, Quimby AL, Noel MP, Jaimes OC, Mehrab-Mohseni M, Ashur SA, Velasco B, Tsuruta JK, Kasoji SK, Santos CM, Dayton PA, Parker JS, Davis IJ, Pattenden SG. Genome-wide cancer-specific chromatin accessibility patterns derived from archival processed xenograft tumors. Genome Res 2021; 31:2327-2339. [PMID: 34815311 PMCID: PMC8647830 DOI: 10.1101/gr.275219.121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 10/22/2021] [Indexed: 01/01/2023]
Abstract
Chromatin accessibility states that influence gene expression and other nuclear processes can be altered in disease. The constellation of transcription factors and chromatin regulatory complexes in cells results in characteristic patterns of chromatin accessibility. The study of these patterns in tissues has been limited because existing chromatin accessibility assays are ineffective for archival formalin-fixed, paraffin-embedded (FFPE) tissues. We have developed a method to efficiently extract intact chromatin from archival tissue via enhanced cavitation with a nanodroplet reagent consisting of a lipid shell with a liquid perfluorocarbon core. Inclusion of nanodroplets during the extraction of chromatin from FFPE tissues enhances the recovery of intact accessible and nucleosome-bound chromatin. We show that the addition of nanodroplets to the chromatin accessibility assay formaldehyde-assisted isolation of regulatory elements (FAIRE), does not affect the accessible chromatin signal. Applying the technique to FFPE human tumor xenografts, we identified tumor-relevant regions of accessible chromatin shared with those identified in primary tumors. Further, we deconvoluted non-tumor signal to identify cellular components of the tumor microenvironment. Incorporation of this method of enhanced cavitation into FAIRE offers the potential for extending chromatin accessibility to clinical diagnosis and personalized medicine, while also enabling the exploration of gene regulatory mechanisms in archival samples.
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Affiliation(s)
- Shelsa S Marcel
- Curriculum in Bioinformatics and Computational Biology, Curriculum in Genetics and Molecular Biology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Austin L Quimby
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Melodie P Noel
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Oscar C Jaimes
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Marjan Mehrab-Mohseni
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Joint Department of Biomedical Engineering, The University of North Carolina and North Carolina State University, Chapel Hill, North Carolina 27599, USA
| | - Suud A Ashur
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Brian Velasco
- Joint Department of Biomedical Engineering, The University of North Carolina and North Carolina State University, Chapel Hill, North Carolina 27599, USA
| | - James K Tsuruta
- Joint Department of Biomedical Engineering, The University of North Carolina and North Carolina State University, Chapel Hill, North Carolina 27599, USA
| | - Sandeep K Kasoji
- Triangle Biotechnology, Incorporated, Chapel Hill, North Carolina 27517, USA
| | - Charlene M Santos
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Paul A Dayton
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Joint Department of Biomedical Engineering, The University of North Carolina and North Carolina State University, Chapel Hill, North Carolina 27599, USA
| | - Joel S Parker
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Ian J Davis
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Division of Pediatric Hematology-Oncology, Department of Pediatrics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Samantha G Pattenden
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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161
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Mulqueen RM, Pokholok D, O’Connell BL, Thornton CA, Zhang F, O’Roak BJ, Link J, Yardımcı GG, Sears RC, Steemers FJ, Adey AC. High-content single-cell combinatorial indexing. Nat Biotechnol 2021; 39:1574-1580. [PMID: 34226710 PMCID: PMC8678206 DOI: 10.1038/s41587-021-00962-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 05/20/2021] [Indexed: 02/06/2023]
Abstract
Single-cell combinatorial indexing (sci) with transposase-based library construction increases the throughput of single-cell genomics assays but produces sparse coverage in terms of usable reads per cell. We develop symmetrical strand sci ('s3'), a uracil-based adapter switching approach that improves the rate of conversion of source DNA into viable sequencing library fragments following tagmentation. We apply this chemistry to assay chromatin accessibility (s3-assay for transposase-accessible chromatin, s3-ATAC) in human cortical and mouse whole-brain tissues, with mouse datasets demonstrating a six- to 13-fold improvement in usable reads per cell compared with other available methods. Application of s3 to single-cell whole-genome sequencing (s3-WGS) and to whole-genome plus chromatin conformation (s3-GCC) yields 148- and 14.8-fold improvements, respectively, in usable reads per cell compared with sci-DNA-sequencing and sci-HiC. We show that s3-WGS and s3-GCC resolve subclonal genomic alterations in patient-derived pancreatic cancer cell lines. We expect that the s3 platform will be compatible with other transposase-based techniques, including sci-MET or CUT&Tag.
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Affiliation(s)
- Ryan M. Mulqueen
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
| | | | - Brendan L. O’Connell
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
| | - Casey A. Thornton
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
| | | | - Brian J. O’Roak
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
| | - Jason Link
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR,Oregon Health & Science University, Knight Cancer Institute, Portland, OR,Oregon Health & Science University, Brendan Colson Center for Pancreatic Care, Portland, OR
| | - Galip Gürkan Yardımcı
- Oregon Health & Science University, Knight Cancer Institute, Portland, OR,Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
| | - Rosalie C. Sears
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR,Oregon Health & Science University, Knight Cancer Institute, Portland, OR,Oregon Health & Science University, Brendan Colson Center for Pancreatic Care, Portland, OR,Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
| | | | - Andrew C. Adey
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR,Oregon Health & Science University, Knight Cancer Institute, Portland, OR,Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR,Oregon Health & Science University, Department of Oncological Sciences, Portland, OR,Oregon Health & Science University, Knight Cardiovascular Institute, Portland, OR,Correspondence to
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162
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Tuong ZK, Stewart BJ, Guo SA, Clatworthy MR. Epigenetics and tissue immunity-Translating environmental cues into functional adaptations. Immunol Rev 2021; 305:111-136. [PMID: 34821397 DOI: 10.1111/imr.13036] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/26/2021] [Accepted: 10/28/2021] [Indexed: 12/21/2022]
Abstract
There is an increasing appreciation that many innate and adaptive immune cell subsets permanently reside within non-lymphoid organs, playing a critical role in tissue homeostasis and defense. The best characterized are macrophages and tissue-resident T lymphocytes that work in concert with organ structural cells to generate appropriate immune responses and are functionally shaped by organ-specific environmental cues. The interaction of tissue epithelial, endothelial and stromal cells is also required to attract, differentiate, polarize and maintain organ immune cells in their tissue niche. All of these processes require dynamic regulation of cellular transcriptional programmes, with epigenetic mechanisms playing a critical role, including DNA methylation and post-translational histone modifications. A failure to appropriately regulate immune cell transcription inevitably results in inadequate or inappropriate immune responses and organ pathology. Here, with a focus on the mammalian kidney, an organ which generates differing regional environmental cues (including hypersalinity and hypoxia) due to its physiological functions, we will review the basic concepts of tissue immunity, discuss the technologies available to profile epigenetic modifications in tissue immune cells, including those that enable single-cell profiling, and consider how these mechanisms influence the development, phenotype, activation and function of different tissue immune cell subsets, as well as the immunological function of structural cells.
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Affiliation(s)
- Zewen Kelvin Tuong
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Benjamin J Stewart
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Shuang Andrew Guo
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Menna R Clatworthy
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK.,Cambridge Institute of Therapeutic Immunology and Infectious Diseases, University of Cambridge, Cambridge, UK
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163
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Zhang K, Hocker JD, Miller M, Hou X, Chiou J, Poirion OB, Qiu Y, Li YE, Gaulton KJ, Wang A, Preissl S, Ren B. A single-cell atlas of chromatin accessibility in the human genome. Cell 2021; 184:5985-6001.e19. [PMID: 34774128 PMCID: PMC8664161 DOI: 10.1016/j.cell.2021.10.024] [Citation(s) in RCA: 174] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 07/30/2021] [Accepted: 10/21/2021] [Indexed: 12/12/2022]
Abstract
Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with previous single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for ∼1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell-type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems.
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Affiliation(s)
- Kai Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - James D Hocker
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; 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
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, 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
| | - Olivier B Poirion
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Yunjiang Qiu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Yang E Li
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, 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.
