1
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Izzo F, Myers RM, Ganesan S, Mekerishvili L, Kottapalli S, Prieto T, Eton EO, Botella T, Dunbar AJ, Bowman RL, Sotelo J, Potenski C, Mimitou EP, Stahl M, El Ghaity-Beckley S, Arandela J, Raviram R, Choi DC, Hoffman R, Chaligné R, Abdel-Wahab O, Smibert P, Ghobrial IM, Scandura JM, Marcellino B, Levine RL, Landau DA. Mapping genotypes to chromatin accessibility profiles in single cells. Nature 2024; 629:1149-1157. [PMID: 38720070 DOI: 10.1038/s41586-024-07388-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 04/04/2024] [Indexed: 05/19/2024]
Abstract
In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.
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Affiliation(s)
- Franco Izzo
- New York Genome Center, New York, NY, USA.
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Robert M Myers
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Saravanan Ganesan
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Levan Mekerishvili
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics and Systems Biology Graduate Program, Weill Cornell Medicine, New York, NY, USA
| | - Sanjay Kottapalli
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Tamara Prieto
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Elliot O Eton
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Theo Botella
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Andrew J Dunbar
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert L Bowman
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jesus Sotelo
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Catherine Potenski
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Eleni P Mimitou
- New York Genome Center, New York, NY, USA
- Immunai, New York, NY, USA
| | - Maximilian Stahl
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medical Oncology, Division of Leukemia, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sebastian El Ghaity-Beckley
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - JoAnn Arandela
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ramya Raviram
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Daniel C Choi
- Laboratory of Molecular Hematopoiesis, Hematology and Oncology, Weill Cornell Medicine, New York, NY, USA
- Richard T. Silver MD Myeloproliferative Neoplasm Center, Weill Cornell Medicine, New York, NY, USA
- Regenerative Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Ronald Hoffman
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ronan Chaligné
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- SAIL: Single-cell Analytics Innovation Lab, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Omar Abdel-Wahab
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Peter Smibert
- New York Genome Center, New York, NY, USA
- 10x Genomics, Pleasanton, CA, USA
| | - Irene M Ghobrial
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Joseph M Scandura
- Laboratory of Molecular Hematopoiesis, Hematology and Oncology, Weill Cornell Medicine, New York, NY, USA
- Richard T. Silver MD Myeloproliferative Neoplasm Center, Weill Cornell Medicine, New York, NY, USA
- Regenerative Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Bridget Marcellino
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ross L Levine
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dan A Landau
- New York Genome Center, New York, NY, USA.
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
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2
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Qadir MMF, Elgamal RM, Song K, Kudtarkar P, Sakamuri SS, Katakam PV, El-Dahr S, Kolls J, Gaulton KJ, Mauvais-Jarvis F. Single cell regulatory architecture of human pancreatic islets suggests sex differences in β cell function and the pathogenesis of type 2 diabetes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589096. [PMID: 38645001 PMCID: PMC11030320 DOI: 10.1101/2024.04.11.589096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Biological sex affects the pathogenesis of type 2 and type 1 diabetes (T2D, T1D) including the development of β cell failure observed more often in males. The mechanisms that drive sex differences in β cell failure is unknown. Studying sex differences in islet regulation and function represent a unique avenue to understand the sex-specific heterogeneity in β cell failure in diabetes. Here, we examined sex and race differences in human pancreatic islets from up to 52 donors with and without T2D (including 37 donors from the Human Pancreas Analysis Program [HPAP] dataset) using an orthogonal series of experiments including single cell RNA-seq (scRNA-seq), single nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), dynamic hormone secretion, and bioenergetics. In cultured islets from nondiabetic (ND) donors, in the absence of the in vivo hormonal environment, sex differences in islet cell type gene accessibility and expression predominantly involved sex chromosomes. Of particular interest were sex differences in the X-linked KDM6A and Y-linked KDM5D chromatin remodelers in female and male islet cells respectively. Islets from T2D donors exhibited similar sex differences in differentially expressed genes (DEGs) from sex chromosomes. However, in contrast to islets from ND donors, islets from T2D donors exhibited major sex differences in DEGs from autosomes. Comparing β cells from T2D and ND donors revealed that females had more DEGs from autosomes compared to male β cells. Gene set enrichment analysis of female β cell DEGs showed a suppression of oxidative phosphorylation and electron transport chain pathways, while male β cell had suppressed insulin secretion pathways. Thus, although sex-specific differences in gene accessibility and expression of cultured ND human islets predominantly affect sex chromosome genes, major differences in autosomal gene expression between sexes appear during the transition to T2D and which highlight mitochondrial failure in female β cells.
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Affiliation(s)
- Mirza Muhammad Fahd Qadir
- Section of Endocrinology and Metabolism, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
- Southeast Louisiana Veterans Health Care System, New Orleans, LA, USA
- Tulane Center of Excellence in Sex-Based Biology & Medicine, New Orleans, LA, USA
| | - Ruth M. Elgamal
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Keijing Song
- Center for Translational Research in Infection and Inflammation, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Parul Kudtarkar
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Siva S.V.P Sakamuri
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA
| | - Prasad V. Katakam
- Department of Pharmacology, Tulane University School of Medicine, New Orleans, LA, USA
| | - Samir El-Dahr
- Department of Pediatrics, Tulane University, School of Medicine, New Orleans, LA, USA
| | - Jay Kolls
- Center for Translational Research in Infection and Inflammation, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Kyle J. Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Franck Mauvais-Jarvis
- Section of Endocrinology and Metabolism, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
- Southeast Louisiana Veterans Health Care System, New Orleans, LA, USA
- Tulane Center of Excellence in Sex-Based Biology & Medicine, New Orleans, LA, USA
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3
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Zhang X, Marand AP, Yan H, Schmitz RJ. scifi-ATAC-seq: massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing. Genome Biol 2024; 25:90. [PMID: 38589969 PMCID: PMC11003106 DOI: 10.1186/s13059-024-03235-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 04/01/2024] [Indexed: 04/10/2024] Open
Abstract
Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow.
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Affiliation(s)
- Xuan Zhang
- Department of Genetics, University of Georgia, Athens, GA, USA
| | - Alexandre P Marand
- Department of Genetics, University of Georgia, Athens, GA, USA
- Current address: Department of Molecular, Cellular, and Development Biology, University of Michigan, Ann Arbor, MI, USA
| | - Haidong Yan
- Department of Genetics, University of Georgia, Athens, GA, USA
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4
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Xu M, Li S, Xie X, Guo L, Yu D, Zhuo J, Lin J, Kol L, Gan L. ISL1 and POU4F1 Directly Interact to Regulate the Differentiation and Survival of Inner Ear Sensory Neurons. J Neurosci 2024; 44:e1718232024. [PMID: 38267260 PMCID: PMC10883659 DOI: 10.1523/jneurosci.1718-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/05/2024] [Accepted: 01/11/2024] [Indexed: 01/26/2024] Open
Abstract
The inner ear sensory neurons play a pivotal role in auditory processing and balance control. Though significant progresses have been made, the underlying mechanisms controlling the differentiation and survival of the inner ear sensory neurons remain largely unknown. During development, ISL1 and POU4F transcription factors are co-expressed and are required for terminal differentiation, pathfinding, axon outgrowth and the survival of neurons in the central and peripheral nervous systems. However, little is understood about their functional relationship and regulatory mechanism in neural development. Here, we have knocked out Isl1 or Pou4f1 or both in mice of both sexes. In the absence of Isl1, the differentiation of cochleovestibular ganglion (CVG) neurons is disturbed and with that Isl1-deficient CVG neurons display defects in migration and axon pathfinding. Compound deletion of Isl1 and Pou4f1 causes a delay in CVG differentiation and results in a more severe CVG defect with a loss of nearly all of spiral ganglion neurons (SGNs). Moreover, ISL1 and POU4F1 interact directly in developing CVG neurons and act cooperatively as well as independently in regulating the expression of unique sets of CVG-specific genes crucial for CVG development and survival by binding to the cis-regulatory elements including the promoters of Fgf10, Pou4f2, and Epha5 and enhancers of Eya1 and Ntng2 These findings demonstrate that Isl1 and Pou4f1 are indispensable for CVG development and maintenance by acting epistatically to regulate genes essential for CVG development.
