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Zhao F, Ma X, Yao B, Chen L. scaDA: A Novel Statistical Method for Differential Analysis of Single-Cell Chromatin Accessibility Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.21.576570. [PMID: 38328112 PMCID: PMC10849518 DOI: 10.1101/2024.01.21.576570] [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
Single-cell ATAC-seq sequencing data (scATAC-seq) has been widely used to investigate chromatin accessibility on the single-cell level. One important application of scATAC-seq data analysis is differential chromatin accessibility analysis. However, the data characteristics of scATAC-seq such as excessive zeros and large variability of chromatin accessibility across cells impose a unique challenge for DA analysis. Existing statistical methods focus on detecting the mean difference of the chromatin accessible regions while overlooking the distribution difference. Motivated by real data exploration that distribution difference exists among cell types, we introduce a novel composite statistical test named "scaDA", which is based on zero-inflated negative binomial model (ZINB), for performing differential distribution analysis of chromatin accessibility by jointly testing the abundance, prevalence and dispersion simultaneously. Benefiting from both dispersion shrinkage and iterative refinement of mean and prevalence parameter estimates, scaDA demonstrates its superiority to both ZINB-based likelihood ratio tests and published methods by achieving the highest power and best FDR control in a comprehensive simulation study. In addition to demonstrating the highest power in three real sc-multiome data analyses, scaDA successfully identifies differentially accessible regions in microglia from sc-multiome data for an Alzheimer's disease (AD) study, regions which are most enriched in GO terms related to neurogenesis, the clinical phenotype of AD, and SNPs identified in AD-associated GWAS.
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Affiliation(s)
- Fengdi Zhao
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Xin Ma
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Bing Yao
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Li Chen
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
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52
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Duan Z, Xu S, Sai Srinivasan S, Hwang A, Lee CY, Yue F, Gerstein M, Luan Y, Girgenti M, Zhang J. scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding. Brief Bioinform 2024; 25:bbae096. [PMID: 38493342 PMCID: PMC10944576 DOI: 10.1093/bib/bbae096] [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: 11/06/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 03/18/2024] Open
Abstract
Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data. First, scENCORE constructs a long-range epigenetic correlation graph to mimic chromatin interaction frequencies, where nodes and edges represent genome bins and their correlations. Then, it learns the node embeddings to cluster genome regions into A/B compartments and aligns different graphs to quantify chromatin conformation changes across conditions. Benchmarking using cell-type-matched Hi-C experiments demonstrates that scENCORE can robustly reconstruct A/B compartments in a cell-type-specific manner. Furthermore, our chromatin confirmation switching studies highlight substantial compartment-switching events that may introduce substantial regulatory and transcriptional changes in psychiatric disease. In summary, scENCORE allows accurate and cost-effective A/B compartment reconstruction to delineate higher-order chromatin structure heterogeneity in complex tissues.
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Affiliation(s)
- Ziheng Duan
- Department of Computer Science, University of California, Irvine, 92697 CA, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, 92697 CA, USA
| | | | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, 92697 CA, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, 92697 CA, USA
| | - Feng Yue
- Department of Pathology, Northwestern University, 60611 IL, USA
| | - Mark Gerstein
- Molecular Biophysics & Biochemistry, Yale, 06519 CT, USA
| | - Yu Luan
- Department of Cell Systems and Anatomy, UT Health San Antonio, 78229 TX, USA
| | - Matthew Girgenti
- Department of Psychiatry, School of Medicine, Yale, 06519 CT, USA
- Clinical Neurosciences Division, National Center for PTSD, U.S. Department of Veterans Affairs, 06477 CT, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, 92697 CA, USA
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53
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Meng Q, Wei L, Ma K, Shi M, Lin X, Ho JWK, Li Y, Zhang X. scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq. Brief Bioinform 2024; 25:bbae011. [PMID: 38324621 PMCID: PMC10849189 DOI: 10.1093/bib/bbae011] [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: 10/31/2023] [Revised: 12/18/2023] [Accepted: 01/05/2024] [Indexed: 02/09/2024] Open
Abstract
Single-cell clustered regularly interspaced short palindromic repeats-sequencing (scCRISPR-seq) is an emerging high-throughput CRISPR screening technology where the true cellular response to perturbation is coupled with infected proportion bias of guide RNAs (gRNAs) across different cell clusters. The mixing of these effects introduces noise into scCRISPR-seq data analysis and thus obstacles to relevant studies. We developed scDecouple to decouple true cellular response of perturbation from the influence of infected proportion bias. scDecouple first models the distribution of gene expression profiles in perturbed cells and then iteratively finds the maximum likelihood of cell cluster proportions as well as the cellular response for each gRNA. We demonstrated its performance in a series of simulation experiments. By applying scDecouple to real scCRISPR-seq data, we found that scDecouple enhances the identification of biologically perturbation-related genes. scDecouple can benefit scCRISPR-seq data analysis, especially in the case of heterogeneous samples or complex gRNA libraries.
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Affiliation(s)
- Qiuchen Meng
- MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Lei Wei
- MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Kun Ma
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
| | - Ming Shi
- MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xinyi Lin
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
| | - Joshua W K Ho
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
| | - Yinqing Li
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing 100084, China
- IDG-McGovern Institute for Brain Research, Center for Synthetic and Systems Biology, School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Xuegong Zhang
- MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, School of Life Sciences and School of Medicine, Tsinghua University, Beijing 100084, China
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54
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Kousnetsov R, Bourque J, Surnov A, Fallahee I, Hawiger D. Single-cell sequencing analysis within biologically relevant dimensions. Cell Syst 2024; 15:83-103.e11. [PMID: 38198894 DOI: 10.1016/j.cels.2023.12.005] [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: 12/09/2022] [Revised: 05/23/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024]
Abstract
The currently predominant approach to transcriptomic and epigenomic single-cell analysis depends on a rigid perspective constrained by reduced dimensions and algorithmically derived and annotated clusters. Here, we developed Seqtometry (sequencing-to-measurement), a single-cell analytical strategy based on biologically relevant dimensions enabled by advanced scoring with multiple gene sets (signatures) for examination of gene expression and accessibility across various organ systems. By utilizing information only in the form of specific signatures, Seqtometry bypasses unsupervised clustering and individual annotations of clusters. Instead, Seqtometry combines qualitative and quantitative cell-type identification with specific characterization of diverse biological processes under experimental or disease conditions. Comprehensive analysis by Seqtometry of various immune cells as well as other cells from different organs and disease-induced states, including multiple myeloma and Alzheimer's disease, surpasses corresponding cluster-based analytical output. We propose Seqtometry as a single-cell sequencing analysis approach applicable for both basic and clinical research.
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Affiliation(s)
- Robert Kousnetsov
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Jessica Bourque
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Alexey Surnov
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Ian Fallahee
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Daniel Hawiger
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA.
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55
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Jiang Y, Hu Z, Lynch AW, Jiang J, Zhu A, Zhang Y, Xie Y, Li R, Zhou N, Meyer CA, Cejas P, Brown M, Long HW, Qiu X. scATAnno: Automated Cell Type Annotation for single-cell ATAC Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.01.543296. [PMID: 37333088 PMCID: PMC10274707 DOI: 10.1101/2023.06.01.543296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The recent advances in single-cell epigenomic techniques have created a growing demand for scATAC-seq analysis. One key task is to determine cell types based on epigenetic profiling. We introduce scATAnno, a workflow designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow can generate scATAC-seq reference atlases from publicly available datasets, and enable accurate cell type annotation by integrating query data with reference atlases, without the aid of scRNA-seq profiling. To enhance annotation accuracy, we have incorporated KNN-based and weighted distance-based uncertainty scores to effectively detect unknown cell populations within the query data. We showcase the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cell (PBMC), basal cell carcinoma (BCC) and Triple Negative Breast Cancer (TNBC), and demonstrate that scATAnno accurately annotates cell types across conditions. Overall, scATAnno is a powerful tool for cell type annotation in scATAC-seq data and can aid in the interpretation of new scATAC-seq datasets in complex biological systems.
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56
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Xiong H, Wang Q, Li CC, He A. Single-cell joint profiling of multiple epigenetic proteins and gene transcription. SCIENCE ADVANCES 2024; 10:eadi3664. [PMID: 38170774 PMCID: PMC10796078 DOI: 10.1126/sciadv.adi3664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024]
Abstract
Sculpting the epigenome with a combination of histone modifications and transcription factor occupancy determines gene transcription and cell fate specification. Here, we first develop uCoTarget, utilizing a split-pool barcoding strategy for realizing ultrahigh-throughput single-cell joint profiling of multiple epigenetic proteins. Through extensive optimization for sensitivity and multimodality resolution, we demonstrate that uCoTarget enables simultaneous detection of five histone modifications (H3K27ac, H3K4me3, H3K4me1, H3K36me3, and H3K27me3) in 19,860 single cells. We applied uCoTarget to the in vitro generation of hematopoietic stem/progenitor cells (HSPCs) from human embryonic stem cells, presenting multimodal epigenomic profiles in 26,418 single cells. uCoTarget reveals establishment of pairing of HSPC enhancers (H3K27ac) and promoters (H3K4me3) and RUNX1 engagement priming for H3K27ac activation along the HSPC path. We then develop uCoTargetX, an expansion of uCoTarget to simultaneously measure transcriptome and multiple epigenome targets. Together, our methods enable generalizable, versatile multimodal profiles for reconstructing comprehensive epigenome and transcriptome landscapes and analyzing the regulatory interplay at single-cell level.
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Affiliation(s)
- Haiqing Xiong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
| | - Qianhao Wang
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Chen C. Li
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Aibin He
- Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
- Key laboratory of Carcinogenesis and Translational Research of Ministry of Education of China, Peking University Cancer Hospital & Institute, Peking University, Beijing 100142, China
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57
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Qian FC, Zhou LW, Zhu YB, Li YY, Yu ZM, Feng CC, Fang QL, Zhao Y, Cai FH, Wang QY, Tang HF, Li CQ. scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species. Nucleic Acids Res 2024; 52:D285-D292. [PMID: 37897340 PMCID: PMC10767920 DOI: 10.1093/nar/gkad924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/14/2023] [Accepted: 10/16/2023] [Indexed: 10/30/2023] Open
Abstract
Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.