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164
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Lyu P, Hoang T, Santiago CP, Thomas ED, Timms AE, Appel H, Gimmen M, Le N, Jiang L, Kim DW, Chen S, Espinoza DF, Telger AE, Weir K, Clark BS, Cherry TJ, Qian J, Blackshaw S. Gene regulatory networks controlling temporal patterning, neurogenesis, and cell-fate specification in mammalian retina. Cell Rep 2021; 37:109994. [PMID: 34788628 PMCID: PMC8642835 DOI: 10.1016/j.celrep.2021.109994] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 09/30/2021] [Accepted: 10/21/2021] [Indexed: 12/30/2022] Open
Abstract
Gene regulatory networks (GRNs), consisting of transcription factors and their target sites, control neurogenesis and cell-fate specification in the developing central nervous system. In this study, we use integrated single-cell RNA and single-cell ATAC sequencing (scATAC-seq) analysis in developing mouse and human retina to identify multiple interconnected, evolutionarily conserved GRNs composed of cell-type-specific transcription factors that both activate genes within their own network and inhibit genes in other networks. These GRNs control temporal patterning in primary progenitors, regulate transition from primary to neurogenic progenitors, and drive specification of each major retinal cell type. We confirm that NFI transcription factors selectively activate expression of genes promoting late-stage temporal identity in primary retinal progenitors and identify other transcription factors that regulate rod photoreceptor specification in postnatal retina. This study inventories cis- and trans-acting factors that control retinal development and can guide cell-based therapies aimed at replacing retinal neurons lost to disease.
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Affiliation(s)
- Pin Lyu
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Thanh Hoang
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Clayton P Santiago
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Eric D Thomas
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Andrew E Timms
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Haley Appel
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Megan Gimmen
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nguyet Le
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Lizhi Jiang
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Dong Won Kim
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Siqi Chen
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - David F Espinoza
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Ariel E Telger
- Department of Ophthalmology and Visual Sciences, Brotman Baty Institute, Seattle, WA 98195, USA
| | - Kurt Weir
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Brian S Clark
- Department of Ophthalmology and Visual Sciences, Brotman Baty Institute, Seattle, WA 98195, USA; Brotman Baty Institute, Seattle, WA 98195, USA; Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Timothy J Cherry
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA 98101, USA; Brotman Baty Institute, Seattle, WA 98195, USA; Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Jiang Qian
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
| | - Seth Blackshaw
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
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165
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Pike JW, Meyer MB. New Approaches to Assess Mechanisms of Action of Selective Vitamin D Analogues. Int J Mol Sci 2021; 22:ijms222212352. [PMID: 34830234 PMCID: PMC8619157 DOI: 10.3390/ijms222212352] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/05/2021] [Accepted: 11/11/2021] [Indexed: 12/28/2022] Open
Abstract
Recent studies of transcription have revealed an advanced set of overarching principles that govern vitamin D action on a genome-wide scale. These tenets of vitamin D transcription have emerged as a result of the application of now well-established techniques of chromatin immunoprecipitation coupled to next-generation DNA sequencing that have now been linked directly to CRISPR-Cas9 genomic editing in culture cells and in mouse tissues in vivo. Accordingly, these techniques have established that the vitamin D hormone modulates sets of cell-type specific genes via an initial action that involves rapid binding of the VDR-ligand complex to multiple enhancer elements at open chromatin sites that drive the expression of individual genes. Importantly, a sequential set of downstream events follows this initial binding that results in rapid histone acetylation at these sites, the recruitment of additional histone modifiers across the gene locus, and in many cases, the appearance of H3K36me3 and RNA polymerase II across gene bodies. The measured recruitment of these factors and/or activities and their presence at specific regions in the gene locus correlate with the emerging presence of cognate transcripts, thereby highlighting sequential molecular events that occur during activation of most genes both in vitro and in vivo. These features provide a novel approach to the study of vitamin D analogs and their actions in vivo and suggest that they can be used for synthetic compound evaluation and to select for novel tissue- and gene-specific features. This may be particularly useful for ligand activation of nuclear receptors given the targeting of these factors directly to genetic sites in the nucleus.
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Affiliation(s)
- John Wesley Pike
- Correspondence: ; Tel.: +1-(608)-262-8229; Fax: +1-(608)-263-7609
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166
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Gao T, Zheng Z, Pan Y, Zhu C, Wei F, Yuan J, Sun R, Fang S, Wang N, Zhou Y, Qian J. scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species. Nucleic Acids Res 2021; 50:D371-D379. [PMID: 34761274 PMCID: PMC8728125 DOI: 10.1093/nar/gkab1032] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 10/04/2021] [Accepted: 10/19/2021] [Indexed: 12/14/2022] Open
Abstract
Previous studies on enhancers and their target genes were largely based on bulk samples that represent ‘average’ regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (http://enhanceratlas.net/scenhancer/), covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.
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Affiliation(s)
- Tianshun Gao
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.,Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Zilong Zheng
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Yihang Pan
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.,Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Chengming Zhu
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Fuxin Wei
- Department of Orthopaedics, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Jinqiu Yuan
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.,Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Rui Sun
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.,Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Shuo Fang
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China.,Department of Oncology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Nan Wang
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Yang Zhou
- Big Data Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, P.R. China
| | - Jiang Qian
- The Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, MD 21231, USA.,The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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167
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Zhang H, Lu T, Liu S, Yang J, Sun G, Cheng T, Xu J, Chen F, Yen K. Comprehensive understanding of Tn5 insertion preference improves transcription regulatory element identification. NAR Genom Bioinform 2021; 3:lqab094. [PMID: 34729473 PMCID: PMC8557372 DOI: 10.1093/nargab/lqab094] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 09/20/2021] [Accepted: 09/29/2021] [Indexed: 12/11/2022] Open
Abstract
Tn5 transposase, which can efficiently tagment the genome, has been widely adopted as a molecular tool in next-generation sequencing, from short-read sequencing to more complex methods such as assay for transposase-accessible chromatin using sequencing (ATAC-seq). Here, we systematically map Tn5 insertion characteristics across several model organisms, finding critical parameters that affect its insertion. On naked genomic DNA, we found that Tn5 insertion is not uniformly distributed or random. To uncover drivers of these biases, we used a machine learning framework, which revealed that DNA shape cooperatively works with DNA motif to affect Tn5 insertion preference. These intrinsic insertion preferences can be modeled using nucleotide dependence information from DNA sequences, and we developed a computational pipeline to correct for these biases in ATAC-seq data. Using our pipeline, we show that bias correction improves the overall performance of ATAC-seq peak detection, recovering many potential false-negative peaks. Furthermore, we found that these peaks are bound by transcription factors, underscoring the biological relevance of capturing this additional information. These findings highlight the benefits of an improved understanding and precise correction of Tn5 insertion preference.
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Affiliation(s)
- Houyu Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Ting Lu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Shan Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Jianyu Yang
- Department of Developmental Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Guohuan Sun
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
| | - Jin Xu
- Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou 510006, China
| | - Fangyao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China
| | - Kuangyu Yen
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China
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168
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Li Z, Kuppe C, Ziegler S, Cheng M, Kabgani N, Menzel S, Zenke M, Kramann R, Costa IG. Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen. Nat Commun 2021; 12:6386. [PMID: 34737275 PMCID: PMC8568974 DOI: 10.1038/s41467-021-26530-2] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 10/04/2021] [Indexed: 12/18/2022] Open
Abstract
A major drawback of single-cell ATAC-seq (scATAC-seq) is its sparsity, i.e., open chromatin regions with no reads due to loss of DNA material during the scATAC-seq protocol. Here, we propose scOpen, a computational method based on regularized non-negative matrix factorization for imputing and quantifying the open chromatin status of regulatory regions from sparse scATAC-seq experiments. We show that scOpen improves crucial downstream analysis steps of scATAC-seq data as clustering, visualization, cis-regulatory DNA interactions, and delineation of regulatory features. We demonstrate the power of scOpen to dissect regulatory changes in the development of fibrosis in the kidney. This identifies a role of Runx1 and target genes by promoting fibroblast to myofibroblast differentiation driving kidney fibrosis.
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Affiliation(s)
- Zhijian Li
- Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - Christoph Kuppe
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany
- Division of Nephrology and Clinical Immunology, RWTH Aachen University, 52074, Aachen, Germany
| | - Susanne Ziegler
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - Mingbo Cheng
- Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - Nazanin Kabgani
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - Sylvia Menzel
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - Martin Zenke
- Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany
- Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
| | - Rafael Kramann
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University Medical School, 52074, Aachen, Germany.
- Division of Nephrology and Clinical Immunology, RWTH Aachen University, 52074, Aachen, Germany.
- Department of Internal Medicine, Nephrology and Transplantation, Erasmus Medical Center, 3015GD, Rotterdam, The Netherlands.
| | - Ivan G Costa
- Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074, Aachen, Germany.