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Affiliation(s)
- Mei Xu
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
- Institution of Life Sciences, Hangzhou Normal University, Hangzhou 310036, China
| | - Shuchun Li
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
| | - Xiaoling Xie
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
| | - Luming Guo
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
- Institution of Life Sciences, Hangzhou Normal University, Hangzhou 310036, China
| | - Dongliang Yu
- College of Life Science and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China
| | - Jiaping Zhuo
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
| | - Jacey Lin
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
| | - Lotem Kol
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
| | - Lin Gan
- Department of Neuroscience and Regenerative Medicine, Augusta University, Augusta, Georgia 30912
- James and Jean Culver Vision Discovery Institute, Medical College of Georgia, Augusta University, Georgia 30912
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5
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Zhang X, Marand AP, Yan H, Schmitz RJ. Massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.17.558155. [PMID: 37786710 PMCID: PMC10541611 DOI: 10.1101/2023.09.17.558155] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called single-cell combinatorial fluidic indexing ATAC-sequencing ("scifi-ATAC-seq"), which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using a widely commercialized microfluidics platform (10X Genomics). With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples in a single emulsion reaction can be indexed, representing a ~20-fold increase in throughput compared to the standard 10X Genomics workflow.
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Affiliation(s)
- Xuan Zhang
- Department of Genetics, University of Georgia, Athens, GA, USA
| | - Alexandre P Marand
- Department of Genetics, University of Georgia, Athens, GA, USA
- Current address: Department of Molecular, Cellular, and Development Biology, University of Michigan, Ann Arbor, MI, USA
| | - Haidong Yan
- Department of Genetics, University of Georgia, Athens, GA, USA
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Ledru N, Wilson PC, Muto Y, Yoshimura Y, Wu H, Li D, Asthana A, Tullius SG, Waikar SS, Orlando G, Humphreys BD. Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing. Nat Commun 2024; 15:1291. [PMID: 38347009 PMCID: PMC10861555 DOI: 10.1038/s41467-024-45706-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 01/31/2024] [Indexed: 02/15/2024] Open
Abstract
Renal proximal tubule epithelial cells have considerable intrinsic repair capacity following injury. However, a fraction of injured proximal tubule cells fails to undergo normal repair and assumes a proinflammatory and profibrotic phenotype that may promote fibrosis and chronic kidney disease. The healthy to failed repair change is marked by cell state-specific transcriptomic and epigenomic changes. Single nucleus joint RNA- and ATAC-seq sequencing offers an opportunity to study the gene regulatory networks underpinning these changes in order to identify key regulatory drivers. We develop a regularized regression approach to construct genome-wide parametric gene regulatory networks using multiomic datasets. We generate a single nucleus multiomic dataset from seven adult human kidney samples and apply our method to study drivers of a failed injury response associated with kidney disease. We demonstrate that our approach is a highly effective tool for predicting key cis- and trans-regulatory elements underpinning the healthy to failed repair transition and use it to identify NFAT5 as a driver of the maladaptive proximal tubule state.
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Affiliation(s)
- Nicolas Ledru
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Parker C Wilson
- Division of Anatomic and Molecular Pathology, Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
| | - Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Yasuhiro Yoshimura
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Haojia Wu
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Dian Li
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Amish Asthana
- Department of Surgery, Wake Forest Baptist Medical Center; Wake Forest Institute for Regenerative Medicine, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Stefan G Tullius
- Division of Transplant Surgery and Transplant Surgery Research Laboratory, Department of Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston Medical Center, Boston, MA, USA
| | - Giuseppe Orlando
- Department of Surgery, Wake Forest Baptist Medical Center; Wake Forest Institute for Regenerative Medicine, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
- Department of Developmental Biology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
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7
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Wilson PC, Verma A, Yoshimura Y, Muto Y, Li H, Malvin NP, Dixon EE, Humphreys BD. Mosaic loss of Y chromosome is associated with aging and epithelial injury in chronic kidney disease. Genome Biol 2024; 25:36. [PMID: 38287344 PMCID: PMC10823641 DOI: 10.1186/s13059-024-03173-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 01/12/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND Mosaic loss of Y chromosome (LOY) is the most common chromosomal alteration in aging men. Here, we use single-cell RNA and ATAC sequencing to show that LOY is present in the kidney and increases with age and chronic kidney disease. RESULTS The likelihood of a cell having LOY varies depending on its location in the nephron. Cortical epithelial cell types have a greater proportion of LOY than medullary or glomerular cell types, which may reflect their proliferative history. Proximal tubule cells are the most abundant cell type in the cortex and are susceptible to hypoxic injury. A subset of these cells acquires a pro-inflammatory transcription and chromatin accessibility profile associated with expression of HAVCR1, VCAM1, and PROM1. These injured epithelial cells have the greatest proportion of LOY and their presence predicts future kidney function decline. Moreover, proximal tubule cells with LOY are more likely to harbor additional large chromosomal gains and express pro-survival pathways. Spatial transcriptomics localizes injured proximal tubule cells to a pro-fibrotic microenvironment where they adopt a secretory phenotype and likely communicate with infiltrating immune cells. CONCLUSIONS We hypothesize that LOY is an indicator of increased DNA damage and potential marker of cellular senescence that can be applied to single-cell datasets in other tissues.
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Affiliation(s)
- Parker C Wilson
- Division of Diagnostic Innovation, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Amit Verma
- Division of Diagnostic Innovation, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yasuhiro Yoshimura
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Haikuo Li
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Nicole P Malvin
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Eryn E Dixon
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA
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8
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Muto Y, Dixon EE, Yoshimura Y, Ledru N, Kirita Y, Wu H, Humphreys BD. Epigenetic reprogramming driving successful and failed repair in acute kidney injury. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576421. [PMID: 38328130 PMCID: PMC10849487 DOI: 10.1101/2024.01.20.576421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Acute kidney injury (AKI) causes epithelial damage followed by subsequent repair. While successful repair restores kidney function, this process is often incomplete and can lead to chronic kidney disease (CKD) in a process called failed repair. To better understand the epigenetic reprogramming driving this AKI-to-CKD transition we generated a single nucleus multiomic atlas for the full mouse AKI time course, consisting of ~280,000 single nucleus transcriptomes and epigenomes. We reveal cell-specific dynamic alterations in gene regulatory landscapes reflecting especially activation of proinflammatory pathways. We further generated single nucleus multiomic data from four human AKI samples including validation by genome-wide identification of NF-kB binding sites. A regularized regression analysis identifies key regulators involved in both successful and failed repair cell fate, identifying the transcription factor CREB5 as a regulator of both successful and failed tubular repair that also drives proximal tubule cell proliferation after injury. Our interspecies multiomic approach provides a foundation to comprehensively understand cell states in AKI.