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Affiliation(s)
- Feng-Cui Qian
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Li-Wei Zhou
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Yan-Bing Zhu
- Beijing Clinical Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yan-Yu Li
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing, 163319, China
| | - Zheng-Min Yu
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Chen-Chen Feng
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing, 163319, China
| | - Qiao-Li Fang
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Yu Zhao
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Fu-Hong Cai
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Qiu-Yu Wang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Hui-Fang Tang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Chun-Quan Li
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Maternal and Child Health Care Hospital, National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
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58
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Merkuri F, Rothstein M, Simoes-Costa M. Histone lactylation couples cellular metabolism with developmental gene regulatory networks. Nat Commun 2024; 15:90. [PMID: 38167340 PMCID: PMC10762033 DOI: 10.1038/s41467-023-44121-1] [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: 03/31/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
Embryonic cells exhibit diverse metabolic states. Recent studies have demonstrated that metabolic reprogramming drives changes in cell identity by affecting gene expression. However, the connection between cellular metabolism and gene expression remains poorly understood. Here we report that glycolysis-regulated histone lactylation couples the metabolic state of embryonic cells with chromatin organization and gene regulatory network (GRN) activation. We found that lactylation marks genomic regions of glycolytic embryonic tissues, like the neural crest (NC) and pre-somitic mesoderm. Histone lactylation occurs in the loci of NC genes as these cells upregulate glycolysis. This process promotes the accessibility of active enhancers and the deployment of the NC GRN. Reducing the deposition of the mark by targeting LDHA/B leads to the downregulation of NC genes and the impairment of cell migration. The deposition of lactyl-CoA on histones at NC enhancers is supported by a mechanism that involves transcription factors SOX9 and YAP/TEAD. These findings define an epigenetic mechanism that integrates cellular metabolism with the GRNs that orchestrate embryonic development.
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Affiliation(s)
- Fjodor Merkuri
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Megan Rothstein
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Marcos Simoes-Costa
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA.
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA.
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
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59
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Weidemann BJ, Marcheva B, Kobayashi M, Omura C, Newman MV, Kobayashi Y, Waldeck NJ, Perelis M, Lantier L, McGuinness OP, Ramsey KM, Stein RW, Bass J. Repression of latent NF-κB enhancers by PDX1 regulates β cell functional heterogeneity. Cell Metab 2024; 36:90-102.e7. [PMID: 38171340 PMCID: PMC10793877 DOI: 10.1016/j.cmet.2023.11.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 07/17/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Interactions between lineage-determining and activity-dependent transcription factors determine single-cell identity and function within multicellular tissues through incompletely known mechanisms. By assembling a single-cell atlas of chromatin state within human islets, we identified β cell subtypes governed by either high or low activity of the lineage-determining factor pancreatic duodenal homeobox-1 (PDX1). β cells with reduced PDX1 activity displayed increased chromatin accessibility at latent nuclear factor κB (NF-κB) enhancers. Pdx1 hypomorphic mice exhibited de-repression of NF-κB and impaired glucose tolerance at night. Three-dimensional analyses in tandem with chromatin immunoprecipitation (ChIP) sequencing revealed that PDX1 silences NF-κB at circadian and inflammatory enhancers through long-range chromatin contacts involving SIN3A. Conversely, Bmal1 ablation in β cells disrupted genome-wide PDX1 and NF-κB DNA binding. Finally, antagonizing the interleukin (IL)-1β receptor, an NF-κB target, improved insulin secretion in Pdx1 hypomorphic islets. Our studies reveal functional subtypes of single β cells defined by a gradient in PDX1 activity and identify NF-κB as a target for insulinotropic therapy.
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Affiliation(s)
- Benjamin J Weidemann
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Biliana Marcheva
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Mikoto Kobayashi
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Chiaki Omura
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Marsha V Newman
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Yumiko Kobayashi
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Nathan J Waldeck
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Mark Perelis
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Ionis Pharmaceuticals, Carlsbad, CA 92010, USA
| | - Louise Lantier
- Vanderbilt-NIH Mouse Metabolic Phenotyping Center, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Owen P McGuinness
- Vanderbilt-NIH Mouse Metabolic Phenotyping Center, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kathryn Moynihan Ramsey
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Roland W Stein
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Joseph Bass
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
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60
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Yekelchyk M, Li X, Guenther S, Braun T. Single-Nucleus ATAC-seq for Mapping Chromatin Accessibility in Individual Cells of Murine Hearts. Methods Mol Biol 2024; 2752:245-257. [PMID: 38194039 DOI: 10.1007/978-1-0716-3621-3_16] [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] [Indexed: 01/10/2024]
Abstract
During the last decade a wide range of single-cell and single-nucleus next-generation sequencing techniques have been developed, which revolutionized detection of rare cell populations, enabling creation of comprehensive cell atlases of complex organs and tissues. State-of-the-art methods do not only allow classical transcriptomics of individual cells but also comprise a number of epigenetic approaches, including assessment of chromatin accessibility by single-nucleus Assay for Transposase Accessible Chromatin ATAC-seq (snATAC-seq). The snATAC-seq assay detects "open chromatin," a term for low nucleosome occupancy of genomic regions, which is a prerequisite for effective transcription factor binding. Information about open chromatin at the single-nucleus level helps to recognize epigenetic changes, sometimes before transcription of respective genes occurs. snATAC-seq detects cellular heterogeneity in otherwise still transcriptionally and/or morphologically homogeneous cell populations. Chromatin accessibility assays may be used to detect epigenetic changes in cardiac lineages during heart development, chromatin landscape changes during aging, and epigenetic alterations in heart diseases. Here, we provide an optimized protocol for snATAC-seq of murine hearts. We describe isolation of single nuclei from snap-frozen hearts, provide hints for preparation of libraries suitable for snATAC-seq next-generation sequencing (NGS) using the Chromium 10× platform, and give general recommendations for downstream analysis using conventional bioinformatic pipelines and packages. The protocol should serve as a beginner's guide to generate high-quality snATAC-seq datasets and to perform chromatin accessibility analysis of individual heart-derived cell nuclei.
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Affiliation(s)
- Michail Yekelchyk
- Department of Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Xiang Li
- Department of Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Stefan Guenther
- Department of Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Thomas Braun
- Department of Cardiac Development and Remodelling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany.
- German Centre for Cardiovascular Research (DZHK), Partner site Rhein-Main, Frankfurt am Main, Germany.
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61
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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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62
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Martens LD, Fischer DS, Yépez VA, Theis FJ, Gagneur J. Modeling fragment counts improves single-cell ATAC-seq analysis. Nat Methods 2024; 21:28-31. [PMID: 38049697 PMCID: PMC10776385 DOI: 10.1038/s41592-023-02112-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 10/25/2023] [Indexed: 12/06/2023]
Abstract
Single-cell ATAC sequencing coverage in regulatory regions is typically binarized as an indicator of open chromatin. Here we show that binarization is an unnecessary step that neither improves goodness of fit, clustering, cell type identification nor batch integration. Fragment counts, but not read counts, should instead be modeled, which preserves quantitative regulatory information. These results have immediate implications for single-cell ATAC sequencing analysis.
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Affiliation(s)
- 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
| | - David S Fischer
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Vicente A Yépez
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Fabian J Theis
- 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.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
| | - Julien Gagneur
- 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.
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany.
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63
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Vrljicak P, Lucas ES, Tryfonos M, Muter J, Ott S, Brosens JJ. Dynamic chromatin remodeling in cycling human endometrium at single-cell level. Cell Rep 2023; 42:113525. [PMID: 38060448 DOI: 10.1016/j.celrep.2023.113525] [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: 06/07/2023] [Revised: 09/21/2023] [Accepted: 11/15/2023] [Indexed: 12/30/2023] Open
Abstract
Estrogen-dependent proliferation followed by progesterone-dependent differentiation of the endometrium culminates in a short implantation window. We performed single-cell assay for transposase-accessible chromatin with sequencing on endometrial samples obtained across the menstrual cycle to investigate the regulation of temporal gene networks that control embryo implantation. We identify uniquely accessible chromatin regions in all major cellular constituents of the endometrium, delineate temporal patterns of coordinated chromatin remodeling in epithelial and stromal cells, and gain mechanistic insights into the emergence of a receptive state through integrated analysis of enriched transcription factor (TF) binding sites in dynamic chromatin regions, chromatin immunoprecipitation sequencing analyses, and gene expression data. We demonstrate that the implantation window coincides with pervasive cooption of transposable elements (TEs) into the regulatory chromatin landscape of decidualizing cells and expression of TE-derived transcripts in a spatially defined manner. Our data constitute a comprehensive map of the chromatin changes that control TF activities in a cycling endometrium at cellular resolution.
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Affiliation(s)
- Pavle Vrljicak
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry CV4 7AL, UK
| | - Emma S Lucas
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK
| | - Maria Tryfonos
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK
| | - Joanne Muter
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK; Tommy's National Centre for Miscarriage Research, University Hospitals Coventry & Warwickshire NHS Trust, Coventry CV2 2DX, UK
| | - Sascha Ott
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry CV4 7AL, UK
| | - Jan J Brosens
- Warwick Medical School, Division of Biomedical Sciences, University of Warwick, Coventry CV2 2DX, UK; Tommy's National Centre for Miscarriage Research, University Hospitals Coventry & Warwickshire NHS Trust, Coventry CV2 2DX, UK.
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64
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Lu X, Luo Y, Nie X, Zhang B, Wang X, Li R, Liu G, Zhou Q, Liu Z, Fan L, Hotaling JM, Zhang Z, Bo H, Guo J. Single-cell multi-omics analysis of human testicular germ cell tumor reveals its molecular features and microenvironment. Nat Commun 2023; 14:8462. [PMID: 38123589 PMCID: PMC10733385 DOI: 10.1038/s41467-023-44305-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
Seminoma is the most common malignant solid tumor in 14 to 44 year-old men. However, its molecular features and tumor microenvironment (TME) is largely unexplored. Here, we perform a series of studies via genomics profiling (single cell multi-omics and spatial transcriptomics) and functional examination using seminoma samples and a seminoma cell line. We identify key gene expression programs share between seminoma and primordial germ cells, and further characterize the functions of TFAP2C in promoting tumor invasion and migration. We also identify 15 immune cell subtypes in TME, and find that subtypes with exhaustion features were located closer to the tumor region through combined spatial transcriptome analysis. Furthermore, we identify key pathways and genes that may facilitate seminoma disseminating beyond the seminiferous tubules. These findings advance our knowledge of seminoma tumorigenesis and produce a multi-omics atlas of in situ human seminoma microenvironment, which could help discover potential therapy targets for seminoma.