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169
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Downes DJ, Cross AR, Hua P, Roberts N, Schwessinger R, Cutler AJ, Munis AM, Brown J, Mielczarek O, de Andrea CE, Melero I, Gill DR, Hyde SC, Knight JC, Todd JA, Sansom SN, Issa F, Davies JOJ, Hughes JR. Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus. Nat Genet 2021; 53:1606-1615. [PMID: 34737427 PMCID: PMC7611960 DOI: 10.1038/s41588-021-00955-3] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 09/22/2021] [Indexed: 12/21/2022]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies identified the 3p21.31 region as conferring a twofold increased risk of respiratory failure. Here, using a combined multiomics and machine learning approach, we identify the gain-of-function risk A allele of an SNP, rs17713054G>A, as a probable causative variant. We show with chromosome conformation capture and gene-expression analysis that the rs17713054-affected enhancer upregulates the interacting gene, leucine zipper transcription factor like 1 (LZTFL1). Selective spatial transcriptomic analysis of lung biopsies from patients with COVID-19 shows the presence of signals associated with epithelial-mesenchymal transition (EMT), a viral response pathway that is regulated by LZTFL1. We conclude that pulmonary epithelial cells undergoing EMT, rather than immune cells, are likely responsible for the 3p21.31-associated risk. Since the 3p21.31 effect is conferred by a gain-of-function, LZTFL1 may represent a therapeutic target.
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Affiliation(s)
- Damien J Downes
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Amy R Cross
- Nuffield Department of Surgical Sciences, Transplantation Research and Immunology Group,University of Oxford, Oxford, UK
| | - Peng Hua
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Nigel Roberts
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Ron Schwessinger
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Department of Medicine, Medical Research Council Weatherall Institute of Molecular Medicine Centre for Computational Biology, University of Oxford, Oxford, UK
| | - Antony J Cutler
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Immunology Research Unit, GlaxoSmithKline, Stevenage, UK
| | - Altar M Munis
- Department of Medicine, Gene Medicine Group, Nuffield Division of Clinical Laboratory Sciences, Radcliffe University of Oxford, Oxford, UK
| | - Jill Brown
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Olga Mielczarek
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Carlos E de Andrea
- Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Ignacio Melero
- Division of Immunology and Immunotherapy, Centre for Applied Medical Research, University of Navarra, Pamplona, Spain
| | - Deborah R Gill
- Department of Medicine, Gene Medicine Group, Nuffield Division of Clinical Laboratory Sciences, Radcliffe University of Oxford, Oxford, UK
| | - Stephen C Hyde
- Department of Medicine, Gene Medicine Group, Nuffield Division of Clinical Laboratory Sciences, Radcliffe University of Oxford, Oxford, UK
| | - Julian C Knight
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford, UK
| | - John A Todd
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stephen N Sansom
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Fadi Issa
- Nuffield Department of Surgical Sciences, Transplantation Research and Immunology Group,University of Oxford, Oxford, UK
- Oxford University Hospitals National Health Service Foundation Trust, Oxford, UK
| | - James O J Davies
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
- Oxford University Hospitals National Health Service Foundation Trust, Oxford, UK.
| | - Jim R Hughes
- Department of Medicine, Medical Research Council Molecular Haematology Unit, Medical Research Council Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
- Department of Medicine, Medical Research Council Weatherall Institute of Molecular Medicine Centre for Computational Biology, University of Oxford, Oxford, UK.
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170
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Pandey N, Omkar Chandra, Mishra S, Kumar V. Improving Chromatin-Interaction Prediction Using Single-Cell Open-Chromatin Profiles and Making Insight Into the Cis-Regulatory Landscape of the Human Brain. Front Genet 2021; 12:738194. [PMID: 34691152 PMCID: PMC8533004 DOI: 10.3389/fgene.2021.738194] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 08/31/2021] [Indexed: 11/13/2022] Open
Abstract
Single-cell open-chromatin profiles have the potential to reveal the pattern of chromatin-interaction in a cell type. However, currently available cis-regulatory network prediction methods using single-cell open-chromatin profiles focus more on local chromatin interactions despite the fact that long-range interactions among genomic sites play a significant role in gene regulation. Here, we propose a method that predicts both short and long-range interactions among genomic sites using single-cell open chromatin profiles. Our method, termed as single-cell epigenome based chromatin-interaction analysis (scEChIA) exploits signal imputation and refined L1 regularization. For a few single-cell open-chromatin profiles, scEChIA outperformed other tools even in terms of accuracy of prediction. Using scEChIA, we predicted almost 0.7 million interactions among genomic sites across seven cell types in the human brain. Further analysis revealed cell type for connection between genes and expression quantitative trait locus (eQTL) in the human brain and making insight about target genes of human-accelerated-elements and disease-associated mutations. Our analysis enabled by scEChIA also hints about the possible action of a few transcription factors (TFs), especially through long-range interaction in brain endothelial cells.
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Affiliation(s)
- Neetesh Pandey
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Omkar Chandra
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Shreya Mishra
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Vibhor Kumar
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
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171
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Kramme C, Plesa AM, Wang HH, Wolf B, Smela MP, Guo X, Kohman RE, Chatterjee P, Church GM. An integrated pipeline for mammalian genetic screening. CELL REPORTS METHODS 2021; 1:100082. [PMID: 35474898 PMCID: PMC9017118 DOI: 10.1016/j.crmeth.2021.100082] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/10/2021] [Accepted: 08/20/2021] [Indexed: 12/13/2022]
Abstract
With the recent advancements in genome editing, next-generation sequencing (NGS), and scalable cloning techniques, scientists can now conduct genetic screens at unprecedented levels of scale and precision. With such a multitude of technologies, there is a need for a simple yet comprehensive pipeline to enable systematic mammalian genetic screening. In this study, we develop unique algorithms for target identification and a toxin-less Gateway cloning tool, termed MegaGate, for library cloning which, when combined with existing genetic perturbation methods and NGS-coupled readouts, enable versatile engineering of relevant mammalian cell lines. Our integrated pipeline for sequencing-based target ascertainment and modular perturbation screening (STAMPScreen) can thus be utilized for a host of cell state engineering applications.
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Affiliation(s)
- Christian Kramme
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Alexandru M. Plesa
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Helen H. Wang
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Bennett Wolf
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Merrick Pierson Smela
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Xiaoge Guo
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Richie E. Kohman
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - Pranam Chatterjee
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
| | - George M. Church
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
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172
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Girskis KM, Stergachis AB, DeGennaro EM, Doan RN, Qian X, Johnson MB, Wang PP, Sejourne GM, Nagy MA, Pollina EA, Sousa AMM, Shin T, Kenny CJ, Scotellaro JL, Debo BM, Gonzalez DM, Rento LM, Yeh RC, Song JHT, Beaudin M, Fan J, Kharchenko PV, Sestan N, Greenberg ME, Walsh CA. Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions. Neuron 2021; 109:3239-3251.e7. [PMID: 34478631 DOI: 10.1016/j.neuron.2021.08.005] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/02/2021] [Accepted: 08/06/2021] [Indexed: 01/21/2023]
Abstract
Human accelerated regions (HARs) are the fastest-evolving regions of the human genome, and many are hypothesized to function as regulatory elements that drive human-specific gene regulatory programs. We interrogate the in vitro enhancer activity and in vivo epigenetic landscape of more than 3,100 HARs during human neurodevelopment, demonstrating that many HARs appear to act as neurodevelopmental enhancers and that sequence divergence at HARs has largely augmented their neuronal enhancer activity. Furthermore, we demonstrate PPP1R17 to be a putative HAR-regulated gene that has undergone remarkable rewiring of its cell type and developmental expression patterns between non-primates and primates and between non-human primates and humans. Finally, we show that PPP1R17 slows neural progenitor cell cycle progression, paralleling the cell cycle length increase seen predominantly in primate and especially human neurodevelopment. Our findings establish HARs as key components in rewiring human-specific neurodevelopmental gene regulatory programs and provide an integrated resource to study enhancer activity of specific HARs.
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Affiliation(s)
- Kelly M Girskis
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Program in Neuroscience, Harvard Medical School, Boston, MA, USA
| | - Andrew B Stergachis
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA; Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Ellen M DeGennaro
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ryan N Doan
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Xuyu Qian
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matthew B Johnson
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Peter P Wang
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gabrielle M Sejourne
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Aurel Nagy
- Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Program in Neuroscience, Harvard Medical School, Boston, MA, USA; Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Elizabeth A Pollina
- Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - André M M Sousa
- Department of Neuroscience and Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Taehwan Shin
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Program in Biological and Biomedical Sciences, Harvard Medical School, Boston MA, USA
| | - Connor J Kenny
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Julia L Scotellaro
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Brian M Debo
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Dilenny M Gonzalez
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lariza M Rento
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rebecca C Yeh
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Janet H T Song
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marc Beaudin
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jean Fan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Nenad Sestan
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Michael E Greenberg
- Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Program in Neuroscience, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Christopher A Walsh
- Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Allen Discovery Center for Human Brain Evolution, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Program in Neuroscience, Harvard Medical School, Boston, MA, USA.