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Affiliation(s)
- Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Eryn E. Dixon
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Yasuhiro Yoshimura
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Nicolas Ledru
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Yuhei Kirita
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Haojia Wu
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Benjamin D. Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA
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9
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Benitz S, Steep A, Nasser M, Preall J, Mahajan UM, McQuithey H, Loveless I, Davis ET, Wen HJ, Long DW, Metzler T, Zwernik S, Louw M, Rempinski D, Salas-Escabillas D, Brender S, Song L, Huang L, Zhang Z, Steele NG, Regel I, Bednar F, Crawford HC. ROR2 regulates cellular plasticity in pancreatic neoplasia and adenocarcinoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.13.571566. [PMID: 38168289 PMCID: PMC10760092 DOI: 10.1101/2023.12.13.571566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Cellular plasticity is a hallmark of pancreatic ductal adenocarcinoma (PDAC) starting from the conversion of normal cells into precancerous lesions to the progression of carcinoma subtypes associated with aggressiveness and therapeutic response. We discovered that normal acinar cell differentiation, maintained by the transcription factor Pdx1, suppresses a broad gastric cell identity that is maintained in metaplasia, neoplasia, and the classical subtype of PDAC in mouse and human. We have identified the receptor tyrosine kinase Ror2 as marker of a gastric metaplasia (SPEM)-like identity in the pancreas. Ablation of Ror2 in a mouse model of pancreatic tumorigenesis promoted a switch to a gastric pit cell identity that largely persisted through progression to the classical subtype of PDAC. In both human and mouse pancreatic cancer, ROR2 activity continued to antagonize the gastric pit cell identity, strongly promoting an epithelial to mesenchymal transition, conferring resistance to KRAS inhibition, and vulnerability to AKT inhibition.
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Affiliation(s)
- Simone Benitz
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Alec Steep
- Center of Translational Data Science, University of Chicago, Chicago, Illinois, USA
| | - Malak Nasser
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Jonathan Preall
- Cold Spring Harbor Laboratory Cancer Center, Cold Spring Harbor, New York, USA
| | - Ujjwal M Mahajan
- Department of Medicine II, University Hospital, LMU Munich, Munich, Germany
| | - Holly McQuithey
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Ian Loveless
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan, USA
| | - Erick T Davis
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Hui-Ju Wen
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Daniel W Long
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Thomas Metzler
- Comparative Experimental Pathology (CEP), Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Samuel Zwernik
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Michaela Louw
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Donald Rempinski
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | | | - Sydney Brender
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Linghao Song
- Center of Translational Data Science, University of Chicago, Chicago, Illinois, USA
| | - Ling Huang
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
| | - Zhenyu Zhang
- Center of Translational Data Science, University of Chicago, Chicago, Illinois, USA
| | - Nina G Steele
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
- Department of Pathology, Wayne State University, Detroit, Michigan, USA
- Department of Pharmacology and Toxicology, Michigan State University, Lansing, Michigan, USA
- Department of Oncology, Wayne State University, Detroit, Michigan, USA
| | - Ivonne Regel
- Department of Medicine II, University Hospital, LMU Munich, Munich, Germany
| | - Filip Bednar
- Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA
| | - Howard C Crawford
- Department of Surgery, Henry Ford Health System, Detroit, Michigan, USA
- Department of Pharmacology and Toxicology, Michigan State University, Lansing, Michigan, USA
- Department of Oncology, Wayne State University, Detroit, Michigan, USA
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10
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Miao Z, Kim J. Uniform quantification of single-nucleus ATAC-seq data with Paired-Insertion Counting (PIC) and a model-based insertion rate estimator. Nat Methods 2024; 21:32-36. [PMID: 38049698 PMCID: PMC10776405 DOI: 10.1038/s41592-023-02103-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 10/25/2023] [Indexed: 12/06/2023]
Abstract
Existing approaches to scoring single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) feature matrices from sequencing reads are inconsistent, affecting downstream analyses and displaying artifacts. We show that, even with sparse single-cell data, quantitative counts are informative for estimating the regulatory state of a cell, which calls for a consistent treatment. We propose Paired-Insertion Counting as a uniform method for snATAC-seq feature characterization and provide a probability model for inferring latent insertion dynamics from snATAC-seq count matrices.
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Affiliation(s)
- Zhen Miao
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Junhyong Kim
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
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11
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McKeever PM, Sababi AM, Sharma R, Khuu N, Xu Z, Shen SY, Xiao S, McGoldrick P, Orouji E, Ketela T, Sato C, Moreno D, Visanji N, Kovacs GG, Keith J, Zinman L, Rogaeva E, Goodarzi H, Bader GD, Robertson J. Single-nucleus multiomic atlas of frontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573083. [PMID: 38187588 PMCID: PMC10769403 DOI: 10.1101/2023.12.22.573083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The understanding of how different cell types contribute to amyotrophic lateral sclerosis (ALS) pathogenesis is limited. Here we generated a single-nucleus transcriptomic and epigenomic atlas of the frontal cortex of ALS cases with C9orf72 (C9) hexanucleotide repeat expansions and sporadic ALS (sALS). Our findings reveal shared pathways in C9-ALS and sALS, characterized by synaptic dysfunction in excitatory neurons and a disease-associated state in microglia. The disease subtypes diverge with loss of astrocyte homeostasis in C9-ALS, and a more substantial disturbance of inhibitory neurons in sALS. Leveraging high depth 3'-end sequencing, we found a widespread switch towards distal polyadenylation (PA) site usage across ALS subtypes relative to controls. To explore this differential alternative PA (APA), we developed APA-Net, a deep neural network model that uses transcript sequence and expression levels of RNA-binding proteins (RBPs) to predict cell-type specific APA usage and RBP interactions likely to regulate APA across disease subtypes.
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12
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Zu S, Li YE, Wang K, Armand EJ, Mamde S, Amaral ML, Wang Y, Chu A, Xie Y, Miller M, Xu J, Wang Z, Zhang K, Jia B, Hou X, Lin L, Yang Q, Lee S, Li B, Kuan S, Liu H, Zhou J, Pinto-Duarte A, Lucero J, Osteen J, Nunn M, Smith KA, Tasic B, Yao Z, Zeng H, Wang Z, Shang J, Behrens MM, Ecker JR, Wang A, Preissl S, Ren B. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature 2023; 624:378-389. [PMID: 38092917 PMCID: PMC10719105 DOI: 10.1038/s41586-023-06824-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.