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Affiliation(s)
- Xiaojian Lu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yanwei Luo
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Xichen Nie
- Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Bailing Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoyan Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Ran Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Guangmin Liu
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Qianyin Zhou
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Zhizhong Liu
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Liqing Fan
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, Hunan, China
| | - James M Hotaling
- Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Zhe Zhang
- Department of Urology, Peking University Third Hospital, Beijing, China.
- Center for Reproductive Medicine, Peking University Third Hospital, Beijing, China.
| | - Hao Bo
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China.
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, Hunan, China.
| | - Jingtao Guo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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65
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Liu D, Fu Y, Wang X, Wang X, Fang X, Zhou Y, Wang R, Zhang P, Jiang M, Jia D, Wang J, Chen H, Guo G, Han X. Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses. Stem Cell Reports 2023; 18:2464-2481. [PMID: 37995704 PMCID: PMC10724075 DOI: 10.1016/j.stemcr.2023.10.018] [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: 03/13/2023] [Revised: 10/24/2023] [Accepted: 10/26/2023] [Indexed: 11/25/2023] Open
Abstract
In vivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the in vivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.
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Affiliation(s)
- Daiyuan Liu
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Yuting Fu
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Xinru Wang
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Xueyi Wang
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Xing Fang
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, Zhejiang 310058, China
| | - Yincong Zhou
- College of Life Sciences, Zhejiang University, Hangzhou 310058, China
| | - Renying Wang
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Peijing Zhang
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, Zhejiang 310058, China
| | - Mengmeng Jiang
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
| | - Danmei Jia
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
| | - Jingjing Wang
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
| | - Haide Chen
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China; M20 Genomics, Hangzhou, China
| | - Guoji Guo
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, Zhejiang 310058, China; Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
| | - Xiaoping Han
- Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, Zhejiang 310058, China.
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66
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Lambo S, Trinh DL, Ries RE, Jin D, Setiadi A, Ng M, Leblanc VG, Loken MR, Brodersen LE, Dai F, Pardo LM, Ma X, Vercauteren SM, Meshinchi S, Marra MA. A longitudinal single-cell atlas of treatment response in pediatric AML. Cancer Cell 2023; 41:2117-2135.e12. [PMID: 37977148 DOI: 10.1016/j.ccell.2023.10.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/15/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023]
Abstract
Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse. At diagnosis, cellular composition differed between genetic subgroups. Upon relapse, cellular hierarchies transitioned toward a more primitive state regardless of subtype. Primitive cells in the relapsed tumor were distinct compared to cells at diagnosis, with under-representation of myeloid transcriptional programs and over-representation of other lineage programs. In some patients, this was accompanied by the appearance of a B-lymphoid-like hierarchy. Our data thus reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potentially targetable processes.
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Affiliation(s)
- Sander Lambo
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Diane L Trinh
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Rhonda E Ries
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Dan Jin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Audi Setiadi
- British Columbia Children's Hospital Research Institute, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, Division of Hematopathology, Children's and Women's Health Centre of British Columbia, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Michelle Ng
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada; Department of Medical Genetics and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Veronique G Leblanc
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | | | | | - Fangyan Dai
- Hematologics, Incorporated, Seattle, WA, USA
| | | | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Suzanne M Vercauteren
- British Columbia Children's Hospital Research Institute, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, Division of Hematopathology, Children's and Women's Health Centre of British Columbia, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Soheil Meshinchi
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Marco A Marra
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada; Department of Medical Genetics and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
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67
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Booth GT, Daza RM, Srivatsan SR, McFaline-Figueroa JL, Gladden RG, Mullen AC, Furlan SN, Shendure J, Trapnell C. High-capacity sample multiplexing for single cell chromatin accessibility profiling. BMC Genomics 2023; 24:737. [PMID: 38049719 PMCID: PMC10696879 DOI: 10.1186/s12864-023-09832-1] [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: 05/16/2023] [Accepted: 11/22/2023] [Indexed: 12/06/2023] Open
Abstract
Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.
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Affiliation(s)
- Gregory T Booth
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Sanjay R Srivatsan
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - José L McFaline-Figueroa
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA
| | - Rula Green Gladden
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Andrew C Mullen
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Scott N Furlan
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
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68
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Ahuja P, Yadav R, Goyal S, Yadav C, Ranga S, Kadian L. Targeting epigenetic deregulations for the management of esophageal carcinoma: recent advances and emerging approaches. Cell Biol Toxicol 2023; 39:2437-2465. [PMID: 37338772 DOI: 10.1007/s10565-023-09818-5] [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: 03/16/2023] [Accepted: 06/08/2023] [Indexed: 06/21/2023]
Abstract
Ranking from seventh in incidence to sixth in mortality, esophageal carcinoma is considered a severe malignancy of food pipe. Later-stage diagnosis, drug resistance, and a high mortality rate contribute to its lethality. Esophageal squamous cell carcinoma and esophageal adenocarcinoma are the two main histological subtypes of esophageal carcinoma, with squamous cell carcinoma alone accounting for more than eighty percent of its cases. While genetic anomalies are well known in esophageal cancer, accountability of epigenetic deregulations is also being explored for the recent two decades. DNA methylation, histone modifications, and functional non-coding RNAs are the crucial epigenetic players involved in the modulation of different malignancies, including esophageal carcinoma. Targeting these epigenetic aberrations will provide new insights into the development of biomarker tools for risk stratification, early diagnosis, and effective therapeutic intervention. This review discusses different epigenetic alterations, emphasizing the most significant developments in esophageal cancer epigenetics and their potential implication for the detection, prognosis, and treatment of esophageal carcinoma. Further, the preclinical and clinical status of various epigenetic drugs has also been reviewed.
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Affiliation(s)
- Parul Ahuja
- Department of Genetics, Maharshi Dayanand University, (Haryana), Rohtak, 124001, India
| | - Ritu Yadav
- Department of Genetics, Maharshi Dayanand University, (Haryana), Rohtak, 124001, India.
| | - Sandeep Goyal
- Department of Internal Medicine, Pt. B.D, Sharma University of Health Sciences, (Haryana), Rohtak, 124001, India
| | - Chetna Yadav
- Department of Genetics, Maharshi Dayanand University, (Haryana), Rohtak, 124001, India
| | - Shalu Ranga
- Department of Genetics, Maharshi Dayanand University, (Haryana), Rohtak, 124001, India
| | - Lokesh Kadian
- Department of Dermatology, School of Medicine, Indiana University, Indianapolis, Indiana, 46202, USA
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69
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Janin M, Davalos V, Esteller M. Cancer metastasis under the magnifying glass of epigenetics and epitranscriptomics. Cancer Metastasis Rev 2023; 42:1071-1112. [PMID: 37369946 PMCID: PMC10713773 DOI: 10.1007/s10555-023-10120-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023]
Abstract
Most of the cancer-associated mortality and morbidity can be attributed to metastasis. The role of epigenetic and epitranscriptomic alterations in cancer origin and progression has been extensively demonstrated during the last years. Both regulations share similar mechanisms driven by DNA or RNA modifiers, namely writers, readers, and erasers; enzymes responsible of respectively introducing, recognizing, or removing the epigenetic or epitranscriptomic modifications. Epigenetic regulation is achieved by DNA methylation, histone modifications, non-coding RNAs, chromatin accessibility, and enhancer reprogramming. In parallel, regulation at RNA level, named epitranscriptomic, is driven by a wide diversity of chemical modifications in mostly all RNA molecules. These two-layer regulatory mechanisms are finely controlled in normal tissue, and dysregulations are associated with every hallmark of human cancer. In this review, we provide an overview of the current state of knowledge regarding epigenetic and epitranscriptomic alterations governing tumor metastasis, and compare pathways regulated at DNA or RNA levels to shed light on a possible epi-crosstalk in cancer metastasis. A deeper understanding on these mechanisms could have important clinical implications for the prevention of advanced malignancies and the management of the disseminated diseases. Additionally, as these epi-alterations can potentially be reversed by small molecules or inhibitors against epi-modifiers, novel therapeutic alternatives could be envisioned.
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Affiliation(s)
- Maxime Janin
- Cancer Epigenetics Group, Josep Carreras Leukaemia Research Institute (IJC), IJC Building, Germans Trias I Pujol, Ctra de Can Ruti, Cami de Les Escoles S/N, 08916 Badalona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red Cancer (CIBERONC), Madrid, Spain
| | - Veronica Davalos
- Cancer Epigenetics Group, Josep Carreras Leukaemia Research Institute (IJC), IJC Building, Germans Trias I Pujol, Ctra de Can Ruti, Cami de Les Escoles S/N, 08916 Badalona, Barcelona, Spain
| | - Manel Esteller
- Cancer Epigenetics Group, Josep Carreras Leukaemia Research Institute (IJC), IJC Building, Germans Trias I Pujol, Ctra de Can Ruti, Cami de Les Escoles S/N, 08916 Badalona, Barcelona, Spain.
- Centro de Investigacion Biomedica en Red Cancer (CIBERONC), Madrid, Spain.
- Institucio Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Catalonia, Spain.
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Catalonia, Spain.
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70
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Amarasinghe SL, Yang P, Voogd O, Yang H, Du MM, Su S, Brown D, Jabbari J, Bowden R, Ritchie M. scPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor. NAR Genom Bioinform 2023; 5:lqad105. [PMID: 38046273 PMCID: PMC10689045 DOI: 10.1093/nargab/lqad105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 11/23/2023] [Indexed: 12/05/2023] Open
Abstract
scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify 'true' cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.
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Affiliation(s)
- Shanika L Amarasinghe
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- The Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, 3800, Australia
| | - Phil Yang
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Oliver Voogd
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Haoyu Yang
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Mei R M Du
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Shian Su
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
| | - Daniel V Brown
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Jafar S Jabbari
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Rory Bowden
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Matthew E Ritchie
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia
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71
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Lareau C. Subtle cell states resolved in single-cell data. Nat Biotechnol 2023; 41:1690-1691. [PMID: 37198441 PMCID: PMC10654257 DOI: 10.1038/s41587-023-01797-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Affiliation(s)
- Caleb Lareau
- Department of Pathology, Stanford University, Palo Alto, CA, USA.