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173
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Yousefi S, Deng R, Lanko K, Salsench EM, Nikoncuk A, van der Linde HC, Perenthaler E, van Ham TJ, Mulugeta E, Barakat TS. Comprehensive multi-omics integration identifies differentially active enhancers during human brain development with clinical relevance. Genome Med 2021; 13:162. [PMID: 34663447 PMCID: PMC8524963 DOI: 10.1186/s13073-021-00980-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/29/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Non-coding regulatory elements (NCREs), such as enhancers, play a crucial role in gene regulation, and genetic aberrations in NCREs can lead to human disease, including brain disorders. The human brain is a complex organ that is susceptible to numerous disorders; many of these are caused by genetic changes, but a multitude remain currently unexplained. Understanding NCREs acting during brain development has the potential to shed light on previously unrecognized genetic causes of human brain disease. Despite immense community-wide efforts to understand the role of the non-coding genome and NCREs, annotating functional NCREs remains challenging. METHODS Here we performed an integrative computational analysis of virtually all currently available epigenome data sets related to human fetal brain. RESULTS Our in-depth analysis unravels 39,709 differentially active enhancers (DAEs) that show dynamic epigenomic rearrangement during early stages of human brain development, indicating likely biological function. Many of these DAEs are linked to clinically relevant genes, and functional validation of selected DAEs in cell models and zebrafish confirms their role in gene regulation. Compared to enhancers without dynamic epigenomic rearrangement, DAEs are subjected to higher sequence constraints in humans, have distinct sequence characteristics and are bound by a distinct transcription factor landscape. DAEs are enriched for GWAS loci for brain-related traits and for genetic variation found in individuals with neurodevelopmental disorders, including autism. CONCLUSION This compendium of high-confidence enhancers will assist in deciphering the mechanism behind developmental genetics of human brain and will be relevant to uncover missing heritability in human genetic brain disorders.
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Affiliation(s)
- Soheil Yousefi
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Ruizhi Deng
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Kristina Lanko
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Eva Medico Salsench
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Anita Nikoncuk
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Herma C. van der Linde
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Elena Perenthaler
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Tjakko J. van Ham
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Eskeatnaf Mulugeta
- Department of Cell Biology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Tahsin Stefan Barakat
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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174
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Loker R, Sanner JE, Mann RS. Cell-type-specific Hox regulatory strategies orchestrate tissue identity. Curr Biol 2021; 31:4246-4255.e4. [PMID: 34358443 PMCID: PMC8511240 DOI: 10.1016/j.cub.2021.07.030] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/17/2021] [Accepted: 07/13/2021] [Indexed: 01/25/2023]
Abstract
Hox proteins are homeodomain transcription factors that diversify serially homologous segments along the animal body axis, as revealed by the classic bithorax phenotype of Drosophila melanogaster, in which mutations in Ultrabithorax (Ubx) transform the third thoracic segment into the likeness of the second thoracic segment. To specify segment identity, we show that Ubx both increases and decreases chromatin accessibility, coinciding with its dual role as both an activator and repressor of transcription. However, the choice of transcriptional activity executed by Ubx is spatially regulated and depends on the availability of cofactors, with Ubx acting as a repressor in some populations and as an activator in others. Ubx-mediated changes to chromatin accessibility positively and negatively affect the binding of Scalloped (Sd), a transcription factor that is required for appendage development in both segments. These findings illustrate how a single Hox protein can modify complex gene regulatory networks to transform the identity of an entire tissue.
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Affiliation(s)
- Ryan Loker
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY, USA; Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Jordyn E Sanner
- Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Richard S Mann
- Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA; Department of Neuroscience, Columbia University Irving Medical Center, New York, NY, USA; Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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175
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Kremer H. Novel gene discovery for hearing loss and other routes to increased diagnostic rates. Hum Genet 2021; 141:383-386. [PMID: 34599370 PMCID: PMC9034996 DOI: 10.1007/s00439-021-02374-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/15/2021] [Indexed: 11/29/2022]
Abstract
Despite decades of research, there is much to be learned about the genetic landscape of sensorineural hearing loss. Novel genes for hearing loss remain to be identified while ‘secrets’ of the known genes need to be uncovered. These ‘secrets’ include regulatory mechanisms of gene activity and novel aspects of gene structure. To obtain a more complete picture of the genetics of hearing loss, the available experimental and bioinformatic tools need to be fully exploited. This is also true for data resources such as ENCODE. For the inner ear, however, such data resources and analytical tools need to be developed or extended. Collaborative studies provide opportunities to achieve this and to optimally use those tools and resources that are already available. This will accelerate the discoveries that are necessary for improving molecular genetic diagnostics and genetic counselling and for the development of therapeutic strategies.
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Affiliation(s)
- Hannie Kremer
- Hearing and Genes, Department of Otorhinolaryngology, Radboud University Medical Center, Nijmegen, The Netherlands. .,Department of Human Genetics, Radboud University Medical Center, Internal Postal Code 855, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. .,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.
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176
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Chaligne R, Gaiti F, Silverbush D, Schiffman JS, Weisman HR, Kluegel L, Gritsch S, Deochand SD, Gonzalez Castro LN, Richman AR, Klughammer J, Biancalani T, Muus C, Sheridan C, Alonso A, Izzo F, Park J, Rozenblatt-Rosen O, Regev A, Suvà ML, Landau DA. Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states. Nat Genet 2021; 53:1469-1479. [PMID: 34594037 PMCID: PMC8675181 DOI: 10.1038/s41588-021-00927-7] [Citation(s) in RCA: 96] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 07/30/2021] [Indexed: 02/08/2023]
Abstract
Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.
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Affiliation(s)
- Ronan Chaligne
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Federico Gaiti
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Dana Silverbush
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Joshua S Schiffman
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Hannah R Weisman
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Lloyd Kluegel
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Simon Gritsch
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sunil D Deochand
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - L Nicolas Gonzalez Castro
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alyssa R Richman
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | | | - Christoph Muus
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | | | | | - Franco Izzo
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jane Park
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Orit Rozenblatt-Rosen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Aviv Regev
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Koch Institute for Integrative Cancer Research, Department of Biology, MIT, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Mario L Suvà
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
| | - Dan A Landau
- New York Genome Center, New York, NY, USA.
- Weill Cornell Medicine, New York, NY, USA.
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177
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Samad T, Wu SM. Single cell RNA sequencing approaches to cardiac development and congenital heart disease. Semin Cell Dev Biol 2021; 118:129-135. [PMID: 34006454 PMCID: PMC8434959 DOI: 10.1016/j.semcdb.2021.04.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/26/2021] [Accepted: 04/26/2021] [Indexed: 12/27/2022]
Abstract
The development of single cell RNA sequencing technologies has accelerated the ability of scientists to understand healthy and disease states of the cardiovascular system. Congenital heart defects occur in approximately 40,000 births each year and 1 out of 4 children are born with critical congenital heart disease requiring surgical interventions and a lifetime of monitoring. An understanding of how the normal heart develops and how each cell contributes to normal and pathological anatomy is an important goal in pediatric cardiovascular research. Single cell sequencing has provided the tools to increase the ability to discover rare cell types and novel genes involved in normal cardiac development. Knowledge of gene expression of single cells within cardiac tissue has contributed to the understanding of how each cell type contributes to the anatomic structures of the heart. In this review, we summarize how single cell RNA sequencing has been utilized to understand cardiac developmental processes and congenital heart disease. We discuss the advantages and disadvantages of whole cell versus single nuclei RNA sequencing and describe the approaches to analyze the interactomes, transcriptomes, and differentiation trajectory from single cell data. We summarize the currently available single cell RNA sequencing technologies and technical aspects of performing single cell analysis and how to overcome common obstacles. We also review data from the recently published human and mouse fetal heart atlases and advancements that have occurred within the field due to the application of these single cell tools. Finally we highlight the potential for single cell technologies to uncover novel mechanisms of disease pathogenesis by leveraging findings from genome wide association studies.