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Affiliation(s)
- Songpeng Zu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Eric Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Department of Neurosurgery and Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Kangli Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Ethan J Armand
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Maria Luisa Amaral
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yuelai Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Andre Chu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Jie Xu
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Kai Zhang
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bojing Jia
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Qian Yang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Bin Li
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Samantha Kuan
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Jacinta Lucero
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia Osteen
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michael Nunn
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Zihan Wang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jingbo Shang
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | | | - Joseph R Ecker
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA.
- Center for Epigenomics, University of California San Diego, School of Medicine, La Jolla, CA, USA.
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13
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Meier AB, Zawada D, De Angelis MT, Martens LD, Santamaria G, Zengerle S, Nowak-Imialek M, Kornherr J, Zhang F, Tian Q, Wolf CM, Kupatt C, Sahara M, Lipp P, Theis FJ, Gagneur J, Goedel A, Laugwitz KL, Dorn T, Moretti A. Epicardioid single-cell genomics uncovers principles of human epicardium biology in heart development and disease. Nat Biotechnol 2023; 41:1787-1800. [PMID: 37012447 PMCID: PMC10713454 DOI: 10.1038/s41587-023-01718-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 02/22/2023] [Indexed: 04/05/2023]
Abstract
The epicardium, the mesothelial envelope of the vertebrate heart, is the source of multiple cardiac cell lineages during embryonic development and provides signals that are essential to myocardial growth and repair. Here we generate self-organizing human pluripotent stem cell-derived epicardioids that display retinoic acid-dependent morphological, molecular and functional patterning of the epicardium and myocardium typical of the left ventricular wall. By combining lineage tracing, single-cell transcriptomics and chromatin accessibility profiling, we describe the specification and differentiation process of different cell lineages in epicardioids and draw comparisons to human fetal development at the transcriptional and morphological levels. We then use epicardioids to investigate the functional cross-talk between cardiac cell types, gaining new insights into the role of IGF2/IGF1R and NRP2 signaling in human cardiogenesis. Finally, we show that epicardioids mimic the multicellular pathogenesis of congenital or stress-induced hypertrophy and fibrotic remodeling. As such, epicardioids offer a unique testing ground of epicardial activity in heart development, disease and regeneration.
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Affiliation(s)
- Anna B Meier
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Dorota Zawada
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Maria Teresa De Angelis
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
- Department of Experimental and Clinical Medicine, University 'Magna Graecia', Catanzaro, Italy
| | - Laura D Martens
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
- Helmholtz Association-Munich School for Data Science (MUDS), Munich, Germany
| | - Gianluca Santamaria
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
- Department of Experimental and Clinical Medicine, University 'Magna Graecia', Catanzaro, Italy
| | - Sophie Zengerle
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Monika Nowak-Imialek
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Jessica Kornherr
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Fangfang Zhang
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Qinghai Tian
- Center for Molecular Signaling (PZMS), Institute for Molecular Cell Biology, Research Center for Molecular Imaging and Screening, Medical Faculty, Saarland University, Homburg, Germany
| | - Cordula M Wolf
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
- Department of Congenital Heart Defects and Pediatric Cardiology, German Heart Center Munich, Technical University of Munich, School of Medicine and Health, Munich, Germany
| | - Christian Kupatt
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
| | - Makoto Sahara
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
- Department of Surgery, Yale University School of Medicine, New Haven, CT, USA
| | - Peter Lipp
- Center for Molecular Signaling (PZMS), Institute for Molecular Cell Biology, Research Center for Molecular Imaging and Screening, Medical Faculty, Saarland University, Homburg, Germany
| | - Fabian J Theis
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
| | - Julien Gagneur
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Alexander Goedel
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Karl-Ludwig Laugwitz
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
| | - Tatjana Dorn
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Alessandra Moretti
- First Department of Medicine, Cardiology, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany.
- Regenerative Medicine in Cardiovascular Diseases, First Department of Medicine, Klinikum rechts der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany.
- German Center for Cardiovascular Research (DZHK), Munich Heart Alliance, Munich, Germany.
- Department of Surgery, Yale University School of Medicine, New Haven, CT, USA.
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14
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Walker JT, Saunders DC, Rai V, Chen HH, Orchard P, Dai C, Pettway YD, Hopkirk AL, Reihsmann CV, Tao Y, Fan S, Shrestha S, Varshney A, Petty LE, Wright JJ, Ventresca C, Agarwala S, Aramandla R, Poffenberger G, Jenkins R, Mei S, Hart NJ, Phillips S, Kang H, Greiner DL, Shultz LD, Bottino R, Liu J, Below JE, Parker SCJ, Powers AC, Brissova M. Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature 2023; 624:621-629. [PMID: 38049589 DOI: 10.1038/s41586-023-06693-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 09/28/2023] [Indexed: 12/06/2023]
Abstract
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.
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Affiliation(s)
- John T Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chunhua Dai
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yasminye D Pettway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexander L Hopkirk
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Conrad V Reihsmann
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yicheng Tao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Simin Fan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Shristi Shrestha
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan J Wright
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christa Ventresca
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Samir Agarwala
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Radhika Aramandla
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Greg Poffenberger
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Regina Jenkins
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shaojun Mei
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nathaniel J Hart
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sharon Phillips
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dale L Greiner
- Department of Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA, USA
| | | | - Rita Bottino
- Imagine Pharma, Devon, PA, USA
- Institute of Cellular Therapeutics, Allegheny-Singer Research Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Jie Liu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Alvin C Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA.
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- VA Tennessee Valley Healthcare System, Nashville, TN, USA.
| | - Marcela Brissova
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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15
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Angarola BL, Sharma S, Katiyar N, Gu Kang H, Nehar-Belaid D, Park S, Gott R, Eryilmaz GN, LaBarge MA, Palucka K, Chuang JH, Korstanje R, Ucar D, Anczukow O. Comprehensive single cell aging atlas of mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.20.563147. [PMID: 37961129 PMCID: PMC10634680 DOI: 10.1101/2023.10.20.563147] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Aging is the greatest risk factor for breast cancer; however, how age-related cellular and molecular events impact cancer initiation is unknown. We investigate how aging rewires transcriptomic and epigenomic programs of mouse mammary glands at single cell resolution, yielding a comprehensive resource for aging and cancer biology. Aged epithelial cells exhibit epigenetic and transcriptional changes in metabolic, pro-inflammatory, or cancer-associated genes. Aged stromal cells downregulate fibroblast marker genes and upregulate markers of senescence and cancer-associated fibroblasts. Among immune cells, distinct T cell subsets (Gzmk+, memory CD4+, γδ) and M2-like macrophages expand with age. Spatial transcriptomics reveal co-localization of aged immune and epithelial cells in situ. Lastly, transcriptional signatures of aging mammary cells are found in human breast tumors, suggesting mechanistic links between aging and cancer. Together, these data uncover that epithelial, immune, and stromal cells shift in proportions and cell identity, potentially impacting cell plasticity, aged microenvironment, and neoplasia risk.