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72
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Craig AJ, Silveira MAD, Ma L, Revsine M, Wang L, Heinrich S, Rae Z, Ruchinskas A, Dadkhah K, Do W, Behrens S, Mehrabadi FR, Dominguez DA, Forgues M, Budhu A, Chaisaingmongkol J, Hernandez JM, Davis JL, Tran B, Marquardt JU, Ruchirawat M, Kelly M, Greten TF, Wang XW. Genome-wide profiling of transcription factor activity in primary liver cancer using single-cell ATAC sequencing. Cell Rep 2023; 42:113446. [PMID: 37980571 PMCID: PMC10750269 DOI: 10.1016/j.celrep.2023.113446] [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: 05/21/2023] [Revised: 09/24/2023] [Accepted: 10/31/2023] [Indexed: 11/21/2023] Open
Abstract
Primary liver cancer (PLC) consists of two main histological subtypes; hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). The role of transcription factors (TFs) in malignant hepatobiliary lineage commitment between HCC and iCCA remains underexplored. Here, we present genome-wide profiling of transcription regulatory elements of 16 PLC patients using single-cell assay for transposase accessible chromatin sequencing. Single-cell open chromatin profiles reflect the compositional diversity of liver cancer, identifying both malignant and microenvironment component cells. TF motif enrichment levels of 31 TFs strongly discriminate HCC from iCCA tumors. These TFs are members of the nuclear/retinoid receptor, POU, or ETS motif families. POU factors are associated with prognostic features in iCCA. Overall, nuclear receptors, ETS and POU TF motif families delineate transcription regulation between HCC and iCCA tumors, which may be relevant to development and selection of PLC subtype-specific therapeutics.
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Affiliation(s)
- Amanda J Craig
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Maruhen A Datsch Silveira
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Lichun Ma
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Mahler Revsine
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Limin Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Sophia Heinrich
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Department of Gastroenterology, Hepatology, Infectious Diseases and Endocrinology, Hanover Medical School, 30159 Hanover, Germany
| | - Zachary Rae
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 20701, USA
| | - Allison Ruchinskas
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 20701, USA
| | - Kimia Dadkhah
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 20701, USA
| | - Whitney Do
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Shay Behrens
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Surgical Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Farid R Mehrabadi
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Dana A Dominguez
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Department of Surgical Oncology, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Marshonna Forgues
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Anuradha Budhu
- Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jittiporn Chaisaingmongkol
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology, Office of Higher Education Commission, Ministry of Higher Education, Science, Research and Innovation, Bangkok 10400, Thailand
| | - Jonathan M Hernandez
- Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Surgical Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jeremy L Davis
- Surgical Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Bao Tran
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 20701, USA
| | - Jens U Marquardt
- Department of Medicine I, University of Lübeck, 23552 Lübeck, Germany
| | - Mathuros Ruchirawat
- Laboratory of Chemical Carcinogenesis, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology, Office of Higher Education Commission, Ministry of Higher Education, Science, Research and Innovation, Bangkok 10400, Thailand
| | - Michael Kelly
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 20701, USA
| | - Tim F Greten
- Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA
| | - Xin W Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA; Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
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73
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Blanco-Carmona E, Narayanan A, Hernandez I, Nieto JC, Elosua-Bayes M, Sun X, Schmidt C, Pamir N, Özduman K, Herold-Mende C, Pagani F, Cominelli M, Taranda J, Wick W, von Deimling A, Poliani PL, Rehli M, Schlesner M, Heyn H, Turcan Ş. Tumor heterogeneity and tumor-microglia interactions in primary and recurrent IDH1-mutant gliomas. Cell Rep Med 2023; 4:101249. [PMID: 37883975 PMCID: PMC10694621 DOI: 10.1016/j.xcrm.2023.101249] [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: 09/19/2022] [Revised: 08/06/2023] [Accepted: 09/27/2023] [Indexed: 10/28/2023]
Abstract
The isocitrate dehydrogenase (IDH) gene is recurrently mutated in adult diffuse gliomas. IDH-mutant gliomas are categorized into oligodendrogliomas and astrocytomas, each with unique pathological features. Here, we use single-nucleus RNA and ATAC sequencing to compare the molecular heterogeneity of these glioma subtypes. In addition to astrocyte-like, oligodendrocyte progenitor-like, and cycling tumor subpopulations, a tumor population enriched for ribosomal genes and translation elongation factors is primarily present in oligodendrogliomas. Longitudinal analysis of astrocytomas indicates that the proportion of tumor subpopulations remains stable in recurrent tumors. Analysis of tumor-associated microglia/macrophages (TAMs) reveals significant differences between oligodendrogliomas, with astrocytomas harboring inflammatory TAMs expressing phosphorylated STAT1, as confirmed by immunohistochemistry. Furthermore, inferred receptor-ligand interactions between tumor subpopulations and TAMs may contribute to TAM state diversity. Overall, our study sheds light on distinct tumor populations, TAM heterogeneity, TAM-tumor interactions in IDH-mutant glioma subtypes, and the relative stability of tumor subpopulations in recurrent astrocytomas.
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Affiliation(s)
- Enrique Blanco-Carmona
- Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany; Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Ashwin Narayanan
- Neurology Clinic and National Center for Tumor Diseases, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany
| | - Inmaculada Hernandez
- Next Generation Sequencing Core, Leibniz Institute for Immunotherapy, c/o University Hospital Regensburg, Regensburg, Germany; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Juan C Nieto
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Marc Elosua-Bayes
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Xueyuan Sun
- Neurology Clinic and National Center for Tumor Diseases, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany; DKTK CCU Neurooncology, DKFZ, Heidelberg, Germany
| | - Claudia Schmidt
- Core Facility Unit Light Microscopy, DKFZ, Heidelberg, Germany
| | - Necmettin Pamir
- Acıbadem Mehmet Ali Aydınlar University, School of Medicine, Department of Neurosurgery, Istanbul, Turkey
| | - Koray Özduman
- Acıbadem Mehmet Ali Aydınlar University, School of Medicine, Department of Neurosurgery, Istanbul, Turkey
| | - Christel Herold-Mende
- Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Francesca Pagani
- Pathology Unit, Department of Molecular and Translational Medicine, University of Brescia Medical School, Brescia, Italy
| | - Manuela Cominelli
- Pathology Unit, Department of Molecular and Translational Medicine, University of Brescia Medical School, Brescia, Italy
| | - Julian Taranda
- Neurology Clinic and National Center for Tumor Diseases, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany; DKTK CCU Neurooncology, DKFZ, Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic and National Center for Tumor Diseases, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany; DKTK CCU Neurooncology, DKFZ, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, Heidelberg University Hospital, and DKTK CCU Neuropathology, DKFZ, Heidelberg, Germany
| | - Pietro Luigi Poliani
- Pathology Unit, Department of Molecular and Translational Medicine, University of Brescia Medical School, Brescia, Italy
| | - Michael Rehli
- Next Generation Sequencing Core, Leibniz Institute for Immunotherapy, c/o University Hospital Regensburg, Regensburg, Germany; Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Matthias Schlesner
- Biomedical Informatics, Data Mining and Data Analytics, Faculty for Applied Informatics, University of Augsburg, Augsburg, Germany
| | - Holger Heyn
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain.
| | - Şevin Turcan
- Neurology Clinic and National Center for Tumor Diseases, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany; DKTK CCU Neurooncology, DKFZ, Heidelberg, Germany.
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74
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Martín-Zamora FM, Davies BE, Donnellan RD, Guynes K, Martín-Durán JM. Functional genomics in Spiralia. Brief Funct Genomics 2023; 22:487-497. [PMID: 37981859 PMCID: PMC10658182 DOI: 10.1093/bfgp/elad036] [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: 05/10/2023] [Revised: 07/12/2023] [Accepted: 07/25/2023] [Indexed: 11/21/2023] Open
Abstract
Our understanding of the mechanisms that modulate gene expression in animals is strongly biased by studying a handful of model species that mainly belong to three groups: Insecta, Nematoda and Vertebrata. However, over half of the animal phyla belong to Spiralia, a morphologically and ecologically diverse animal clade with many species of economic and biomedical importance. Therefore, investigating genome regulation in this group is central to uncovering ancestral and derived features in genome functioning in animals, which can also be of significant societal impact. Here, we focus on five aspects of gene expression regulation to review our current knowledge of functional genomics in Spiralia. Although some fields, such as single-cell transcriptomics, are becoming more common, the study of chromatin accessibility, DNA methylation, histone post-translational modifications and genome architecture are still in their infancy. Recent efforts to generate chromosome-scale reference genome assemblies for greater species diversity and optimise state-of-the-art approaches for emerging spiralian research systems will address the existing knowledge gaps in functional genomics in this animal group.
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Affiliation(s)
- Francisco M Martín-Zamora
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Billie E Davies
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Rory D Donnellan
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Kero Guynes
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - José M Martín-Durán
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
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75
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Wei Y, Davenport TC, Collora JA, Ma HK, Pinto-Santini D, Lama J, Alfaro R, Duerr A, Ho YC. Single-cell epigenetic, transcriptional, and protein profiling of latent and active HIV-1 reservoir revealed that IKZF3 promotes HIV-1 persistence. Immunity 2023; 56:2584-2601.e7. [PMID: 37922905 PMCID: PMC10843106 DOI: 10.1016/j.immuni.2023.10.002] [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: 03/22/2023] [Revised: 06/26/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023]
Abstract
Understanding how HIV-1-infected cells proliferate and persist is key to HIV-1 eradication, but the heterogeneity and rarity of HIV-1-infected cells hamper mechanistic interrogations. Here, we used single-cell DOGMA-seq to simultaneously capture transcription factor accessibility, transcriptome, surface proteins, HIV-1 DNA, and HIV-1 RNA in memory CD4+ T cells from six people living with HIV-1 during viremia and after suppressive antiretroviral therapy. We identified increased transcription factor accessibility in latent HIV-1-infected cells (RORC) and transcriptionally active HIV-1-infected cells (interferon regulatory transcription factor [IRF] and activator protein 1 [AP-1]). A proliferation program (IKZF3, IL21, BIRC5, and MKI67 co-expression) promoted the survival of transcriptionally active HIV-1-infected cells. Both latent and transcriptionally active HIV-1-infected cells had increased IKZF3 (Aiolos) expression. Distinct epigenetic programs drove the heterogeneous cellular states of HIV-1-infected cells: IRF:activation, Eomes:cytotoxic effector differentiation, AP-1:migration, and cell death. Our study revealed the single-cell epigenetic, transcriptional, and protein states of latent and transcriptionally active HIV-1-infected cells and cellular programs promoting HIV-1 persistence.
