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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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Wang J, Liang Y, Xu C, Gao J, Tong J, Shi L. The heterogeneity of erythroid cells: insight at the single-cell transcriptome level. Cell Tissue Res 2024:10.1007/s00441-024-03903-9. [PMID: 38953986 DOI: 10.1007/s00441-024-03903-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.
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Affiliation(s)
- Jingwei Wang
- 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
| | - Yipeng Liang
- 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
| | - Changlu Xu
- 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
| | - Jie Gao
- 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
| | - Jingyuan Tong
- 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.
| | - Lihong Shi
- 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.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
- CAMS Center for Stem Cell Medicine, PUMC Department of Stem Cell and Regenerative Medicine, Tianjin, 300020, China.
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3
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Long Q, Zhang P, Ou Y, Li W, Yan Q, Yuan X. Single-cell sequencing advances in research on mesenchymal stem/stromal cells. Hum Cell 2024; 37:904-916. [PMID: 38743204 DOI: 10.1007/s13577-024-01076-9] [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: 02/29/2024] [Accepted: 05/04/2024] [Indexed: 05/16/2024]
Abstract
Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.
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Affiliation(s)
- Qingxi Long
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Pingshu Zhang
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China
| | - Ya Ou
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China
| | - Wen Li
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Qi Yan
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Xiaodong Yuan
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China.
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China.
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4
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Nishide M, Shimagami H, Kumanogoh A. Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice. Nat Rev Immunol 2024:10.1038/s41577-024-01043-3. [PMID: 38914790 DOI: 10.1038/s41577-024-01043-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/08/2024] [Indexed: 06/26/2024]
Abstract
Since the advent of single-cell RNA sequencing (scRNA-seq) methodology, single-cell analysis has become a powerful tool for exploration of cellular networks and dysregulated immune responses in disease pathogenesis. Advanced bioinformatics tools have enabled the combined analysis of scRNA-seq data and information on various cell properties, such as cell surface molecular profiles, chromatin accessibility and spatial information, leading to a deeper understanding of pathology. This Review provides an overview of the achievements in single-cell analysis applied to clinical samples of rheumatic and allergic diseases, including rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, allergic airway diseases and atopic dermatitis, with an expanded scope beyond peripheral blood cells to include local diseased tissues. Despite the valuable insights that single-cell analysis has provided into disease pathogenesis, challenges remain in translating single-cell findings into clinical practice and developing personalized treatment strategies. Beyond understanding the atlas of cellular diversity, we discuss the application of data obtained in each study to clinical practice, with a focus on identifying biomarkers and therapeutic targets.
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Affiliation(s)
- Masayuki Nishide
- Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
- Department of Immunopathology, World Premier International Research Center Initiative (WPI), Immunology Frontier Research Center (IFReC), Osaka University, Suita, Osaka, Japan.
- Department of Advanced Clinical and Translational Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
| | - Hiroshi Shimagami
- Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
- Department of Immunopathology, World Premier International Research Center Initiative (WPI), Immunology Frontier Research Center (IFReC), Osaka University, Suita, Osaka, Japan
- Department of Advanced Clinical and Translational Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
- Department of Immunopathology, World Premier International Research Center Initiative (WPI), Immunology Frontier Research Center (IFReC), Osaka University, Suita, Osaka, Japan.
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, Osaka, Japan.
- Center for Infectious Diseases for Education and Research (CiDER), Osaka University, Suita, Osaka, Japan.
- Center for Advanced Modalities and DDS (CAMaD), Osaka University, Suita, Osaka, Japan.
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5
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Duhan L, Kumari D, Naime M, Parmar VS, Chhillar AK, Dangi M, Pasrija R. Single-cell transcriptomics: background, technologies, applications, and challenges. Mol Biol Rep 2024; 51:600. [PMID: 38689046 DOI: 10.1007/s11033-024-09553-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: 02/09/2024] [Accepted: 04/15/2024] [Indexed: 05/02/2024]
Abstract
Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.