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Affiliation(s)
| | | | - Neerja Katiyar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Hyeon Gu Kang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - SungHee Park
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Giray N Eryilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Mark A LaBarge
- Beckman Research Institute at City of Hope, Duarte, CA, USA
| | - Karolina Palucka
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Jeffrey H Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
- Institute for Systems Genomics, UConn Health, Farmington, CT, USA
| | - Olga Anczukow
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
- Institute for Systems Genomics, UConn Health, Farmington, CT, USA
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16
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Nair S, Ameen M, Sundaram L, Pampari A, Schreiber J, Balsubramani A, Wang YX, Burns D, Blau HM, Karakikes I, Wang KC, Kundaje A. Transcription factor stoichiometry, motif affinity and syntax regulate single-cell chromatin dynamics during fibroblast reprogramming to pluripotency. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.04.560808. [PMID: 37873116 PMCID: PMC10592962 DOI: 10.1101/2023.10.04.560808] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Ectopic expression of OCT4, SOX2, KLF4 and MYC (OSKM) transforms differentiated cells into induced pluripotent stem cells. To refine our mechanistic understanding of reprogramming, especially during the early stages, we profiled chromatin accessibility and gene expression at single-cell resolution across a densely sampled time course of human fibroblast reprogramming. Using neural networks that map DNA sequence to ATAC-seq profiles at base-resolution, we annotated cell-state-specific predictive transcription factor (TF) motif syntax in regulatory elements, inferred affinity- and concentration-dependent dynamics of Tn5-bias corrected TF footprints, linked peaks to putative target genes, and elucidated rewiring of TF-to-gene cis-regulatory networks. Our models reveal that early in reprogramming, OSK, at supraphysiological concentrations, rapidly open transient regulatory elements by occupying non-canonical low-affinity binding sites. As OSK concentration falls, the accessibility of these transient elements decays as a function of motif affinity. We find that these OSK-dependent transient elements sequester the somatic TF AP-1. This redistribution is strongly associated with the silencing of fibroblast-specific genes within individual nuclei. Together, our integrated single-cell resource and models reveal insights into the cis-regulatory code of reprogramming at unprecedented resolution, connect TF stoichiometry and motif syntax to diversification of cell fate trajectories, and provide new perspectives on the dynamics and role of transient regulatory elements in somatic silencing.
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Affiliation(s)
- Surag Nair
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Mohamed Ameen
- Department of Cancer Biology, Stanford University, Stanford, CA, USA
- Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
| | | | - Anusri Pampari
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jacob Schreiber
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Yu Xin Wang
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
| | - David Burns
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
| | - Helen M Blau
- Baxter Laboratory for Stem Cell Biology, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Ioannis Karakikes
- Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
| | - Kevin C Wang
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Anshul Kundaje
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
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17
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Zhang W, Jiang R, Chen S, Wang Y. scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data. Genome Biol 2023; 24:225. [PMID: 37814314 PMCID: PMC10561408 DOI: 10.1186/s13059-023-03072-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 09/22/2023] [Indexed: 10/11/2023] Open
Abstract
Application of the widely used droplet-based microfluidic technologies in single-cell sequencing often yields doublets, introducing bias to downstream analyses. Especially, doublet-detection methods for single-cell chromatin accessibility sequencing (scCAS) data have multiple assay-specific challenges. Therefore, we propose scIBD, a self-supervised iterative-optimizing model for boosting heterotypic doublet detection in scCAS data. scIBD introduces an adaptive strategy to simulate high-confident heterotypic doublets and self-supervise for doublet-detection in an iteratively optimizing manner. Comprehensive benchmarking on various simulated and real datasets demonstrates the outperformance and robustness of scIBD. Moreover, the downstream biological analyses suggest the efficacy of doublet-removal by scIBD.
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Affiliation(s)
- Wenhao Zhang
- Department of Automation, Xiamen University, Xiamen, 361000, Fujian, China
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361000, Fujian, China
| | - Rui Jiang
- Ministry of Education Key Laboratory of Bioinformatics, Research Department of Bioinformatics at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Shengquan Chen
- School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, China.
| | - Ying Wang
- Department of Automation, Xiamen University, Xiamen, 361000, Fujian, China.
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361000, Fujian, China.
- Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen, 361005, Fujian, China.
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18
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Engel JL, Zhang X, Lu DR, Vila OF, Arias V, Lee J, Hale C, Hsu YH, Li CM, Wu RS, Vedantham V, Ang YS. Single Cell Multi-Omics of an iPSC Model of Human Sinoatrial Node Development Reveals Genetic Determinants of Heart Rate and Arrhythmia Susceptibility. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.01.547335. [PMID: 37425707 PMCID: PMC10327193 DOI: 10.1101/2023.07.01.547335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Cellular heterogeneity within the sinoatrial node (SAN) is functionally important but has been difficult to model in vitro , presenting a major obstacle to studies of heart rate regulation and arrhythmias. Here we describe a scalable method to derive sinoatrial node pacemaker cardiomyocytes (PCs) from human induced pluripotent stem cells that recapitulates differentiation into distinct PC subtypes, including SAN Head, SAN Tail, transitional zone cells, and sinus venosus myocardium. Single cell (sc) RNA-sequencing, sc-ATAC-sequencing, and trajectory analyses were used to define epigenetic and transcriptomic signatures of each cell type, and to identify novel transcriptional pathways important for PC subtype differentiation. Integration of our multi-omics datasets with genome wide association studies uncovered cell type-specific regulatory elements that associated with heart rate regulation and susceptibility to atrial fibrillation. Taken together, these datasets validate a novel, robust, and realistic in vitro platform that will enable deeper mechanistic exploration of human cardiac automaticity and arrhythmia.
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19
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Wong M, Wei Y, Ho YC. Single-cell multiomic understanding of HIV-1 reservoir at epigenetic, transcriptional, and protein levels. Curr Opin HIV AIDS 2023; 18:246-256. [PMID: 37535039 PMCID: PMC10442869 DOI: 10.1097/coh.0000000000000809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
PURPOSE OF REVIEW The success of HIV-1 eradication strategies relies on in-depth understanding of HIV-1-infected cells. However, HIV-1-infected cells are extremely heterogeneous and rare. Single-cell multiomic approaches resolve the heterogeneity and rarity of HIV-1-infected cells. RECENT FINDINGS Advancement in single-cell multiomic approaches enabled HIV-1 reservoir profiling across the epigenetic (ATAC-seq), transcriptional (RNA-seq), and protein levels (CITE-seq). Using HIV-1 RNA as a surrogate, ECCITE-seq identified enrichment of HIV-1-infected cells in clonally expanded cytotoxic CD4+ T cells. Using HIV-1 DNA PCR-activated microfluidic sorting, FIND-seq captured the bulk transcriptome of HIV-1 DNA+ cells. Using targeted HIV-1 DNA amplification, PheP-seq identified surface protein expression of intact versus defective HIV-1-infected cells. Using ATAC-seq to identify HIV-1 DNA, ASAP-seq captured transcription factor activity and surface protein expression of HIV-1 DNA+ cells. Combining HIV-1 mapping by ATAC-seq and HIV-1 RNA mapping by RNA-seq, DOGMA-seq captured the epigenetic, transcriptional, and surface protein expression of latent and transcriptionally active HIV-1-infected cells. To identify reproducible biological insights and authentic HIV-1-infected cells and avoid false-positive discovery of artifacts, we reviewed current practices of single-cell multiomic experimental design and bioinformatic analysis. SUMMARY Single-cell multiomic approaches may identify innovative mechanisms of HIV-1 persistence, nominate therapeutic strategies, and accelerate discoveries.