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Affiliation(s)
- Yulong Wei
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Timothy C Davenport
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Jack A Collora
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Haocong Katherine Ma
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Delia Pinto-Santini
- Vaccine and Infectious Disease, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Javier Lama
- Asociación Civil Impacta Salud y Educación, Lima 15063, Perú
| | - Ricardo Alfaro
- Centro de Investigaciones Tecnológicas Biomédicas y Medioambientales (CITBM), Lima 07006, Perú
| | - Ann Duerr
- Vaccine and Infectious Disease, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Ya-Chi Ho
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT 06519, USA.
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76
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Rajbhandari N, Hamilton M, Quintero CM, Ferguson LP, Fox R, Schürch CM, Wang J, Nakamura M, Lytle NK, McDermott M, Diaz E, Pettit H, Kritzik M, Han H, Cridebring D, Wen KW, Tsai S, Goggins MG, Lowy AM, Wechsler-Reya RJ, Von Hoff DD, Newman AM, Reya T. Single-cell mapping identifies MSI + cells as a common origin for diverse subtypes of pancreatic cancer. Cancer Cell 2023; 41:1989-2005.e9. [PMID: 37802055 PMCID: PMC10836835 DOI: 10.1016/j.ccell.2023.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 06/12/2023] [Accepted: 09/08/2023] [Indexed: 10/08/2023]
Abstract
Identifying the cells from which cancers arise is critical for understanding the molecular underpinnings of tumor evolution. To determine whether stem/progenitor cells can serve as cells of origin, we created a Msi2-CreERT2 knock-in mouse. When crossed to CAG-LSL-MycT58A mice, Msi2-CreERT2 mice developed multiple pancreatic cancer subtypes: ductal, acinar, adenosquamous, and rare anaplastic tumors. Combining single-cell genomics with computational analysis of developmental states and lineage trajectories, we demonstrate that MYC preferentially triggers transformation of the most immature MSI2+ pancreas cells into multi-lineage pre-cancer cells. These pre-cancer cells subsequently diverge to establish pancreatic cancer subtypes by activating distinct transcriptional programs and large-scale genomic changes, and enforced expression of specific signals like Ras can redirect subtype specification. This study shows that multiple pancreatic cancer subtypes can arise from a common pool of MSI2+ cells and provides a powerful model to understand and control the programs that shape divergent fates in pancreatic cancer.
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Affiliation(s)
- Nirakar Rajbhandari
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Michael Hamilton
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Cynthia M Quintero
- Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York City, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA
| | - L Paige Ferguson
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Raymond Fox
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Christian M Schürch
- Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany
| | - Jun Wang
- Tumor Initiation and Maintenance Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Mari Nakamura
- Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York City, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA
| | - Nikki K Lytle
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Matthew McDermott
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Emily Diaz
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Hannah Pettit
- Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York City, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA
| | - Marcie Kritzik
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA; Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York City, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA
| | - Haiyong Han
- Molecular Medicine Division, The Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Derek Cridebring
- Molecular Medicine Division, The Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Kwun Wah Wen
- Department of Pathology, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Susan Tsai
- Department of Surgery, The Medical College of Wisconsin, Milwaukee, WI, USA
| | - Michael G Goggins
- Departments of Pathology, Medicine and Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Andrew M Lowy
- Department of Surgery, Division of Surgical Oncology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Robert J Wechsler-Reya
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA; Tumor Initiation and Maintenance Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA; Rady Children's Institute for Genomic Medicine, San Diego, CA, USA; Department of Neurology, Columbia University Medical Center, New York City, NY, USA
| | - Daniel D Von Hoff
- Molecular Medicine Division, The Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Aaron M Newman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Tannishtha Reya
- Departments of Pharmacology and Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, CA, USA; Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York City, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York City, NY, USA.
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77
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Kim YI, O'Rourke R, Sagerström CG. scMultiome analysis identifies embryonic hindbrain progenitors with mixed rhombomere identities. eLife 2023; 12:e87772. [PMID: 37947350 PMCID: PMC10662952 DOI: 10.7554/elife.87772] [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: 03/16/2023] [Accepted: 11/09/2023] [Indexed: 11/12/2023] Open
Abstract
Rhombomeres serve to position neural progenitors in the embryonic hindbrain, thereby ensuring appropriate neural circuit formation, but the molecular identities of individual rhombomeres and the mechanism whereby they form has not been fully established. Here, we apply scMultiome analysis in zebrafish to molecularly resolve all rhombomeres for the first time. We find that rhombomeres become molecularly distinct between 10hpf (end of gastrulation) and 13hpf (early segmentation). While the embryonic hindbrain transiently contains alternating odd- versus even-type rhombomeres, our scMultiome analyses do not detect extensive odd versus even molecular characteristics in the early hindbrain. Instead, we find that each rhombomere displays a unique gene expression and chromatin profile. Prior to the appearance of distinct rhombomeres, we detect three hindbrain progenitor clusters (PHPDs) that correlate with the earliest visually observed segments in the hindbrain primordium that represent prospective rhombomere r2/r3 (possibly including r1), r4, and r5/r6, respectively. We further find that the PHPDs form in response to Fgf and RA morphogens and that individual PHPD cells co-express markers of multiple mature rhombomeres. We propose that the PHPDs contain mixed-identity progenitors and that their subdivision into individual rhombomeres requires the resolution of mixed transcription and chromatin states.
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Affiliation(s)
- Yong-Il Kim
- Section of Developmental Biology, Department of Pediatrics, University of Colorado Medical SchoolAuroraUnited States
| | - Rebecca O'Rourke
- Section of Developmental Biology, Department of Pediatrics, University of Colorado Medical SchoolAuroraUnited States
| | - Charles G Sagerström
- Section of Developmental Biology, Department of Pediatrics, University of Colorado Medical SchoolAuroraUnited States
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78
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Poos AM, Prokoph N, Przybilla MJ, Mallm JP, Steiger S, Seufert I, John L, Tirier SM, Bauer K, Baumann A, Rohleder J, Munawar U, Rasche L, Kortüm KM, Giesen N, Reichert P, Huhn S, Müller-Tidow C, Goldschmidt H, Stegle O, Raab MS, Rippe K, Weinhold N. Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis. Blood 2023; 142:1633-1646. [PMID: 37390336 PMCID: PMC10733835 DOI: 10.1182/blood.2023019758] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.
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Affiliation(s)
- Alexandra M. Poos
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Nina Prokoph
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Moritz J. Przybilla
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
| | - Jan-Philipp Mallm
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Simon Steiger
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Isabelle Seufert
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Lukas John
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Stephan M. Tirier
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Katharina Bauer
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Anja Baumann
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Jennifer Rohleder
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Umair Munawar
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Leo Rasche
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
- Mildred Scheel Early Career Center, University Hospital of Würzburg, Würzburg, Germany
| | - K. Martin Kortüm
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Nicola Giesen
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Philipp Reichert
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Stefanie Huhn
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- National Center for Tumor Diseases, Heidelberg, Germany
| | - Hartmut Goldschmidt
- Department of Internal Medicine V, GMMG-Study Group at University Hospital Heidelberg, Heidelberg, Germany
| | - Oliver Stegle
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Marc S. Raab
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Niels Weinhold
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
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79
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Tang L, Huang ZP, Mei H, Hu Y. Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer. Mil Med Res 2023; 10:52. [PMID: 37941075 PMCID: PMC10631149 DOI: 10.1186/s40779-023-00486-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/10/2023] [Indexed: 11/10/2023] Open
Abstract
Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.
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Affiliation(s)
- Lu Tang
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China
| | - Zhong-Pei Huang
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China
| | - Heng Mei
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China.
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China.
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Yu Hu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China.
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China.
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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80
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Phillips RA, Wan E, Tuscher JJ, Reid D, Drake OR, Ianov L, Day JJ. Temporally specific gene expression and chromatin remodeling programs regulate a conserved Pdyn enhancer. eLife 2023; 12:RP89993. [PMID: 37938195 PMCID: PMC10631760 DOI: 10.7554/elife.89993] [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: 11/09/2023] Open
Abstract
Neuronal and behavioral adaptations to novel stimuli are regulated by temporally dynamic waves of transcriptional activity, which shape neuronal function and guide enduring plasticity. Neuronal activation promotes expression of an immediate early gene (IEG) program comprised primarily of activity-dependent transcription factors, which are thought to regulate a second set of late response genes (LRGs). However, while the mechanisms governing IEG activation have been well studied, the molecular interplay between IEGs and LRGs remain poorly characterized. Here, we used transcriptomic and chromatin accessibility profiling to define activity-driven responses in rat striatal neurons. As expected, neuronal depolarization generated robust changes in gene expression, with early changes (1 hr) enriched for inducible transcription factors and later changes (4 hr) enriched for neuropeptides, synaptic proteins, and ion channels. Remarkably, while depolarization did not induce chromatin remodeling after 1 hr, we found broad increases in chromatin accessibility at thousands of sites in the genome at 4 hr after neuronal stimulation. These putative regulatory elements were found almost exclusively at non-coding regions of the genome, and harbored consensus motifs for numerous activity-dependent transcription factors such as AP-1. Furthermore, blocking protein synthesis prevented activity-dependent chromatin remodeling, suggesting that IEG proteins are required for this process. Targeted analysis of LRG loci identified a putative enhancer upstream of Pdyn (prodynorphin), a gene encoding an opioid neuropeptide implicated in motivated behavior and neuropsychiatric disease states. CRISPR-based functional assays demonstrated that this enhancer is both necessary and sufficient for Pdyn transcription. This regulatory element is also conserved at the human PDYN locus, where its activation is sufficient to drive PDYN transcription in human cells. These results suggest that IEGs participate in chromatin remodeling at enhancers and identify a conserved enhancer that may act as a therapeutic target for brain disorders involving dysregulation of Pdyn.