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Affiliation(s)
- Lucky Duhan
- Department of Biochemistry, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
| | - Deepika Kumari
- Department of Biochemistry, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
| | - Mohammad Naime
- Central Research Institute of Unani Medicine (Under Central Council for Research in Unani Medicine, Ministry of Ayush, Govt of India), Uttar Pradesh, Lucknow, India
| | - Virinder S Parmar
- CUNY-Graduate Center and Departments of Chemistry, Nanoscience Program, City College & Medgar Evers College, The City University of New York, 1638 Bedford Avenue, Brooklyn, NY, 11225, USA
- Institute of Click Chemistry Research and Studies, Amity University, Noida, Uttar Pradesh, 201303, India
| | - Anil K Chhillar
- Centre for Biotechnology, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
| | - Mehak Dangi
- Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
| | - Ritu Pasrija
- Department of Biochemistry, Maharshi Dayanand University, Rohtak, Haryana, 124001, India.
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Yin K, Zhao M, Xu Y, Zheng Z, Huang S, Liang D, Dong H, Guo Y, Lin L, Song J, Zhang H, Zheng J, Zhu Z, Yang C. Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes. Anal Chem 2024; 96:6301-6310. [PMID: 38597061 DOI: 10.1021/acs.analchem.3c05785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.
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Affiliation(s)
- Kun Yin
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, 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 Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Meijuan Zhao
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Yiling Xu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Zhong Zheng
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Shanqing Huang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Dianyi Liang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - He Dong
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Ye Guo
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Li Lin
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Jia Song
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Huimin Zhang
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
| | - Junhua Zheng
- Institute of Molecular Medicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Zhi Zhu
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China
| | - Chaoyong Yang
- State Key Laboratory of Physical Chemistry of Solid Surfaces, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, Collaborative Innovation Center of Chemistry for Energy Materials, 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 Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, China
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7
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Yagishita H, Go Y, Okamoto K, Arimura N, Ikegaya Y, Sasaki T. A method to analyze gene expression profiles from hippocampal neurons electrophysiologically recorded in vivo. Front Neurosci 2024; 18:1360432. [PMID: 38694898 PMCID: PMC11061373 DOI: 10.3389/fnins.2024.1360432] [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: 12/23/2023] [Accepted: 03/26/2024] [Indexed: 05/04/2024] Open
Abstract
Hippocampal pyramidal neurons exhibit diverse spike patterns and gene expression profiles. However, their relationships with single neurons are not fully understood. In this study, we designed an electrophysiology-based experimental procedure to identify gene expression profiles using RNA sequencing of single hippocampal pyramidal neurons whose spike patterns were recorded in living mice. This technique involves a sequence of experiments consisting of in vivo juxtacellular recording and labeling, brain slicing, cell collection, and transcriptome analysis. We demonstrated that the expression levels of a subset of genes in individual hippocampal pyramidal neurons were significantly correlated with their spike burstiness, submillisecond-level spike rise times or spike rates, directly measured by in vivo electrophysiological recordings. Because this methodological approach can be applied across a wide range of brain regions, it is expected to contribute to studies on various neuronal heterogeneities to understand how physiological spike patterns are associated with gene expression profiles.
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Affiliation(s)
- Haruya Yagishita
- Department of Pharmacology, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, Japan
- Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Yasuhiro Go
- Graduate School of Information Science, University of Hyogo, Hyogo, Japan
- Department of System Neuroscience, Division of Behavioral Development, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Aichi, Japan
- Cognitive Genomics Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Aichi, Japan
| | - Kazuki Okamoto
- Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
- Department of Neuroanatomy, Graduate School of Medicine, Juntendo University, Tokyo, Japan
- Department of Cell Biology and Neuroscience, Graduate School of Medicine, Juntendo University, Bunkyo, Tokyo, Japan
| | - Nariko Arimura
- Department of Pharmacology, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, Japan
| | - Yuji Ikegaya
- Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Institute for AI and Beyond, The University of Tokyo, Tokyo, Japan
| | - Takuya Sasaki
- Department of Pharmacology, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, Japan
- Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
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8