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Affiliation(s)
- Michelle Wong
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, Connecticut, USA
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20
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Cheong JG, Ravishankar A, Sharma S, Parkhurst CN, Grassmann SA, Wingert CK, Laurent P, Ma S, Paddock L, Miranda IC, Karakaslar EO, Nehar-Belaid D, Thibodeau A, Bale MJ, Kartha VK, Yee JK, Mays MY, Jiang C, Daman AW, Martinez de Paz A, Ahimovic D, Ramos V, Lercher A, Nielsen E, Alvarez-Mulett S, Zheng L, Earl A, Yallowitz A, Robbins L, LaFond E, Weidman KL, Racine-Brzostek S, Yang HS, Price DR, Leyre L, Rendeiro AF, Ravichandran H, Kim J, Borczuk AC, Rice CM, Jones RB, Schenck EJ, Kaner RJ, Chadburn A, Zhao Z, Pascual V, Elemento O, Schwartz RE, Buenrostro JD, Niec RE, Barrat FJ, Lief L, Sun JC, Ucar D, Josefowicz SZ. Epigenetic memory of coronavirus infection in innate immune cells and their progenitors. Cell 2023; 186:3882-3902.e24. [PMID: 37597510 PMCID: PMC10638861 DOI: 10.1016/j.cell.2023.07.019] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 04/20/2023] [Accepted: 07/12/2023] [Indexed: 08/21/2023]
Abstract
Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.
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Affiliation(s)
- Jin-Gyu Cheong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Arjun Ravishankar
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Siddhartha Sharma
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | | | - Simon A Grassmann
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Claire K Wingert
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Paoline Laurent
- HSS Research Institute, Hospital for Special Surgery, New York, NY 10021, USA
| | - Sai Ma
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Lucinda Paddock
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Emin Onur Karakaslar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | | | - Asa Thibodeau
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Michael J Bale
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Vinay K Kartha
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Jim K Yee
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Minh Y Mays
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Chenyang Jiang
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Andrew W Daman
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alexia Martinez de Paz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Dughan Ahimovic
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Victor Ramos
- The Rockefeller University, New York, NY 10065, USA
| | | | - Erik Nielsen
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Ling Zheng
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Andrew Earl
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Alisha Yallowitz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Lexi Robbins
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Karissa L Weidman
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Sabrina Racine-Brzostek
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - He S Yang
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - David R Price
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Louise Leyre
- Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - André F Rendeiro
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA; CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Hiranmayi Ravichandran
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Junbum Kim
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alain C Borczuk
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Pathology and Laboratory Medicine, Northwell Health, Greenvale, NY 11548, USA
| | | | - R Brad Jones
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY 10065, USA; Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Edward J Schenck
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Robert J Kaner
- Department of Genetic Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Amy Chadburn
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Zhen Zhao
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Virginia Pascual
- Department of Pediatrics, Gale and Ira Drukier Institute for Children's Health, Weill Cornell Medicine, New York, NY 10065, USA
| | - Olivier Elemento
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Robert E Schwartz
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Jason D Buenrostro
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Rachel E Niec
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA; The Rockefeller University, New York, NY 10065, USA
| | - Franck J Barrat
- Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA; HSS Research Institute, Hospital for Special Surgery, New York, NY 10021, USA; Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Lindsay Lief
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Joseph C Sun
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, USA.
| | - Steven Z Josefowicz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA.
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21
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Heumos L, Schaar AC, Lance C, Litinetskaya A, Drost F, Zappia L, Lücken MD, Strobl DC, Henao J, Curion F, Schiller HB, Theis FJ. Best practices for single-cell analysis across modalities. Nat Rev Genet 2023; 24:550-572. [PMID: 37002403 PMCID: PMC10066026 DOI: 10.1038/s41576-023-00586-w] [Citation(s) in RCA: 111] [Impact Index Per Article: 111.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2023] [Indexed: 04/03/2023]
Abstract
Recent advances in single-cell technologies have enabled high-throughput molecular profiling of cells across modalities and locations. Single-cell transcriptomics data can now be complemented by chromatin accessibility, surface protein expression, adaptive immune receptor repertoire profiling and spatial information. The increasing availability of single-cell data across modalities has motivated the development of novel computational methods to help analysts derive biological insights. As the field grows, it becomes increasingly difficult to navigate the vast landscape of tools and analysis steps. Here, we summarize independent benchmarking studies of unimodal and multimodal single-cell analysis across modalities to suggest comprehensive best-practice workflows for the most common analysis steps. Where independent benchmarks are not available, we review and contrast popular methods. Our article serves as an entry point for novices in the field of single-cell (multi-)omic analysis and guides advanced users to the most recent best practices.
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Affiliation(s)
- Lukas Heumos
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center, Helmholtz Munich; Member of the German Center for Lung Research (DZL), Munich, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
| | - Anna C Schaar
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Munich Center for Machine Learning, Technical University of Munich, Garching, Germany
| | - Christopher Lance
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Department of Paediatrics, Dr von Hauner Children's Hospital, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anastasia Litinetskaya
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Felix Drost
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
| | - Luke Zappia
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Malte D Lücken
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Institute of Lung Health and Immunity, Helmholtz Munich, Munich, Germany
| | - Daniel C Strobl
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
- Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine, Technical University of Munich, Munich, Germany
- TranslaTUM, Center for Translational Cancer Research, Technical University of Munich, Munich, Germany
| | - Juan Henao
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
| | - Fabiola Curion
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Herbert B Schiller
- Institute of Lung Health and Immunity and Comprehensive Pneumology Center, Helmholtz Munich; Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Fabian J Theis
- Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
- Munich Center for Machine Learning, Technical University of Munich, Garching, Germany.
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22
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Chambers C, Cermakova K, Chan YS, Kurtz K, Wohlan K, Lewis AH, Wang C, Pham A, Dejmek M, Sala M, Loeza Cabrera M, Aguilar R, Nencka R, Lacorazza HD, Rau RE, Hodges HC. SWI/SNF Blockade Disrupts PU.1-Directed Enhancer Programs in Normal Hematopoietic Cells and Acute Myeloid Leukemia. Cancer Res 2023; 83:983-996. [PMID: 36662812 PMCID: PMC10071820 DOI: 10.1158/0008-5472.can-22-2129] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/09/2022] [Accepted: 01/18/2023] [Indexed: 01/21/2023]
Abstract
In acute myeloid leukemia (AML), SWI/SNF chromatin remodeling complexes sustain leukemic identity by driving high levels of MYC. Previous studies have implicated the hematopoietic transcription factor PU.1 (SPI1) as an important target of SWI/SNF inhibition, but PU.1 is widely regarded to have pioneer-like activity. As a result, many questions have remained regarding the interplay between PU.1 and SWI/SNF in AML as well as normal hematopoiesis. Here we found that PU.1 binds to most of its targets in a SWI/SNF-independent manner and recruits SWI/SNF to promote accessibility for other AML core regulatory factors, including RUNX1, LMO2, and MEIS1. SWI/SNF inhibition in AML cells reduced DNA accessibility and binding of these factors at PU.1 sites and redistributed PU.1 to promoters. Analysis of nontumor hematopoietic cells revealed that similar effects also impair PU.1-dependent B-cell and monocyte populations. Nevertheless, SWI/SNF inhibition induced profound therapeutic response in an immunocompetent AML mouse model as well as in primary human AML samples. In vivo, SWI/SNF inhibition promoted leukemic differentiation and reduced the leukemic stem cell burden in bone marrow but also induced leukopenia. These results reveal a variable therapeutic window for SWI/SNF blockade in AML and highlight important off-tumor effects of such therapies in immunocompetent settings. SIGNIFICANCE Disruption of PU.1-directed enhancer programs upon SWI/SNF inhibition causes differentiation of AML cells and induces leukopenia of PU.1-dependent B cells and monocytes, revealing the on- and off-tumor effects of SWI/SNF blockade.