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Affiliation(s)
- Robert A Phillips
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
| | - Ethan Wan
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
| | - Jennifer J Tuscher
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
| | - David Reid
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
| | - Olivia R Drake
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
| | - Lara Ianov
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
- Civitan International Research Center, University of Alabama at BirminghamBirminghamUnited States
| | - Jeremy J Day
- Department of Neurobiology, University of Alabama at BirminghamBirminghamUnited States
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81
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Doan A, Mueller KP, Chen A, Rouin GT, Daniel B, Lattin J, Chen Y, Mozarsky B, Markovska M, Arias-Umana J, Hapke R, Jung I, Xu P, Klysz D, Bashti M, Quinn PJ, Sandor K, Zhang W, Hall J, Lareau C, Grupp SA, Fraietta JA, Sotillo E, Satpathy AT, Mackall CL, Weber EW. FOXO1 is a master regulator of CAR T memory programming. RESEARCH SQUARE 2023:rs.3.rs-2802998. [PMID: 37986944 PMCID: PMC10659532 DOI: 10.21203/rs.3.rs-2802998/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Poor CAR T persistence limits CAR T cell therapies for B cell malignancies and solid tumors1,2. The expression of memory-associated genes such as TCF7 (protein name TCF1) is linked to response and long-term persistence in patients3-7, thereby implicating memory programs in therapeutic efficacy. Here, we demonstrate that the pioneer transcription factor, FOXO1, is responsible for promoting memory programs and restraining exhaustion in human CAR T cells. Pharmacologic inhibition or gene editing of endogenous FOXO1 in human CAR T cells diminished the expression of memory-associated genes, promoted an exhaustion-like phenotype, and impaired antitumor activity in vitro and in vivo. FOXO1 overexpression induced a gene expression program consistent with T cell memory and increased chromatin accessibility at FOXO1 binding motifs. FOXO1-overexpressing cells retained function, memory potential, and metabolic fitness during settings of chronic stimulation and exhibited enhanced persistence and antitumor activity in vivo. In contrast, TCF1 overexpression failed to enforce canonical memory programs or enhance CAR T cell potency. Importantly, endogenous FOXO1 activity correlated with CAR T and TIL responses in patients, underscoring its clinical relevance in cancer immunotherapy. Our results demonstrate that memory reprogramming through FOXO1 can enhance the persistence and potency of human CAR T cells and highlights the utility of pioneer factors, which bind condensed chromatin and induce local epigenetic remodeling, for optimizing therapeutic T cell states.
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Affiliation(s)
- Alexander Doan
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Katherine P Mueller
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andy Chen
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
| | - Geoffrey T Rouin
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Cell and Molecular Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bence Daniel
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305, USA
| | - John Lattin
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yingshi Chen
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Brett Mozarsky
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Martina Markovska
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jose Arias-Umana
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Cell and Molecular Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Robert Hapke
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Cell and Molecular Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Inyoung Jung
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Peng Xu
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Dorota Klysz
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Malek Bashti
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Patrick J Quinn
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Katalin Sandor
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
| | - Wenxi Zhang
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Junior Hall
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Caleb Lareau
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94129 USA
| | - Stephan A Grupp
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joseph A Fraietta
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Elena Sotillo
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ansuman T Satpathy
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94129 USA
| | - Crystal L Mackall
- Center for Cancer Cell Therapy, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94129 USA
- Division of Hematology, Oncology, Stem Cell Transplantation and Regenerative Medicine, Department of Pediatrics, Stanford University, Stanford, CA 94305, USA
- Division of Blood and Marrow Transplantation and Cell Therapy, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Evan W Weber
- Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94129 USA
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82
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Zhou JL, de Guglielmo G, Ho AJ, Kallupi M, Pokhrel N, Li HR, Chitre AS, Munro D, Mohammadi P, Carrette LLG, George O, Palmer AA, McVicker G, Telese F. Single-nucleus genomics in outbred rats with divergent cocaine addiction-like behaviors reveals changes in amygdala GABAergic inhibition. Nat Neurosci 2023; 26:1868-1879. [PMID: 37798411 PMCID: PMC10620093 DOI: 10.1038/s41593-023-01452-y] [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: 09/03/2022] [Accepted: 09/06/2023] [Indexed: 10/07/2023]
Abstract
The amygdala processes positive and negative valence and contributes to addiction, but the cell-type-specific gene regulatory programs involved are unknown. We generated an atlas of single-nucleus gene expression and chromatin accessibility in the amygdala of outbred rats with high and low cocaine addiction-like behaviors following prolonged abstinence. Differentially expressed genes between the high and low groups were enriched for energy metabolism across cell types. Rats with high addiction index (AI) showed increased relapse-like behaviors and GABAergic transmission in the amygdala. Both phenotypes were reversed by pharmacological inhibition of the glyoxalase 1 enzyme, which metabolizes methylglyoxal-a GABAA receptor agonist produced by glycolysis. Differences in chromatin accessibility between high and low AI rats implicated pioneer transcription factors in the basic helix-loop-helix, FOX, SOX and activator protein 1 families. We observed opposite regulation of chromatin accessibility across many cell types. Most notably, excitatory neurons had greater accessibility in high AI rats and inhibitory neurons had greater accessibility in low AI rats.
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Affiliation(s)
- Jessica L Zhou
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Aaron J Ho
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Marsida Kallupi
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Narayan Pokhrel
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Hai-Ri Li
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Daniel Munro
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Pejman Mohammadi
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Olivier George
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Graham McVicker
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Francesca Telese
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
- Department of Medicine, University of California San Diego, La Jolla, CA, USA.
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83
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Derrien J, Gastineau S, Frigout A, Giordano N, Cherkaoui M, Gaborit V, Boinon R, Douillard E, Devic M, Magrangeas F, Moreau P, Minvielle S, Touzeau C, Letouzé E. Acquired resistance to a GPRC5D-directed T-cell engager in multiple myeloma is mediated by genetic or epigenetic target inactivation. NATURE CANCER 2023; 4:1536-1543. [PMID: 37653140 DOI: 10.1038/s43018-023-00625-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/28/2023] [Indexed: 09/02/2023]
Abstract
Bispecific antibodies targeting GPRC5D demonstrated promising efficacy in multiple myeloma, but acquired resistance usually occurs within a few months. Using a single-nucleus multi-omic strategy in three patients from the MYRACLE cohort (ClinicalTrials.gov registration: NCT03807128 ), we identified two resistance mechanisms, by bi-allelic genetic inactivation of GPRC5D or by long-range epigenetic silencing of its promoter and enhancer regions. Molecular profiling of target genes may help to guide the choice of immunotherapy and early detection of resistance in multiple myeloma.
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Affiliation(s)
- Jennifer Derrien
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Sarah Gastineau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Antoine Frigout
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Nils Giordano
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Mia Cherkaoui
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Victor Gaborit
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Rémi Boinon
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Elise Douillard
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Magali Devic
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Florence Magrangeas
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Philippe Moreau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- Hematology Department, University Hospital Hôtel-Dieu, Nantes, France
| | - Stéphane Minvielle
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Cyrille Touzeau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- Hematology Department, University Hospital Hôtel-Dieu, Nantes, France
| | - Eric Letouzé
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France.
- University Hospital Hôtel-Dieu, Nantes, France.
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84
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Patruno L, Milite S, Bergamin R, Calonaci N, D’Onofrio A, Anselmi F, Antoniotti M, Graudenzi A, Caravagna G. A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing. PLoS Comput Biol 2023; 19:e1011557. [PMID: 37917660 PMCID: PMC10645363 DOI: 10.1371/journal.pcbi.1011557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/14/2023] [Accepted: 09/30/2023] [Indexed: 11/04/2023] Open
Abstract
Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.
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Affiliation(s)
- Lucrezia Patruno
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Salvatore Milite
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
- Centre for Computational Biology, Human Technopole, Milan, Italy
| | - Riccardo Bergamin
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Nicola Calonaci
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Alberto D’Onofrio
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Fabio Anselmi
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Marco Antoniotti
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- B4—Bicocca Bioinformatics Biostatistics and Bioimaging Centre, Università degli Studi di Milano-Bicocca, Milan, Italy
| | - Alex Graudenzi
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- B4—Bicocca Bioinformatics Biostatistics and Bioimaging Centre, Università degli Studi di Milano-Bicocca, Milan, Italy
| | - Giulio Caravagna
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
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85
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Shi W, Ye J, Shi Z, Pan C, Zhang Q, Lin Y, Liang D, Liu Y, Lin X, Zheng Y. Single-cell chromatin accessibility and transcriptomic characterization of Behcet's disease. Commun Biol 2023; 6:1048. [PMID: 37848613 PMCID: PMC10582193 DOI: 10.1038/s42003-023-05420-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 10/04/2023] [Indexed: 10/19/2023] Open
Abstract
Behect's disease is a chronic vasculitis characterized by complex multi-organ immune aberrations. However, a comprehensive understanding of the gene-regulatory profile of peripheral autoimmunity and the diverse immune responses across distinct cell types in Behcet's disease (BD) is still lacking. Here, we present a multi-omic single-cell study of 424,817 cells in BD patients and non-BD individuals. This study maps chromatin accessibility and gene expression in the same biological samples, unraveling vast cellular heterogeneity. We identify widespread cell-type-specific, disease-associated active and pro-inflammatory immunity in both transcript and epigenomic aspects. Notably, integrative multi-omic analysis reveals putative TF regulators that might contribute to chromatin accessibility and gene expression in BD. Moreover, we predicted gene-regulatory networks within nominated TF activators, including AP-1, NF-kB, and ETS transcript factor families, which may regulate cellular interaction and govern inflammation. Our study illustrates the epigenetic and transcriptional landscape in BD peripheral blood and expands understanding of potential epigenomic immunopathology in this disease.
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Affiliation(s)
- Wen Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China
| | - Jinguo Ye
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Zhuoxing Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Caineng Pan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Qikai Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Yuheng Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China
| | - Dan Liang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
| | - Yizhi Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
| | - Xianchai Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
| | - Yingfeng Zheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, 510060, Guangzhou, China.
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, 100085, Beijing, China.
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86
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Chen S, Jiang W, Du Y, Yang M, Pan Y, Li H, Cui M. Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy. Front Genet 2023; 14:1276959. [PMID: 37900181 PMCID: PMC10602688 DOI: 10.3389/fgene.2023.1276959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.