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Nakamura T, Yoshihara T, Tanegashima C, Kadota M, Kobayashi Y, Honda K, Ishiwata M, Ueda J, Hara T, Nakanishi M, Takumi T, Itohara S, Kuraku S, Asano M, Kasahara T, Nakajima K, Tsuboi T, Takata A, Kato T. Transcriptomic dysregulation and autistic-like behaviors in Kmt2c haploinsufficient mice rescued by an LSD1 inhibitor. Mol Psychiatry 2024:10.1038/s41380-024-02479-8. [PMID: 38528071 DOI: 10.1038/s41380-024-02479-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 03/27/2024]
Abstract
Recent studies have consistently demonstrated that the regulation of chromatin and gene transcription plays a pivotal role in the pathogenesis of neurodevelopmental disorders. Among many genes involved in these pathways, KMT2C, encoding one of the six known histone H3 lysine 4 (H3K4) methyltransferases in humans and rodents, was identified as a gene whose heterozygous loss-of-function variants are causally associated with autism spectrum disorder (ASD) and the Kleefstra syndrome phenotypic spectrum. However, little is known about how KMT2C haploinsufficiency causes neurodevelopmental deficits and how these conditions can be treated. To address this, we developed and analyzed genetically engineered mice with a heterozygous frameshift mutation of Kmt2c (Kmt2c+/fs mice) as a disease model with high etiological validity. In a series of behavioral analyses, the mutant mice exhibit autistic-like behaviors such as impairments in sociality, flexibility, and working memory, demonstrating their face validity as an ASD model. To investigate the molecular basis of the observed abnormalities, we performed a transcriptomic analysis of their bulk adult brains and found that ASD risk genes were specifically enriched in the upregulated differentially expressed genes (DEGs), whereas KMT2C peaks detected by ChIP-seq were significantly co-localized with the downregulated genes, suggesting an important role of putative indirect effects of Kmt2c haploinsufficiency. We further performed single-cell RNA sequencing of newborn mouse brains to obtain cell type-resolved insights at an earlier stage. By integrating findings from ASD exome sequencing, genome-wide association, and postmortem brain studies to characterize DEGs in each cell cluster, we found strong ASD-associated transcriptomic changes in radial glia and immature neurons with no obvious bias toward upregulated or downregulated DEGs. On the other hand, there was no significant gross change in the cellular composition. Lastly, we explored potential therapeutic agents and demonstrate that vafidemstat, a lysine-specific histone demethylase 1 (LSD1) inhibitor that was effective in other models of neuropsychiatric/neurodevelopmental disorders, ameliorates impairments in sociality but not working memory in adult Kmt2c+/fs mice. Intriguingly, the administration of vafidemstat was shown to alter the vast majority of DEGs in the direction to normalize the transcriptomic abnormalities in the mutant mice (94.3 and 82.5% of the significant upregulated and downregulated DEGs, respectively, P < 2.2 × 10-16, binomial test), which could be the molecular mechanism underlying the behavioral rescuing. In summary, our study expands the repertoire of ASD models with high etiological and face validity, elucidates the cell-type resolved molecular alterations due to Kmt2c haploinsufficiency, and demonstrates the efficacy of an LSD1 inhibitor that might be generalizable to multiple categories of psychiatric disorders along with a better understanding of its presumed mechanisms of action.
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Affiliation(s)
- Takumi Nakamura
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Department of Psychiatry and Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Toru Yoshihara
- Institute of Laboratory Animals, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Chiharu Tanegashima
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Hyogo, Japan
| | - Mitsutaka Kadota
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Hyogo, Japan
| | - Yuki Kobayashi
- Laboratory for Behavioral Genetics, RIKEN Center for Brain Science, Saitama, Japan
| | - Kurara Honda
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, Saitama, Japan
| | - Mizuho Ishiwata
- Department of Psychiatry and Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan
| | - Junko Ueda
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan
| | - Tomonori Hara
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Department of Organ Anatomy, Tohoku University Graduate School of Medicine, Miyagi, Japan
| | - Moe Nakanishi
- Laboratory for Mental Biology, RIKEN Center for Brain Science, Saitama, Japan
- Laboratory for Molecular Mechanism of Brain Development, RIKEN Center for Brain Science, Saitama, Japan
| | - Toru Takumi
- Laboratory for Mental Biology, RIKEN Center for Brain Science, Saitama, Japan
- Department of Physiology and Cell Biology, Kobe University School of Medicine, Hyogo, Japan
| | - Shigeyoshi Itohara
- Laboratory for Behavioral Genetics, RIKEN Center for Brain Science, Saitama, Japan
| | - Shigehiro Kuraku
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Hyogo, Japan
- Molecular Life History Laboratory, Department of Genomics and Evolutionary Biology, National Institute of Genetics, Shizuoka, Japan
- Department of Genetics, SOKENDAI (Graduate University for Advanced Studies), Shizuoka, Japan
| | - Masahide Asano
- Institute of Laboratory Animals, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takaoki Kasahara
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Institute of Biology and Environmental Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Kazuo Nakajima
- Department of Psychiatry and Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan
- Department of Physiology, Teikyo University School of Medicine, Tokyo, Japan
| | - Takashi Tsuboi
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Atsushi Takata
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, Saitama, Japan.