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Affiliation(s)
- Courtney Chambers
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
- Translational Biology and Molecular Medicine Graduate Program, Baylor College of Medicine, Houston, Texas
| | - Katerina Cermakova
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Yuen San Chan
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Kristen Kurtz
- Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas
| | - Katharina Wohlan
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
| | - Andrew Henry Lewis
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas
| | - Christiana Wang
- Genetics and Genomics Graduate Program, Baylor College of Medicine, Houston, Texas
| | - Anh Pham
- Department of Bioengineering, Rice University, Houston, Texas
| | - Milan Dejmek
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Michal Sala
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Mario Loeza Cabrera
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Rogelio Aguilar
- Stem Cells and Regenerative Medicine Center, Baylor College of Medicine, Houston, Texas
| | - Radim Nencka
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - H. Daniel Lacorazza
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas
| | - Rachel E. Rau
- Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas
- Stem Cells and Regenerative Medicine Center, Baylor College of Medicine, Houston, Texas
| | - H. Courtney Hodges
- Department of Molecular and Cellular Biology, Center for Precision Environmental Health, Baylor College of Medicine, Houston, Texas
- Department of Bioengineering, Rice University, Houston, Texas
- Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, Texas
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23
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Wu VH, Nordin JML, Nguyen S, Joy J, Mampe F, Del Rio Estrada PM, Torres-Ruiz F, González-Navarro M, Luna-Villalobos YA, Ávila-Ríos S, Reyes-Terán G, Tebas P, Montaner LJ, Bar KJ, Vella LA, Betts MR. Profound phenotypic and epigenetic heterogeneity of the HIV-1-infected CD4 + T cell reservoir. Nat Immunol 2023; 24:359-370. [PMID: 36536105 PMCID: PMC9892009 DOI: 10.1038/s41590-022-01371-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/24/2022] [Indexed: 12/24/2022]
Abstract
Understanding the complexity of the long-lived HIV reservoir during antiretroviral therapy (ART) remains a considerable impediment in research towards a cure for HIV. To address this, we developed a single-cell strategy to precisely define the unperturbed peripheral blood HIV-infected memory CD4+ T cell reservoir from ART-treated people living with HIV (ART-PLWH) via the presence of integrated accessible proviral DNA in concert with epigenetic and cell surface protein profiling. We identified profound reservoir heterogeneity within and between ART-PLWH, characterized by new and known surface markers within total and individual memory CD4+ T cell subsets. We further uncovered new epigenetic profiles and transcription factor motifs enriched in HIV-infected cells that suggest infected cells with accessible provirus, irrespective of reservoir distribution, are poised for reactivation during ART treatment. Together, our findings reveal the extensive inter- and intrapersonal cellular heterogeneity of the HIV reservoir, and establish an initial multiomic atlas to develop targeted reservoir elimination strategies.
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Affiliation(s)
- Vincent H Wu
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Jayme M L Nordin
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Son Nguyen
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Medical Engineering and Science, Department of Chemistry, and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jaimy Joy
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Felicity Mampe
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Perla M Del Rio Estrada
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Fernanda Torres-Ruiz
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Mauricio González-Navarro
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Yara Andrea Luna-Villalobos
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Santiago Ávila-Ríos
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Gustavo Reyes-Terán
- Institutos Nacionales de Salud y Hospitales de Alta Especialidad, Secretaría de Salud de México, Mexico City, Mexico
| | - Pablo Tebas
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Luis J Montaner
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- The Wistar Institute, Philadelphia, PA, USA
| | - Katharine J Bar
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura A Vella
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA.
- Division of Infectious Diseases, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Michael R Betts
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA.
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24
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Preissl S, Gaulton KJ, Ren B. Characterizing cis-regulatory elements using single-cell epigenomics. Nat Rev Genet 2023; 24:21-43. [PMID: 35840754 PMCID: PMC9771884 DOI: 10.1038/s41576-022-00509-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2022] [Indexed: 12/24/2022]
Abstract
Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.
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Affiliation(s)
- Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Kyle J Gaulton
- Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
| | - Bing Ren
- 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.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
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25
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Hu K, Liu H, Lawson ND, Zhu LJ. scATACpipe: A nextflow pipeline for comprehensive and reproducible analyses of single cell ATAC-seq data. Front Cell Dev Biol 2022; 10:981859. [PMID: 36238687 PMCID: PMC9551270 DOI: 10.3389/fcell.2022.981859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Single cell ATAC-seq (scATAC-seq) has become the most widely used method for profiling open chromatin landscape of heterogeneous cell populations at a single-cell resolution. Although numerous software tools and pipelines have been developed, an easy-to-use, scalable, reproducible, and comprehensive pipeline for scATAC-seq data analyses is still lacking. To fill this gap, we developed scATACpipe, a Nextflow pipeline, for performing comprehensive analyses of scATAC-seq data including extensive quality assessment, preprocessing, dimension reduction, clustering, peak calling, differential accessibility inference, integration with scRNA-seq data, transcription factor activity and footprinting analysis, co-accessibility inference, and cell trajectory prediction. scATACpipe enables users to perform the end-to-end analysis of scATAC-seq data with three sub-workflow options for preprocessing that leverage 10x Genomics Cell Ranger ATAC software, the ultra-fast Chromap procedures, and a set of custom scripts implementing current best practices for scATAC-seq data preprocessing. The pipeline extends the R package ArchR for downstream analysis with added support to any eukaryotic species with an annotated reference genome. Importantly, scATACpipe generates an all-in-one HTML report for the entire analysis and outputs cluster-specific BAM, BED, and BigWig files for visualization in a genome browser. scATACpipe eliminates the need for users to chain different tools together and facilitates reproducible and comprehensive analyses of scATAC-seq data from raw reads to various biological insights with minimal changes of configuration settings for different computing environments or species. By applying it to public datasets, we illustrated the utility, flexibility, versatility, and reliability of our pipeline, and demonstrated that our scATACpipe outperforms other workflows.
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Affiliation(s)
- Kai Hu
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Haibo Liu
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Nathan D. Lawson
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Lihua Julie Zhu
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, United States
- Program in Molecular Medicine, Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, United States
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26
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Wilson PC, Muto Y, Wu H, Karihaloo A, Waikar SS, Humphreys BD. Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression. Nat Commun 2022; 13:5253. [PMID: 36068241 PMCID: PMC9448792 DOI: 10.1038/s41467-022-32972-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 08/25/2022] [Indexed: 11/09/2022] Open
Abstract
The proximal tubule is a key regulator of kidney function and glucose metabolism. Diabetic kidney disease leads to proximal tubule injury and changes in chromatin accessibility that modify the activity of transcription factors involved in glucose metabolism and inflammation. Here we use single nucleus RNA and ATAC sequencing to show that diabetic kidney disease leads to reduced accessibility of glucocorticoid receptor binding sites and an injury-associated expression signature in the proximal tubule. We hypothesize that chromatin accessibility is regulated by genetic background and closely-intertwined with metabolic memory, which pre-programs the proximal tubule to respond differently to external stimuli. Glucocorticoid excess has long been known to increase risk for type 2 diabetes, which raises the possibility that glucocorticoid receptor inhibition may mitigate the adverse metabolic effects of diabetic kidney disease.