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Affiliation(s)
- Siyuan Chen
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Weibo Jiang
- Department of Orthopaedic, The Second Hospital of Jilin University, Changchun, China
| | - Yanhui Du
- Department of Orthopaedics, Jilin Province People’s Hospital, Changchun, China
| | - Manshi Yang
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Yihan Pan
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Huan Li
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Mengying Cui
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
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87
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Hu Y, Shen F, Yang X, Han T, Long Z, Wen J, Huang J, Shen J, Guo Q. Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity. Clin Epigenetics 2023; 15:161. [PMID: 37821906 PMCID: PMC10568863 DOI: 10.1186/s13148-023-01574-x] [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: 07/16/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies. RESULTS The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development. CONCLUSION This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.
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Affiliation(s)
- Yuhua Hu
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Feng Shen
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Department of Neurosurgery, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Xi Yang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Tingting Han
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Zhuowen Long
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Jiale Wen
- Graduate School, Dalian Medical University, Dalian, 116044, Liaoning, China
- Department of Cardiology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Junxing Huang
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
| | - Jiangfeng Shen
- Department of Thoracic Surgery, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
| | - Qing Guo
- Department of Oncology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China.
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88
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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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89
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Luo J, Deng M, Zhang X, Sun X. ESICCC as a systematic computational framework for evaluation, selection, and integration of cell-cell communication inference methods. Genome Res 2023; 33:1788-1805. [PMID: 37827697 PMCID: PMC10691505 DOI: 10.1101/gr.278001.123] [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: 04/22/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023]
Abstract
Cell-cell communication (CCC) is critical for determining cell fates and functions in multicellular organisms. With the advent of single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST), an increasing number of CCC inference methods have been developed. Nevertheless, a thorough comparison of their performances is yet to be conducted. To fill this gap, we developed a systematic benchmark framework called ESICCC to evaluate 18 ligand-receptor (LR) inference methods and five ligand/receptor-target inference methods using a total of 116 data sets, including 15 ST data sets, 15 sets of cell line perturbation data, two sets of cell type-specific expression/proteomics data, and 84 sets of sampled or unsampled scRNA-seq data. We evaluated and compared the agreement, accuracy, robustness, and usability of these methods. Regarding accuracy evaluation, RNAMagnet, CellChat, and scSeqComm emerge as the three best-performing methods for intercellular ligand-receptor inference based on scRNA-seq data, whereas stMLnet and HoloNet are the best methods for predicting ligand/receptor-target regulation using ST data. To facilitate the practical applications, we provide a decision-tree-style guideline for users to easily choose best tools for their specific research concerns in CCC inference, and develop an ensemble pipeline CCCbank that enables versatile combinations of methods and databases. Moreover, our comparative results also uncover several critical influential factors for CCC inference, such as prior interaction information, ligand-receptor scoring algorithm, intracellular signaling complexity, and spatial relationship, which may be considered in the future studies to advance the development of new methodologies.
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Affiliation(s)
- Jiaxin Luo
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China
| | - Minghua Deng
- School of Mathematical Sciences, Peking University, Beijing, 100871, China
| | - Xuegong Zhang
- Bioinformatics Division of BNRIST and Department of Automation, MOE Key Lab of Bioinformatics, Tsinghua University, Beijing, 100084, China
| | - Xiaoqiang Sun
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China;
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90
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Goswami S, Raychaudhuri D, Singh P, Natarajan SM, Chen Y, Poon C, Hennessey M, Tannir AJ, Zhang J, Anandhan S, Kerrigan BP, Macaluso MD, He Z, Jindal S, Lang FF, Basu S, Sharma P. Myeloid-specific KDM6B inhibition sensitizes glioblastoma to PD1 blockade. NATURE CANCER 2023; 4:1455-1473. [PMID: 37653141 DOI: 10.1038/s43018-023-00620-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 07/21/2023] [Indexed: 09/02/2023]
Abstract
Glioblastoma (GBM) tumors are enriched in immune-suppressive myeloid cells and are refractory to immune checkpoint therapy (ICT). Targeting epigenetic pathways to reprogram the functional phenotype of immune-suppressive myeloid cells to overcome resistance to ICT remains unexplored. Single-cell and spatial transcriptomic analyses of human GBM tumors demonstrated high expression of an epigenetic enzyme-histone 3 lysine 27 demethylase (KDM6B)-in intratumoral immune-suppressive myeloid cell subsets. Importantly, myeloid cell-specific Kdm6b deletion enhanced proinflammatory pathways and improved survival in GBM tumor-bearing mice. Mechanistic studies showed that the absence of Kdm6b enhances antigen presentation, interferon response and phagocytosis in myeloid cells by inhibition of mediators of immune suppression including Mafb, Socs3 and Sirpa. Further, pharmacological inhibition of KDM6B mirrored the functional phenotype of Kdm6b-deleted myeloid cells and enhanced anti-PD1 efficacy. This study thus identified KDM6B as an epigenetic regulator of the functional phenotype of myeloid cell subsets and a potential therapeutic target for enhanced response to ICT.
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Affiliation(s)
- Sangeeta Goswami
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- James P. Allison Institute, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Deblina Raychaudhuri
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Pratishtha Singh
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Seanu Meena Natarajan
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yulong Chen
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Candice Poon
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mercedes Hennessey
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Aminah J Tannir
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jan Zhang
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Swetha Anandhan
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Marc D Macaluso
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhong He
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sonali Jindal
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Frederick F Lang
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sreyashi Basu
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Padmanee Sharma
- Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- James P. Allison Institute, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Immunotherapy Platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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91
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Shi Q, Chen X, Zhang Z. Decoding Human Biology and Disease Using Single-cell Omics Technologies. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:926-949. [PMID: 37739168 PMCID: PMC10928380 DOI: 10.1016/j.gpb.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/22/2023] [Accepted: 06/08/2023] [Indexed: 09/24/2023]
Abstract
Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.
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Affiliation(s)
- Qiang Shi
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Xueyan Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Changping Laboratory, Beijing 102206, China.
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92
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Baysoy A, Bai Z, Satija R, Fan R. The technological landscape and applications of single-cell multi-omics. Nat Rev Mol Cell Biol 2023; 24:695-713. [PMID: 37280296 PMCID: PMC10242609 DOI: 10.1038/s41580-023-00615-w] [Citation(s) in RCA: 80] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2023] [Indexed: 06/08/2023]
Abstract
Single-cell multi-omics technologies and methods characterize cell states and activities by simultaneously integrating various single-modality omics methods that profile the transcriptome, genome, epigenome, epitranscriptome, proteome, metabolome and other (emerging) omics. Collectively, these methods are revolutionizing molecular cell biology research. In this comprehensive Review, we discuss established multi-omics technologies as well as cutting-edge and state-of-the-art methods in the field. We discuss how multi-omics technologies have been adapted and improved over the past decade using a framework characterized by optimization of throughput and resolution, modality integration, uniqueness and accuracy, and we also discuss multi-omics limitations. We highlight the impact that single-cell multi-omics technologies have had in cell lineage tracing, tissue-specific and cell-specific atlas production, tumour immunology and cancer genetics, and in mapping of cellular spatial information in fundamental and translational research. Finally, we discuss bioinformatics tools that have been developed to link different omics modalities and elucidate functionality through the use of better mathematical modelling and computational methods.
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Affiliation(s)
- Alev Baysoy
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Zhiliang Bai
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Rahul Satija
- New York Genome Center, New York, NY, USA
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
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93
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Sun N, Victor MB, Park YP, Xiong X, Scannail AN, Leary N, Prosper S, Viswanathan S, Luna X, Boix CA, James BT, Tanigawa Y, Galani K, Mathys H, Jiang X, Ng AP, Bennett DA, Tsai LH, Kellis M. Human microglial state dynamics in Alzheimer's disease progression. Cell 2023; 186:4386-4403.e29. [PMID: 37774678 PMCID: PMC10644954 DOI: 10.1016/j.cell.2023.08.037] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 03/21/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer's disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution.
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Affiliation(s)
- Na Sun
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yongjin P Park
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Pathology and Laboratory Medicine, Department of Statistics, University of British Columbia, Vancouver, BC, Canada; Department of Molecular Oncology, BC Cancer, Vancouver, BC, Canada
| | - Xushen Xiong
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aine Ni Scannail
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Noelle Leary
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Shaniah Prosper
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Soujanya Viswanathan
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Xochitl Luna
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Carles A Boix
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin T James
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yosuke Tanigawa
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kyriaki Galani
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hansruedi Mathys
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Xueqiao Jiang
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ayesha P Ng
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Li-Huei Tsai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Manolis Kellis
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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94
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Long E, Yin J, Shin JH, Li Y, Kane A, Patel H, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi MT, Rothman N, Lan Q, Chang YS, Yu F, Amos C, Shi J, Lee JG, Kim EY, Choi J. Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559336. [PMID: 37808664 PMCID: PMC10557605 DOI: 10.1101/2023.09.25.559336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.
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Affiliation(s)
- Erping Long
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Current affiliation: Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ju Hye Shin
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yuyan Li
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Alexander Kane
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thong Luong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jun Xia
- Department of Biomedical Sciences, Creighton University, Omaha, NE, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yoon Soo Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Fulong Yu
- Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Christopher Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jin Gu Lee
- Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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95
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Han X, Xu X, Yang C, Liu G. Microfluidic design in single-cell sequencing and application to cancer precision medicine. CELL REPORTS METHODS 2023; 3:100591. [PMID: 37725985 PMCID: PMC10545941 DOI: 10.1016/j.crmeth.2023.100591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/01/2023] [Accepted: 08/24/2023] [Indexed: 09/21/2023]
Abstract
Single-cell sequencing (SCS) is a crucial tool to reveal the genetic and functional heterogeneity of tumors, providing unique insights into the clonal evolution, microenvironment, drug resistance, and metastatic progression of cancers. Microfluidics is a critical component of many SCS technologies and workflows, conferring advantages in throughput, economy, and automation. Here, we review the current landscape of microfluidic architectures and sequencing techniques for single-cell omics analysis and highlight how these have enabled recent applications in oncology research. We also discuss the challenges and the promise of microfluidics-based single-cell analysis in the future of precision oncology.