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Affiliation(s)
- Tahmina Samad
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA, USA; Clinical and Translational Research Program, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Sean M Wu
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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178
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Abstract
It has been just over 10 years since the initial description of transposase-based methods to prepare high-throughput sequencing libraries, or "tagmentation," in which a hyperactive transposase is used to simultaneously fragment target DNA and append universal adapter sequences. Tagmentation effectively replaced a series of processing steps in traditional workflows with one single reaction. It is the simplicity, coupled with the high efficiency of tagmentation, that has made it a favored means of sequencing library construction and fueled a diverse range of adaptations to assay a variety of molecular properties. In recent years, this has been centered in the single-cell space with a catalog of tagmentation-based assays that have been developed, covering a substantial swath of the regulatory landscape. To date, there have been a number of excellent reviews on single-cell technologies structured around the molecular properties that can be profiled. This review is instead framed around the central components and properties of tagmentation and how they have enabled the development of innovative molecular tools to probe the regulatory landscape of single cells. Furthermore, the granular specifics on cell throughput or richness of data provided by the extensive list of individual technologies are not discussed. Such metrics are rapidly changing and highly sample specific and are better left to studies that directly compare technologies for assays against one another in a rigorously controlled framework. The hope for this review is that, in laying out the diversity of molecular techniques at each stage of these assay platforms, new ideas may arise for others to pursue that will further advance the field of single-cell genomics.
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Affiliation(s)
- Andrew C Adey
- Department of Molecular & Medical Genetics, Knight Cancer Institute, Knight Cardiovascular Institute, Cancer Early Detection Advanced Research Center, Oregon Health and Science University, Portland, Oregon 97239, USA
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179
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Rautenstrauch P, Vlot AHC, Saran S, Ohler U. Intricacies of single-cell multi-omics data integration. Trends Genet 2021; 38:128-139. [PMID: 34561102 DOI: 10.1016/j.tig.2021.08.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 08/20/2021] [Accepted: 08/23/2021] [Indexed: 02/06/2023]
Abstract
A wealth of single-cell protocols makes it possible to characterize different molecular layers at unprecedented resolution. Integrating the resulting multimodal single-cell data to find cell-to-cell correspondences remains a challenge. We argue that data integration needs to happen at a meaningful biological level of abstraction and that it is necessary to consider the inherent discrepancies between modalities to strike a balance between biological discovery and noise removal. A survey of current methods reveals that a distinction between technical and biological origins of presumed unwanted variation between datasets is not yet commonly considered. The increasing availability of paired multimodal data will aid the development of improved methods by providing a ground truth on cell-to-cell matches.
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Affiliation(s)
- Pia Rautenstrauch
- The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 10115 Berlin, Germany; Department of Computer Science, Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Anna Hendrika Cornelia Vlot
- The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 10115 Berlin, Germany; Department of Computer Science, Humboldt Universität zu Berlin, 10117 Berlin, Germany
| | - Sepideh Saran
- The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 10115 Berlin, Germany
| | - Uwe Ohler
- The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 10115 Berlin, Germany; Department of Computer Science, Humboldt Universität zu Berlin, 10117 Berlin, Germany; Department of Biology, Humboldt Universität zu Berlin, 10117 Berlin, Germany.
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180
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A roadmap for the Human Developmental Cell Atlas. Nature 2021; 597:196-205. [PMID: 34497388 DOI: 10.1038/s41586-021-03620-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 05/07/2021] [Indexed: 12/12/2022]
Abstract
The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.
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181
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Chen J, Ali MW, Yan L, Dighe SG, Dai JY, Vaughan TL, Casey G, Buas MF. Prioritization and functional analysis of GWAS risk loci for Barrett's esophagus and esophageal adenocarcinoma. Hum Mol Genet 2021; 31:410-422. [PMID: 34505128 DOI: 10.1093/hmg/ddab259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/17/2021] [Accepted: 08/30/2021] [Indexed: 01/03/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified ~ 20 genetic susceptibility loci for esophageal adenocarcinoma (EAC), and its precursor, Barrett's esophagus (BE). Despite such advances, functional/causal variants and gene targets at these loci remain undefined, hindering clinical translation. A key challenge is that most causal variants map to non-coding regulatory regions such as enhancers, and typically, numerous potential candidate variants at GWAS loci require testing. We developed a systematic informatics pipeline for prioritizing candidate functional variants via integrative functional potential scores consolidated from multi-omics annotations, and used this pipeline to identify two high-scoring variants for experimental interrogation: chr9q22.32/rs11789015 and chr19p13.11/rs10423674. Minimal candidate enhancer regions spanning these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two variants tested (rs10423674) exhibited allele-specific enhancer activity. CRISPR-mediated deletion of the putative enhancer region in EAC cell lines correlated with reduced expression of two genes-CREB-regulated transcription coactivator 1 (CRTC1) and Cartilage oligomeric matrix protein (COMP); expression of five other genes remained unchanged (CRLF1, KLHL26, TMEM59L, UBA52, RFXANK). Expression quantitative trait locus (eQTL) mapping indicated that rs10423674 genotype correlated with CRTC1 and COMP expression in normal esophagus. This study represents the first experimental effort to bridge GWAS associations to biology in BE/EAC, and supports the utility of functional potential scores to guide variant prioritization. Our findings reveal a functional variant and candidate risk enhancer at chr19p13.11, and implicate CRTC1 and COMP as putative gene targets, suggesting that altered expression of these genes may underlie the BE/EAC risk association.
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Affiliation(s)
- Jianhong Chen
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263 USA
| | - Mourad Wagdy Ali
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22903 USA
| | - Li Yan
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263 USA
| | - Shruti G Dighe
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263 USA
| | - James Y Dai
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109 USA
| | - Thomas L Vaughan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109 USA.,Department of Epidemiology, University of Washington, School of Public Health, Seattle, Washington, 98195 USA
| | - Graham Casey
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22903 USA
| | - Matthew F Buas
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263 USA
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182
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Danese A, Richter ML, Chaichoompu K, Fischer DS, Theis FJ, Colomé-Tatché M. EpiScanpy: integrated single-cell epigenomic analysis. Nat Commun 2021; 12:5228. [PMID: 34471111 PMCID: PMC8410937 DOI: 10.1038/s41467-021-25131-3] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 07/22/2021] [Indexed: 11/14/2022] Open
Abstract
EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets. The toolkit also features numerous useful downstream functions, such as differential methylation and differential openness calling, mapping epigenomic features of interest to their nearest gene, or constructing gene activity matrices using chromatin openness. We successfully benchmark epiScanpy against other scATAC-seq analysis tools and show its outperformance at discriminating cell types.
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Affiliation(s)
- Anna Danese
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Maria L Richter
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kridsadakorn Chaichoompu
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - David S Fischer
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
- Department of Mathematics, Technical University of Munich, Garching, Germany.
| | - Maria Colomé-Tatché
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.
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183
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Sarropoulos I, Sepp M, Frömel R, Leiss K, Trost N, Leushkin E, Okonechnikov K, Joshi P, Giere P, Kutscher LM, Cardoso-Moreira M, Pfister SM, Kaessmann H. Developmental and evolutionary dynamics of cis-regulatory elements in mouse cerebellar cells. Science 2021; 373:eabg4696. [PMID: 34446581 PMCID: PMC7611596 DOI: 10.1126/science.abg4696] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 07/14/2021] [Indexed: 12/13/2022]
Abstract
Organ development is orchestrated by cell- and time-specific gene regulatory networks. In this study, we investigated the regulatory basis of mouse cerebellum development from early neurogenesis to adulthood. By acquiring snATAC-seq (single-nucleus assay for transposase accessible chromatin using sequencing) profiles for ~90,000 cells spanning 11 stages, we mapped cerebellar cell types and identified candidate cis-regulatory elements (CREs). We detected extensive spatiotemporal heterogeneity among progenitor cells and a gradual divergence in the regulatory programs of cerebellar neurons during differentiation. Comparisons to vertebrate genomes and snATAC-seq profiles for ∼20,000 cerebellar cells from the marsupial opossum revealed a shared decrease in CRE conservation during development and differentiation as well as differences in constraint between cell types. Our work delineates the developmental and evolutionary dynamics of gene regulation in cerebellar cells and provides insights into mammalian organ development.
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Affiliation(s)
- Ioannis Sarropoulos
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
| | - Mari Sepp
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
| | - Robert Frömel
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Kevin Leiss
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Nils Trost
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Evgeny Leushkin
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
| | - Konstantin Okonechnikov
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Piyush Joshi
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Peter Giere
- Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Lena M Kutscher
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Developmental Origins of Pediatric Cancer Group, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany
| | - Margarida Cardoso-Moreira
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany
- Evolutionary Developmental Biology Laboratory, Francis Crick Institute, London NW1 1AT, UK
| | - Stefan M Pfister
- Hopp Children's Cancer Center (KiTZ) Heidelberg, Division of Pediatric Neurooncology, German Cancer Consortium (DKTK), and German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany.
- Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Henrik Kaessmann
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, D-69120 Heidelberg, Germany.
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184
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Claringbould A, Zaugg JB. Enhancers in disease: molecular basis and emerging treatment strategies. Trends Mol Med 2021; 27:1060-1073. [PMID: 34420874 DOI: 10.1016/j.molmed.2021.07.012] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 07/22/2021] [Accepted: 07/26/2021] [Indexed: 02/07/2023]
Abstract
Enhancers are genomic sequences that play a key role in regulating tissue-specific gene expression levels. An increasing number of diseases are linked to impaired enhancer function through chromosomal rearrangement, genetic variation within enhancers, or epigenetic modulation. Here, we review how these enhancer disruptions have recently been implicated in congenital disorders, cancers, and common complex diseases and address the implications for diagnosis and treatment. Although further fundamental research into enhancer function, target genes, and context is required, enhancer-targeting drugs and gene editing approaches show great therapeutic promise for a range of diseases.
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Affiliation(s)
- Annique Claringbould
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Judith B Zaugg
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstraße 1, 69117 Heidelberg, Germany.
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185
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Mechanisms of Binding Specificity among bHLH Transcription Factors. Int J Mol Sci 2021; 22:ijms22179150. [PMID: 34502060 PMCID: PMC8431614 DOI: 10.3390/ijms22179150] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/14/2021] [Accepted: 08/18/2021] [Indexed: 12/25/2022] Open
Abstract
The transcriptome of every cell is orchestrated by the complex network of interaction between transcription factors (TFs) and their binding sites on DNA. Disruption of this network can result in many forms of organism malfunction but also can be the substrate of positive natural selection. However, understanding the specific determinants of each of these individual TF-DNA interactions is a challenging task as it requires integrating the multiple possible mechanisms by which a given TF ends up interacting with a specific genomic region. These mechanisms include DNA motif preferences, which can be determined by nucleotide sequence but also by DNA’s shape; post-translational modifications of the TF, such as phosphorylation; and dimerization partners and co-factors, which can mediate multiple forms of direct or indirect cooperative binding. Binding can also be affected by epigenetic modifications of putative target regions, including DNA methylation and nucleosome occupancy. In this review, we describe how all these mechanisms have a role and crosstalk in one specific family of TFs, the basic helix-loop-helix (bHLH), with a very conserved DNA binding domain and a similar DNA preferred motif, the E-box. Here, we compile and discuss a rich catalog of strategies used by bHLH to acquire TF-specific genome-wide landscapes of binding sites.
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186
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Wilson SL, Wallingford M. Epigenetic regulation of reproduction in human and in animal models. Mol Hum Reprod 2021; 27:6329199. [PMID: 34318322 DOI: 10.1093/molehr/gaab041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/07/2021] [Indexed: 12/24/2022] Open
Affiliation(s)
- Samantha L Wilson
- Princess Margaret Cancer Centre, University Health Network, Toronto Medical Discovery Tower, Toronto, ON, Canada
| | - Mary Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA.,Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
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187
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Abstract
Cell atlases are essential companions to the genome as they elucidate how genes are used in a cell type-specific manner or how the usage of genes changes over the lifetime of an organism. This review explores recent advances in whole-organism single-cell atlases, which enable understanding of cell heterogeneity and tissue and cell fate, both in health and disease. Here we provide an overview of recent efforts to build cell atlases across species and discuss the challenges that the field is currently facing. Moreover, we propose the concept of having a knowledgebase that can scale with the number of experiments and computational approaches and a new feedback loop for development and benchmarking of computational methods that includes contributions from the users. These two aspects are key for community efforts in single-cell biology that will help produce a comprehensive annotated map of cell types and states with unparalleled resolution.
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Affiliation(s)
| | - Bruno Tojo
- Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
| | - Aaron McGeever
- Chan Zuckerberg Biohub, San Francisco, California 94103, USA;
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188
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Mantri S, Wu SM, Goodyer WR. Molecular Profiling of the Cardiac Conduction System: the Dawn of a New Era. Curr Cardiol Rep 2021; 23:103. [PMID: 34196831 DOI: 10.1007/s11886-021-01536-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/17/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE OF REVIEW Recent technological advances have led to an increased ability to define the gene expression profile of the cardiac conduction system (CCS). Here, we review the most salient studies to emerge in recent years and discuss existing gaps in our knowledge as well as future areas of investigation. RECENT FINDINGS Molecular profiling of the CCS spans several decades. However, the advent of high-throughput sequencing strategies has allowed for the discovery of unique transcriptional programs of the many diverse CCS cell types. The CCS, a diverse structure with significant inter- and intra-component cellular heterogeneity, is essential to the normal function of the heart. Progress in transcriptomic profiling has improved the resolution and depth of characterization of these unique and clinically relevant CCS cell types. Future studies leveraging this big data will play a crucial role in improving our understanding of CCS development and function as well as translating these findings into tangible translational tools for the improved detection, prevention, and treatment of cardiac arrhythmias.
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Affiliation(s)
- Sruthi Mantri
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Sean M Wu
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA.,Division of Pediatric Cardiology, Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA.,Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - William R Goodyer
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA. .,Division of Pediatric Cardiology, Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA. .,Division of Pediatric Cardiology, Electrophysiology, Department of Pediatrics, Lucile Packard Children's Hospital, Stanford University School of Medicine, Room G1105 Lokey Stem Cell Research Building, 265 Campus Drive, Stanford, CA, 94305, USA.
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189
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Gao S, Dai Y, Rehman J. A Bayesian inference transcription factor activity model for the analysis of single-cell transcriptomes. Genome Res 2021; 31:1296-1311. [PMID: 34193535 PMCID: PMC8256867 DOI: 10.1101/gr.265595.120] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 05/26/2021] [Indexed: 01/06/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful experimental approach to study cellular heterogeneity. One of the challenges in scRNA-seq data analysis is integrating different types of biological data to consistently recognize discrete biological functions and regulatory mechanisms of cells, such as transcription factor activities and gene regulatory networks in distinct cell populations. We have developed an approach to infer transcription factor activities from scRNA-seq data that leverages existing biological data on transcription factor binding sites. The Bayesian inference transcription factor activity model (BITFAM) integrates ChIP-seq transcription factor binding information into scRNA-seq data analysis. We show that the inferred transcription factor activities for key cell types identify regulatory transcription factors that are known to mechanistically control cell function and cell fate. The BITFAM approach not only identifies biologically meaningful transcription factor activities, but also provides valuable insights into underlying transcription factor regulatory mechanisms.
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Affiliation(s)
- Shang Gao
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60612, USA
- Department of Medicine, Division of Cardiology, University of Illinois at Chicago, Chicago, Illinois 60612, USA
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, Illinois 60612, USA
| | - Yang Dai
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60612, USA
| | - Jalees Rehman
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60612, USA
- Department of Medicine, Division of Cardiology, University of Illinois at Chicago, Chicago, Illinois 60612, USA
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, Illinois 60612, USA
- University of Illinois Cancer Center, Chicago, Illinois 60612, USA
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190
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Alexanian M, Przytycki PF, Micheletti R, Padmanabhan A, Ye L, Travers JG, Gonzalez-Teran B, Silva AC, Duan Q, Ranade SS, Felix F, Linares-Saldana R, Li L, Lee CY, Sadagopan N, Pelonero A, Huang Y, Andreoletti G, Jain R, McKinsey TA, Rosenfeld MG, Gifford CA, Pollard KS, Haldar SM, Srivastava D. A transcriptional switch governs fibroblast activation in heart disease. Nature 2021; 595:438-443. [PMID: 34163071 PMCID: PMC8341289 DOI: 10.1038/s41586-021-03674-1] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 05/26/2021] [Indexed: 12/22/2022]
Abstract
In diseased organs, stress-activated signalling cascades alter chromatin, thereby triggering maladaptive cell state transitions. Fibroblast activation is a common stress response in tissues that worsens lung, liver, kidney and heart disease, yet its mechanistic basis remains unclear1,2. Pharmacological inhibition of bromodomain and extra-terminal domain (BET) proteins alleviates cardiac dysfunction3-7, providing a tool to interrogate and modulate cardiac cell states as a potential therapeutic approach. Here we use single-cell epigenomic analyses of hearts dynamically exposed to BET inhibitors to reveal a reversible transcriptional switch that underlies the activation of fibroblasts. Resident cardiac fibroblasts demonstrated robust toggling between the quiescent and activated state in a manner directly correlating with BET inhibitor exposure and cardiac function. Single-cell chromatin accessibility revealed previously undescribed DNA elements, the accessibility of which dynamically correlated with cardiac performance. Among the most dynamic elements was an enhancer that regulated the transcription factor MEOX1, which was specifically expressed in activated fibroblasts, occupied putative regulatory elements of a broad fibrotic gene program and was required for TGFβ-induced fibroblast activation. Selective CRISPR inhibition of the single most dynamic cis-element within the enhancer blocked TGFβ-induced Meox1 activation. We identify MEOX1 as a central regulator of fibroblast activation associated with cardiac dysfunction and demonstrate its upregulation after activation of human lung, liver and kidney fibroblasts. The plasticity and specificity of BET-dependent regulation of MEOX1 in tissue fibroblasts provide previously unknown trans- and cis-targets for treating fibrotic disease.