- Research Institute for Diseases of Old Age, Juntendo University Graduate School of Medicine, Tokyo, Japan.
| | - Tadafumi Kato
- Department of Psychiatry and Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan.
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Saitama, Japan.
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9
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Kaur H, Jha P, Ochatt SJ, Kumar V. Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities. Crit Rev Biotechnol 2024; 44:202-217. [PMID: 36775666 DOI: 10.1080/07388551.2023.2165900] [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: 08/07/2022] [Revised: 11/04/2022] [Accepted: 12/08/2022] [Indexed: 02/14/2023]
Abstract
Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.
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Affiliation(s)
- Harmeet Kaur
- Division of Research and Development, Plant Biotechnology Lab, Lovely Professional University, Phagwara, Punjab, India
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
| | - Priyanka Jha
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
- Department of Research Facilitation, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India
| | - Sergio J Ochatt
- Agroécologie, InstitutAgro Dijon, INRAE, Univ. Bourgogne Franche-Comté, Dijon, France
| | - Vijay Kumar
- Division of Research and Development, Plant Biotechnology Lab, Lovely Professional University, Phagwara, Punjab, India
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
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10
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Boder-Pasche S, Demir M, Heub S, Garzuel M, Ischer R, Migliozzi D, Graf S, Schmid N, Atakan HB, Gudkova D, Alpern D, Dainese R, Deplancke B, Weder G. Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing. Biomed Microdevices 2024; 26:18. [PMID: 38416278 PMCID: PMC10902082 DOI: 10.1007/s10544-024-00702-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2024] [Indexed: 02/29/2024]
Abstract
High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatments. Focusing on gene expression, the transcriptomic market exploits the benefits of next-generation sequencing (NGS), leveraging RNA sequencing (RNA-seq) as standard for measuring genome-wide gene expression in biological samples. The cumbersome sample preparation, including RNA extraction, conversion to cDNA and amplification, prevents high-throughput translation of RNA-seq technologies. Bulk RNA barcoding and sequencing (BRB-seq) addresses this limitation by enabling sample preparation in multi-well plate format. Sample multiplexing combined with early pooling into a single tube reduces reagents consumption and manual steps. Enabling simultaneous pooling of all samples from the multi-well plate into one tube, our technology relies on smart labware: a pooling lid comprising fluidic features and small pins to transport the liquid, adapted to standard 96-well plates. Operated with standard fluidic tubes and pump, the system enables over 90% recovery of liquid in a single step in less than a minute. Large scale manufacturing of the lid is demonstrated with the transition from a milled polycarbonate/steel prototype into an injection molded polystyrene lid. The pooling lid demonstrated its value in supporting high-throughput barcode-based sequencing by pooling 96 different DNA barcodes directly from a standard 96-well plate, followed by processing within the single sample pool. This new pooling technology shows great potential to address medium throughput needs in the BRB-seq workflow, thereby addressing the challenge of large-scale and cost-efficient sample preparation for RNA-seq.
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Affiliation(s)
- Stéphanie Boder-Pasche
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland.