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Affiliation(s)
- Parker C Wilson
- Division of Anatomic and Molecular Pathology, Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
| | - Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Haojia Wu
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Anil Karihaloo
- Novo Nordisk Research Center Seattle Inc, Seattle, WA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA.
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27
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Shi P, Nie Y, Yang J, Zhang W, Tang Z, Xu J. Fundamental and practical approaches for single-cell ATAC-seq analysis. ABIOTECH 2022; 3:212-223. [PMID: 36313930 PMCID: PMC9590475 DOI: 10.1007/s42994-022-00082-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 09/07/2022] [Indexed: 11/28/2022]
Abstract
Assays for transposase-accessible chromatin through high-throughput sequencing (ATAC-seq) are effective tools in the study of genome-wide chromatin accessibility landscapes. With the rapid development of single-cell technology, open chromatin regions that play essential roles in epigenetic regulation have been measured at the single-cell level using single-cell ATAC-seq approaches. The application of scATAC-seq has become as popular as that of scRNA-seq. However, owing to the nature of scATAC-seq data, which are sparse and noisy, processing the data requires different methodologies and empirical experience. This review presents a practical guide for processing scATAC-seq data, from quality evaluation to downstream analysis, for various applications. In addition to the epigenomic profiling from scATAC-seq, we also discuss recent studies in which the function of non-coding variants has been investigated based on cell type-specific cis-regulatory elements and how to use the by-product genetic information obtained from scATAC-seq to infer single-cell copy number variants and trace cell lineage. We anticipate that this review will assist researchers in designing and implementing scATAC-seq assays to facilitate research in diverse fields.
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Affiliation(s)
- Peiyu Shi
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275 China
| | - Yage Nie
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275 China
| | - Jiawen Yang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275 China
| | - Weixing Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275 China
| | - Zhongjie Tang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275 China
| | - Jin Xu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275 China
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28
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Duttke SH, Montilla-Perez P, Chang MW, Li H, Chen H, Carrette LLG, de Guglielmo G, George O, Palmer AA, Benner C, Telese F. Glucocorticoid Receptor-Regulated Enhancers Play a Central Role in the Gene Regulatory Networks Underlying Drug Addiction. Front Neurosci 2022; 16:858427. [PMID: 35651629 PMCID: PMC9149415 DOI: 10.3389/fnins.2022.858427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/25/2022] [Indexed: 01/07/2023] Open
Abstract
Substance abuse and addiction represent a significant public health problem that impacts multiple dimensions of society, including healthcare, the economy, and the workforce. In 2021, over 100,000 drug overdose deaths were reported in the US, with an alarming increase in fatalities related to opioids and psychostimulants. Understanding the fundamental gene regulatory mechanisms underlying addiction and related behaviors could facilitate more effective treatments. To explore how repeated drug exposure alters gene regulatory networks in the brain, we combined capped small (cs)RNA-seq, which accurately captures nascent-like initiating transcripts from total RNA, with Hi-C and single nuclei (sn)ATAC-seq. We profiled initiating transcripts in two addiction-related brain regions, the prefrontal cortex (PFC) and the nucleus accumbens (NAc), from rats that were never exposed to drugs or were subjected to prolonged abstinence after oxycodone or cocaine intravenous self-administration (IVSA). Interrogating over 100,000 active transcription start regions (TSRs) revealed that most TSRs had hallmarks of bonafide enhancers and highlighted the KLF/SP1, RFX, and AP1 transcription factors families as central to establishing brain-specific gene regulatory programs. Analysis of rats with addiction-like behaviors versus controls identified addiction-associated repression of transcription at regulatory enhancers recognized by nuclear receptor subfamily 3 group C (NR3C) factors, including glucocorticoid receptors. Cell-type deconvolution analysis using snATAC-seq uncovered a potential role of glial cells in driving the gene regulatory programs associated with addiction-related phenotypes. These findings highlight the power of advanced transcriptomics methods to provide insight into how addiction perturbs gene regulatory programs in the brain.
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Affiliation(s)
- Sascha H. Duttke
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, United States
| | | | - Max W. Chang
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Hairi Li
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, United States
| | | | - Giordano de Guglielmo
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Olivier George
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Abraham A. Palmer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Christopher Benner
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Francesca Telese
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
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29
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Germain PL, Lun A, Garcia Meixide C, Macnair W, Robinson MD. Doublet identification in single-cell sequencing data using scDblFinder. F1000Res 2022; 10:979. [PMID: 35814628 PMCID: PMC9204188 DOI: 10.12688/f1000research.73600.2] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/28/2022] [Indexed: 11/20/2022] Open
Abstract
Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed
scDblFinder, a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility (ATAC) sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets,
scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.
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Affiliation(s)
- Pierre-Luc Germain
- DMLS Lab of Statistical Bioinformatics, University of Zürich, Zürich, 805, Switzerland
- D-HEST Institute for Neuroscience, ETH Zürich, Zürich, Switzerland
- Swiss Institute of Bioinformatics, University of Zürich, Zürich, Switzerland
| | - Aaron Lun
- Genentech Inc., South San Francisco, CA, USA
| | | | - Will Macnair
- Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-LaRoche Ltd, Basel, Switzerland
| | - Mark D. Robinson
- DMLS Lab of Statistical Bioinformatics, University of Zürich, Zürich, 805, Switzerland
- Swiss Institute of Bioinformatics, University of Zürich, Zürich, Switzerland
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30
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Germain PL, Lun A, Garcia Meixide C, Macnair W, Robinson MD. Doublet identification in single-cell sequencing data using scDblFinder. F1000Res 2021; 10:979. [PMID: 35814628 PMCID: PMC9204188 DOI: 10.12688/f1000research.73600.1] [Citation(s) in RCA: 118] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/28/2022] [Indexed: 07/27/2023] Open
Abstract
Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed scDblFinder, a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility (ATAC) sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets, scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.
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Affiliation(s)
- Pierre-Luc Germain
- DMLS Lab of Statistical Bioinformatics, University of Zürich, Zürich, 805, Switzerland
- D-HEST Institute for Neuroscience, ETH Zürich, Zürich, Switzerland
- Swiss Institute of Bioinformatics, University of Zürich, Zürich, Switzerland
| | - Aaron Lun
- Genentech Inc., South San Francisco, CA, USA
| | | | - Will Macnair
- Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, F. Hoffmann-LaRoche Ltd, Basel, Switzerland
| | - Mark D. Robinson
- DMLS Lab of Statistical Bioinformatics, University of Zürich, Zürich, 805, Switzerland
- Swiss Institute of Bioinformatics, University of Zürich, Zürich, Switzerland
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