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Affiliation(s)
| | | | - Rudi Micheletti
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Arun Padmanabhan
- Gladstone Institutes, San Francisco, CA, USA
- Department of Medicine, Cardiology Division, UCSF School of Medicine, San Francisco, CA, USA
| | - Lin Ye
- Gladstone Institutes, San Francisco, CA, USA
| | - Joshua G Travers
- Department of Medicine, Division of Cardiology and Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | | | - Qiming Duan
- Gladstone Institutes, San Francisco, CA, USA
| | | | | | - Ricardo Linares-Saldana
- Cardiovascular Institute and Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li Li
- Cardiovascular Institute and Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Nandhini Sadagopan
- Gladstone Institutes, San Francisco, CA, USA
- Department of Medicine, Cardiology Division, UCSF School of Medicine, San Francisco, CA, USA
| | | | - Yu Huang
- Gladstone Institutes, San Francisco, CA, USA
| | - Gaia Andreoletti
- Institute for Computational Health Sciences, University of California, San Francisco, CA, USA
| | - Rajan Jain
- Cardiovascular Institute and Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy A McKinsey
- Department of Medicine, Division of Cardiology and Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Michael G Rosenfeld
- Howard Hughes Medical Institute, Department and School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | | | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA
- Institute for Computational Health Sciences, University of California, San Francisco, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Saptarsi M Haldar
- Gladstone Institutes, San Francisco, CA, USA.
- Department of Medicine, Cardiology Division, UCSF School of Medicine, San Francisco, CA, USA.
- Amgen Research, Cardiometabolic Disorders, South San Francisco, CA, USA.
| | - Deepak Srivastava
- Gladstone Institutes, San Francisco, CA, USA.
- Department of Pediatrics, UCSF School of Medicine, San Francisco, CA, USA.
- Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA.
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA.
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191
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Qiu X, Yu H, Wu H, Hu Z, Zhou J, Lin H, Xue W, Cai W, Chen J, Yan Q, Dai W, Yang M, Tang D, Dai Y. Single-cell chromatin accessibility landscape of human umbilical cord blood in trisomy 18 syndrome. Hum Genomics 2021; 15:40. [PMID: 34193281 PMCID: PMC8246660 DOI: 10.1186/s40246-021-00338-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/29/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Trisomy 18 syndrome (Edwards syndrome, ES) is a type of aneuploidy caused by the presence of an extra chromosome 18. Aneuploidy is the leading cause of early pregnancy loss, intellectual disability, and multiple congenital anomalies. The research of trisomy 18 is progressing slowly, and the molecular characteristics of the disease mechanism and phenotype are still largely unclear. RESULTS In this study, we used the commercial Chromium platform (10× Genomics) to perform sc-ATAC-seq to measure chromatin accessibility in 11,611 single umbilical cord blood cells derived from one trisomy 18 syndrome patient and one healthy donor. We obtained 13 distinct major clusters of cells and identified them as 6 human umbilical cord blood mononuclear cell types using analysis tool. Compared with the NC group, the ES group had a lower ratio of T cells to NK cells, the ratio of monocytes/DC cell population did not change significantly, and the ratio of B cell nuclear progenitor and megakaryocyte erythroid cells was higher. The differential genes of ME-0 are enriched in Human T cell leukemia virus 1 infection pathway, and the differential peak genes of ME-1 are enriched in apopotosis pathway. We found that CCNB2 and MCM3 may be vital to the development of trisomy 18. CCNB2 and MCM3, which have been reported to be essential components of the cell cycle and chromatin. CONCLUSIONS We have identified 6 cell populations in cord blood. Disorder in megakaryocyte erythroid cells implicates trisomy 18 in perturbing fetal hematopoiesis. We identified a pathway in which the master differential regulatory pathway in the ME-0 cell population involves human T cell leukemia virus 1 infection, a pathway that is dysregulated in patients with trisomy 18 and which may increase the risk of leukemia in patients with trisomy 18. CCNB2 and MCM3 in progenitor may be vital to the development of trisomy 18. CCNB2 and MCM3, which have been reported to be essential components of the cell cycle and chromatin, may be related to chromosomal abnormalities in trisomy 18.
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Affiliation(s)
- Xiaofen Qiu
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China.,Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China.,College of Life Science, Guangxi Normal University, Guilin, Guangxi, 541004, People's Republic of China
| | - Haiyan Yu
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China
| | - Hongwei Wu
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China
| | - Zhiyang Hu
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China
| | - Jun Zhou
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China
| | - Hua Lin
- Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China
| | - Wen Xue
- Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China
| | - Wanxia Cai
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China
| | - Jiejing Chen
- Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China
| | - Qiang Yan
- Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China
| | - Weier Dai
- College of Natural Science, University of Texas at Austin, Austin, TX, 78712, USA
| | - Ming Yang
- Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China
| | - Donge Tang
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China.
| | - Yong Dai
- Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong, 518020, People's Republic of China. .,Guangxi Key Laboratory of Metabolic Diseases Research, Department of Clinical Laboratory of Guilin, No. 924 Hospital, 541002, Guilin, Guangxi, People's Republic of China.
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192
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Richard D, Capellini TD. Shifting epigenetic contexts influence regulatory variation and disease risk. Aging (Albany NY) 2021; 13:15699-15749. [PMID: 34138751 PMCID: PMC8266365 DOI: 10.18632/aging.203194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/01/2021] [Indexed: 11/25/2022]
Abstract
Epigenetic shifts are a hallmark of aging that impact transcriptional networks at regulatory level. These shifts may modify the effects of genetic regulatory variants during aging and contribute to disease pathomechanism. However, these shifts occur on the backdrop of epigenetic changes experienced throughout an individual's development into adulthood; thus, the phenotypic, and ultimately fitness, effects of regulatory variants subject to developmental- versus aging-related epigenetic shifts may differ considerably. Natural selection therefore may act differently on variants depending on their changing epigenetic context, which we propose as a novel lens through which to consider regulatory sequence evolution and phenotypic effects. Here, we define genomic regions subjected to altered chromatin accessibility as tissues transition from their fetal to adult forms, and subsequently from early to late adulthood. Based on these epigenomic datasets, we examine patterns of evolutionary constraint and potential functional impacts of sequence variation (e.g., genetic disease risk associations). We find that while the signals observed with developmental epigenetic changes are consistent with stronger fitness consequences (i.e., negative selection pressures), they tend to have weaker effects on genetic risk associations for aging-related diseases. Conversely, we see stronger effects of variants with increased local accessibility in adult tissues, strongest in young adult when compared to old. We propose a model for how epigenetic status of a region may influence the effects of evolutionary relevant sequence variation, and suggest that such a perspective on gene regulatory networks may elucidate our understanding of aging biology.
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Affiliation(s)
- Daniel Richard
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Terence D Capellini
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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193
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Guo X, Ohler U, Yildirim F. How to find genomic regions relevant for gene regulation. MED GENET-BERLIN 2021; 33:157-165. [PMID: 38836026 PMCID: PMC11007629 DOI: 10.1515/medgen-2021-2074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 07/09/2021] [Indexed: 06/06/2024]
Abstract
Genetic variants associated with human diseases are often located outside the protein coding regions of the genome. Identification and functional characterization of the regulatory elements in the non-coding genome is therefore of crucial importance for understanding the consequences of genetic variation and the mechanisms of disease. The past decade has seen rapid progress in high-throughput analysis and mapping of chromatin accessibility, looping, structure, and occupancy by transcription factors, as well as epigenetic modifications, all of which contribute to the proper execution of regulatory functions in the non-coding genome. Here, we review the current technologies for the definition and functional validation of non-coding regulatory regions in the genome.