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Affiliation(s)
- Xin Han
- CUHK(SZ)-Boyalife Joint Laboratory of Regenerative Medicine Engineering, Biomedical Engineering Programme, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Ciechanover Institute of Precision and Regenerative Medicine, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China
| | - Xing Xu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P.R. China; Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related 12 Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, P.R. China
| | - Chaoyang Yang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P.R. China; Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related 12 Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, P.R. China.
| | - Guozhen Liu
- CUHK(SZ)-Boyalife Joint Laboratory of Regenerative Medicine Engineering, Biomedical Engineering Programme, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Ciechanover Institute of Precision and Regenerative Medicine, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
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96
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Li W, Xiang B, Yang F, Rong Y, Yin Y, Yao J, Zhang H. scMHNN: a novel hypergraph neural network for integrative analysis of single-cell epigenomic, transcriptomic and proteomic data. Brief Bioinform 2023; 24:bbad391. [PMID: 37930028 DOI: 10.1093/bib/bbad391] [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: 07/24/2023] [Revised: 09/09/2023] [Accepted: 10/11/2023] [Indexed: 11/07/2023] Open
Abstract
Technological advances have now made it possible to simultaneously profile the changes of epigenomic, transcriptomic and proteomic at the single cell level, allowing a more unified view of cellular phenotypes and heterogeneities. However, current computational tools for single-cell multi-omics data integration are mainly tailored for bi-modality data, so new tools are urgently needed to integrate tri-modality data with complex associations. To this end, we develop scMHNN to integrate single-cell multi-omics data based on hypergraph neural network. After modeling the complex data associations among various modalities, scMHNN performs message passing process on the multi-omics hypergraph, which can capture the high-order data relationships and integrate the multiple heterogeneous features. Followingly, scMHNN learns discriminative cell representation via a dual-contrastive loss in self-supervised manner. Based on the pretrained hypergraph encoder, we further introduce the pre-training and fine-tuning paradigm, which allows more accurate cell-type annotation with only a small number of labeled cells as reference. Benchmarking results on real and simulated single-cell tri-modality datasets indicate that scMHNN outperforms other competing methods on both cell clustering and cell-type annotation tasks. In addition, we also demonstrate scMHNN facilitates various downstream tasks, such as cell marker detection and enrichment analysis.
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Affiliation(s)
- Wei Li
- College of Artificial Intelligence, Nankai University, Tongyan Road, 300350 Tianjin, China
- AI Lab, Tencent, Gaoxin 9th South Road, 518000 Shenzhen, China
| | - Bin Xiang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Yueyang Road, 200031 Shanghai, China
| | - Fan Yang
- AI Lab, Tencent, Gaoxin 9th South Road, 518000 Shenzhen, China
| | - Yu Rong
- AI Lab, Tencent, Gaoxin 9th South Road, 518000 Shenzhen, China
| | - Yanbin Yin
- Department of Food Science and Technology, University of Nebraska - Lincoln, 1400 R Street, 68588 Nebraska, USA
| | - Jianhua Yao
- AI Lab, Tencent, Gaoxin 9th South Road, 518000 Shenzhen, China
| | - Han Zhang
- College of Artificial Intelligence, Nankai University, Tongyan Road, 300350 Tianjin, China
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97
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Ramakrishnan A, Symeonidi A, Hanel P, Schmid KT, Richter ML, Schubert M, Colomé-Tatché M. epiAneufinder identifies copy number alterations from single-cell ATAC-seq data. Nat Commun 2023; 14:5846. [PMID: 37730813 PMCID: PMC10511508 DOI: 10.1038/s41467-023-41076-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/23/2023] [Indexed: 09/22/2023] Open
Abstract
Single-cell open chromatin profiling via scATAC-seq has become a mainstream measurement of open chromatin in single-cells. Here we present epiAneufinder, an algorithm that exploits the read count information from scATAC-seq data to extract genome-wide copy number alterations (CNAs) for individual cells, allowing the study of CNA heterogeneity present in a sample at the single-cell level. Using different cancer scATAC-seq datasets, we show that epiAneufinder can identify intratumor clonal heterogeneity in populations of single cells based on their CNA profiles. We demonstrate that these profiles are concordant with the ones inferred from single-cell whole genome sequencing data for the same samples. EpiAneufinder allows the inference of single-cell CNA information from scATAC-seq data, without the need of additional experiments, unlocking a layer of genomic variation which is otherwise unexplored.
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Affiliation(s)
- Akshaya Ramakrishnan
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Aikaterini Symeonidi
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.
| | - Patrick Hanel
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany
| | - Katharina T Schmid
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany
| | - Maria L Richter
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany
| | - Michael Schubert
- Oncode Institute, Division of Cell Biology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, the Netherlands
| | - Maria Colomé-Tatché
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.
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98
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Athaya T, Ripan RC, Li X, Hu H. Multimodal deep learning approaches for single-cell multi-omics data integration. Brief Bioinform 2023; 24:bbad313. [PMID: 37651607 PMCID: PMC10516349 DOI: 10.1093/bib/bbad313] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/23/2023] [Accepted: 07/18/2023] [Indexed: 09/02/2023] Open
Abstract
Integrating single-cell multi-omics data is a challenging task that has led to new insights into complex cellular systems. Various computational methods have been proposed to effectively integrate these rapidly accumulating datasets, including deep learning. However, despite the proven success of deep learning in integrating multi-omics data and its better performance over classical computational methods, there has been no systematic study of its application to single-cell multi-omics data integration. To fill this gap, we conducted a literature review to explore the use of multimodal deep learning techniques in single-cell multi-omics data integration, taking into account recent studies from multiple perspectives. Specifically, we first summarized different modalities found in single-cell multi-omics data. We then reviewed current deep learning techniques for processing multimodal data and categorized deep learning-based integration methods for single-cell multi-omics data according to data modality, deep learning architecture, fusion strategy, key tasks and downstream analysis. Finally, we provided insights into using these deep learning models to integrate multi-omics data and better understand single-cell biological mechanisms.
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Affiliation(s)
- Tasbiraha Athaya
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
| | - Rony Chowdhury Ripan
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
| | - Xiaoman Li
- Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, Florida, United States of America
| | - Haiyan Hu
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
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99
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Li J, Jaiswal MK, Chien JF, Kozlenkov A, Jung J, Zhou P, Gardashli M, Pregent LJ, Engelberg-Cook E, Dickson DW, Belzil VV, Mukamel EA, Dracheva S. Divergent single cell transcriptome and epigenome alterations in ALS and FTD patients with C9orf72 mutation. Nat Commun 2023; 14:5714. [PMID: 37714849 PMCID: PMC10504300 DOI: 10.1038/s41467-023-41033-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 08/21/2023] [Indexed: 09/17/2023] Open
Abstract
A repeat expansion in the C9orf72 (C9) gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here we investigate single nucleus transcriptomics (snRNA-seq) and epigenomics (snATAC-seq) in postmortem motor and frontal cortices from C9-ALS, C9-FTD, and control donors. C9-ALS donors present pervasive alterations of gene expression with concordant changes in chromatin accessibility and histone modifications. The greatest alterations occur in upper and deep layer excitatory neurons, as well as in astrocytes. In neurons, the changes imply an increase in proteostasis, metabolism, and protein expression pathways, alongside a decrease in neuronal function. In astrocytes, the alterations suggest activation and structural remodeling. Conversely, C9-FTD donors have fewer high-quality neuronal nuclei in the frontal cortex and numerous gene expression changes in glial cells. These findings highlight a context-dependent molecular disruption in C9-ALS and C9-FTD, indicating unique effects across cell types, brain regions, and diseases.
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Affiliation(s)
- Junhao Li
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, 92037, US
| | - Manoj K Jaiswal
- Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, US
| | - Jo-Fan Chien
- Department of Physics, University of California San Diego, La Jolla, CA, 92037, US
| | - Alexey Kozlenkov
- Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, US
| | - Jinyoung Jung
- Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, US
| | - Ping Zhou
- Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, US
| | | | - Luc J Pregent
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, US
| | | | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, US
| | | | - Eran A Mukamel
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, 92037, US.
| | - Stella Dracheva
- Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, US.
- Research & Development and VISN2 MIREC, James J, Peters VA Medical Center, Bronx, NY, 10468, US.
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100
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Feng W, Liu S, Deng Q, Fu S, Yang Y, Dai X, Wang S, Wang Y, Liu Y, Lin X, Pan X, Hao S, Yuan Y, Gu Y, Zhang X, Li H, Liu L, Liu C, Fei JF, Wei X. A scATAC-seq atlas of chromatin accessibility in axolotl brain regions. Sci Data 2023; 10:627. [PMID: 37709774 PMCID: PMC10502032 DOI: 10.1038/s41597-023-02533-0] [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: 05/18/2023] [Accepted: 09/01/2023] [Indexed: 09/16/2023] Open
Abstract
Axolotl (Ambystoma mexicanum) is an excellent model for investigating regeneration, the interaction between regenerative and developmental processes, comparative genomics, and evolution. The brain, which serves as the material basis of consciousness, learning, memory, and behavior, is the most complex and advanced organ in axolotl. The modulation of transcription factors is a crucial aspect in determining the function of diverse regions within the brain. There is, however, no comprehensive understanding of the gene regulatory network of axolotl brain regions. Here, we utilized single-cell ATAC sequencing to generate the chromatin accessibility landscapes of 81,199 cells from the olfactory bulb, telencephalon, diencephalon and mesencephalon, hypothalamus and pituitary, and the rhombencephalon. Based on these data, we identified key transcription factors specific to distinct cell types and compared cell type functions across brain regions. Our results provide a foundation for comprehensive analysis of gene regulatory programs, which are valuable for future studies of axolotl brain development, regeneration, and evolution, as well as on the mechanisms underlying cell-type diversity in vertebrate brains.
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Affiliation(s)
- Weimin Feng
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Shuai Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Qiuting Deng
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Sulei Fu
- Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Yunzhi Yang
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Xi Dai
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Shuai Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Yijin Wang
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Yang Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Xiumei Lin
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Xiangyu Pan
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovsacular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Shijie Hao
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Yue Yuan
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Ying Gu
- BGI-Shenzhen, Shenzhen, 518103, China
| | | | - Hanbo Li
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI-Qingdao, Qingdao, 266555, China
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, 266555, China
| | - Longqi Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | | | - Ji-Feng Fei
- Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China.
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China.
- School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
| | - Xiaoyu Wei
- BGI-Hangzhou, Hangzhou, 310012, China.
- BGI-Shenzhen, Shenzhen, 518103, China.
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