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Affiliation(s)
- Xuanzong Guo
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Uwe Ohler
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology, 10115 Berlin, Germany
- Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Ferah Yildirim
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
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194
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Green DJ, Lenassi E, Manning CS, McGaughey D, Sharma V, Black GC, Ellingford JM, Sergouniotis PI. North Carolina Macular Dystrophy: Phenotypic Variability and Computational Analysis of Disease-Associated Noncoding Variants. Invest Ophthalmol Vis Sci 2021; 62:16. [PMID: 34125159 PMCID: PMC8212441 DOI: 10.1167/iovs.62.7.16] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Purpose North Carolina macular dystrophy (NCMD) is an autosomal dominant, congenital disorder affecting the central retina. Here, we report clinical and genetic findings in three families segregating NCMD and use epigenomic datasets from human tissues to gain insights into the effect of NCMD-implicated variants. Methods Clinical assessment and genetic testing were performed. Publicly available transcriptomic and epigenomic datasets were analyzed and the activity-by-contact method for scoring enhancer elements and linking them to target genes was used. Results A previously described, heterozygous, noncoding variant upstream of the PRDM13 gene was detected in all six affected study participants (chr6:100,040,987G>C [GRCh37/hg19]). Interfamilial and intrafamilial variability were observed; the visual acuity ranged from 0.0 to 1.6 LogMAR and fundoscopic findings ranged from visually insignificant, confluent, drusen-like macular deposits to coloboma-like macular lesions. Variable degrees of peripheral retinal spots (which were easily detected on widefield retinal imaging) were observed in all study subjects. Notably, a 6-year-old patient developed choroidal neovascularization and required treatment with intravitreal bevacizumab injections. Computational analysis of the five single nucleotide variants that have been implicated in NCMD revealed that these noncoding changes lie within two putative enhancer elements; these elements are predicted to interact with PRDM13 in the developing human retina. PRDM13 was found to be expressed in the fetal retina, with greatest expression in the amacrine precursor cell population. Conclusions We provide further evidence supporting the role of PRDM13 dysregulation in the pathogenesis of NCMD and highlight the usefulness of widefield retinal imaging in individuals suspected to have this condition.
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Affiliation(s)
- David J Green
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Eva Lenassi
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
- Manchester Royal Eye Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Cerys S Manning
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - David McGaughey
- Ophthalmic Genetics and Visual Function Branch, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States
| | - Vinod Sharma
- Manchester Royal Eye Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Graeme C Black
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Jamie M Ellingford
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Panagiotis I Sergouniotis
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
- Manchester Royal Eye Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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195
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Adey AC. Single-cell multiomics to probe relationships between histone modifications and transcription. Nat Methods 2021; 18:602-603. [PMID: 33958789 DOI: 10.1038/s41592-021-01147-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Affiliation(s)
- Andrew C Adey
- Department of Molecular & Medical Genetics, Knight Cardiovascular Institute, Knight Cancer Institute, and Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA.
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196
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Yuan Y, Deng Q, Wei X, Liu Y, Lan Q, Jiang Y, Yu Y, Guo P, Xu J, Yu C, Han L, Cheng M, Wu P, Zhang X, Lai Y, Volpe G, Esteban MA, Yang H, Liu C, Liu L. The Chromatin Accessibility Landscape of Adult Rat. Front Genet 2021; 12:651604. [PMID: 34108989 PMCID: PMC8181391 DOI: 10.3389/fgene.2021.651604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 04/01/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Yue Yuan
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | - Qiuting Deng
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | - Xiaoyu Wei
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | - Yang Liu
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | | | - Yu Jiang
- First Hospital, Jilin University, Changchun, China
| | - Yeya Yu
- BGI-Shenzhen, Shenzhen, China.,BGI College, Zhengzhou University, Zhengzhou, China
| | - Pengcheng Guo
- College of Veterinary Medicine, Jilin University, Changchun, China
| | - Jiangshan Xu
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | - Cong Yu
- BGI-Shenzhen, Shenzhen, China
| | - Lei Han
- BGI-Shenzhen, Shenzhen, China
| | - Mengnan Cheng
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China.,BGI-Shenzhen, Shenzhen, China
| | | | - Xiao Zhang
- College of Veterinary Medicine, Jilin University, Changchun, China
| | - Yiwei Lai
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Giacomo Volpe
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Miguel A Esteban
- BGI-Shenzhen, Shenzhen, China.,First Hospital, Jilin University, Changchun, China.,College of Veterinary Medicine, Jilin University, Changchun, China.,Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, China.,James D. Watson Institute of Genome Sciences, Hangzhou, China.,Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, BGI-Shenzhen, Shenzhen, China
| | - Chuanyu Liu
- BGI-Shenzhen, Shenzhen, China.,Shenzhen Bay Laboratory, Shenzhen, China
| | - Longqi Liu
- BGI-Shenzhen, Shenzhen, China.,Shenzhen Bay Laboratory, Shenzhen, China
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197
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Li H, Humphreys BD. Single Cell Technologies: Beyond Microfluidics. KIDNEY360 2021; 2:1196-1204. [PMID: 35368355 PMCID: PMC8786099 DOI: 10.34067/kid.0001822021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 05/13/2021] [Indexed: 02/04/2023]
Abstract
Single-cell RNA-sequencing (scRNA-seq) has been widely adopted in recent years due to standardized protocols and automation, reliability, and standardized bioinformatic pipelines. The most widely adopted platform is the 10× Genomics solution. Although powerful, this system is limited by its high cost, moderate throughput, and the inability to customize due to fixed kit components. This study will cover new approaches that do not rely on microfluidics and thus have low entry costs, are highly customizable, and are within the reach of any laboratory possessing molecular biology expertise.
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Affiliation(s)
| | - Benjamin D. Humphreys
- Division of Nephrology, Washington University in St. Louis School of Medicine, St. Louis, Missouri,Department of Developmental Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
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198
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Karlsson G, Sommarin MNE, Böiers C. Defining the Emerging Blood System During Development at Single-Cell Resolution. Front Cell Dev Biol 2021; 9:660350. [PMID: 34055791 PMCID: PMC8158578 DOI: 10.3389/fcell.2021.660350] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 03/26/2021] [Indexed: 12/20/2022] Open
Abstract
Developmental hematopoiesis differs from adult and is far less described. In the developing embryo, waves of lineage-restricted blood precede the ultimate emergence of definitive hematopoietic stem cells (dHSCs) capable of maintaining hematopoiesis throughout life. During the last two decades, the advent of single-cell genomics has provided tools to circumvent previously impeding characteristics of embryonic hematopoiesis, such as cell heterogeneity and rare cell states, allowing for definition of lineage trajectories, cellular hierarchies, and cell-type specification. The field has rapidly advanced from microfluidic platforms and targeted gene expression analysis, to high throughput unbiased single-cell transcriptomic profiling, single-cell chromatin analysis, and cell tracing-offering a plethora of tools to resolve important questions within hematopoietic development. Here, we describe how these technologies have been implemented to address a wide range of aspects of embryonic hematopoiesis ranging from the gene regulatory network of dHSC formation via endothelial to hematopoietic transition (EHT) and how EHT can be recapitulated in vitro, to hematopoietic trajectories and cell fate decisions. Together, these studies have important relevance for regenerative medicine and for our understanding of genetic blood disorders and childhood leukemias.
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Affiliation(s)
| | | | - Charlotta Böiers
- Division of Molecular Hematology, Lund Stem Cell Center, Lund University, Lund, Sweden
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199
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Computational principles and challenges in single-cell data integration. Nat Biotechnol 2021; 39:1202-1215. [PMID: 33941931 DOI: 10.1038/s41587-021-00895-7] [Citation(s) in RCA: 158] [Impact Index Per Article: 52.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 03/16/2021] [Indexed: 02/07/2023]
Abstract
The development of single-cell multimodal assays provides a powerful tool for investigating multiple dimensions of cellular heterogeneity, enabling new insights into development, tissue homeostasis and disease. A key challenge in the analysis of single-cell multimodal data is to devise appropriate strategies for tying together data across different modalities. The term 'data integration' has been used to describe this task, encompassing a broad collection of approaches ranging from batch correction of individual omics datasets to association of chromatin accessibility and genetic variation with transcription. Although existing integration strategies exploit similar mathematical ideas, they typically have distinct goals and rely on different principles and assumptions. Consequently, new definitions and concepts are needed to contextualize existing methods and to enable development of new methods.
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200
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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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