| | - Mustafa Demir
- Laboratory of Systems Biology and Genetics, Institute of Bio-Engineering & Global Health Institute, School of Life Sciences, EPFL, CH-1015, Lausanne, Switzerland
- Alithea Genomics, Biopôle, CH-1066, Epalinges, Switzerland
| | - Sarah Heub
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Manon Garzuel
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Réal Ischer
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Daniel Migliozzi
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Siegfried Graf
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Noa Schmid
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - H Baris Atakan
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
| | - Daria Gudkova
- Laboratory of Systems Biology and Genetics, Institute of Bio-Engineering & Global Health Institute, School of Life Sciences, EPFL, CH-1015, Lausanne, Switzerland
- Alithea Genomics, Biopôle, CH-1066, Epalinges, Switzerland
| | - Daniel Alpern
- Laboratory of Systems Biology and Genetics, Institute of Bio-Engineering & Global Health Institute, School of Life Sciences, EPFL, CH-1015, Lausanne, Switzerland
- Alithea Genomics, Biopôle, CH-1066, Epalinges, Switzerland
- Swiss Institute of Bioinformatics, CH-1015, Lausanne, Switzerland
| | - Riccardo Dainese
- Laboratory of Systems Biology and Genetics, Institute of Bio-Engineering & Global Health Institute, School of Life Sciences, EPFL, CH-1015, Lausanne, Switzerland
- Alithea Genomics, Biopôle, CH-1066, Epalinges, Switzerland
- Swiss Institute of Bioinformatics, CH-1015, Lausanne, Switzerland
| | - Bart Deplancke
- Laboratory of Systems Biology and Genetics, Institute of Bio-Engineering & Global Health Institute, School of Life Sciences, EPFL, CH-1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, CH-1015, Lausanne, Switzerland
| | - Gilles Weder
- CSEM SA Centre Suisse d'Electronique et de Microtechnique, Jaquet-Droz 1, CH-2002, Neuchâtel, Switzerland
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11
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Ohara D, Takeuchi Y, Watanabe H, Lee Y, Mukoyama H, Ohteki T, Kondoh G, Hirota K. Notch2 with retinoic acid license IL-23 expression by intestinal EpCAM+ DCIR2+ cDC2s in mice. J Exp Med 2024; 221:e20230923. [PMID: 38180443 PMCID: PMC10770806 DOI: 10.1084/jem.20230923] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 11/06/2023] [Accepted: 12/07/2023] [Indexed: 01/06/2024] Open
Abstract
Despite the importance of IL-23 in mucosal host defense and disease pathogenesis, the mechanisms regulating the development of IL-23-producing mononuclear phagocytes remain poorly understood. Here, we employed an Il23aVenus reporter strain to investigate the developmental identity and functional regulation of IL-23-producing cells. We showed that flagellin stimulation or Citrobacter rodentium infection led to robust induction of IL-23-producing EpCAM+ DCIR2+ CD103- cDC2s, termed cDCIL23, which was confined to gut-associated lymphoid tissues, including the mesenteric lymph nodes, cryptopatches, and isolated lymphoid follicles. Furthermore, we demonstrated that Notch2 signaling was crucial for the development of EpCAM+ DCIR2+ cDC2s, and the combination of Notch2 signaling with retinoic acid signaling controlled their terminal differentiation into cDCIL23, supporting a two-step model for the development of gut cDCIL23. Our findings provide fundamental insights into the developmental pathways and cellular dynamics of IL-23-producing cDC2s at steady state and during pathogen infection.
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Affiliation(s)
- Daiya Ohara
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Yusuke Takeuchi
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Hitomi Watanabe
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Yoonha Lee
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Hiroki Mukoyama
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Toshiaki Ohteki
- Department of Biodefense Research, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Gen Kondoh
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Keiji Hirota
- Laboratory of Integrative Biological Science, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
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12
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Bawa G, Liu Z, Yu X, Tran LSP, Sun X. Introducing single cell stereo-sequencing technology to transform the plant transcriptome landscape. TRENDS IN PLANT SCIENCE 2024; 29:249-265. [PMID: 37914553 DOI: 10.1016/j.tplants.2023.10.002] [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: 11/10/2022] [Revised: 10/01/2023] [Accepted: 10/02/2023] [Indexed: 11/03/2023]
Abstract
Single cell RNA-sequencing (scRNA-seq) advancements have helped detect transcriptional heterogeneities in biological samples. However, scRNA-seq cannot currently provide high-resolution spatial transcriptome information or identify subcellular organs in biological samples. These limitations have led to the development of spatially enhanced-resolution omics-sequencing (Stereo-seq), which combines spatial information with single cell transcriptomics to address the challenges of scRNA-seq alone. In this review, we discuss the advantages of Stereo-seq technology. We anticipate that the application of such an integrated approach in plant research will advance our understanding of biological process in the plant transcriptomics era. We conclude with an outlook of how such integration will enhance crop improvement.
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Affiliation(s)
- George Bawa
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Zhixin Liu
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Xiaole Yu
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA.
| | - Xuwu Sun
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China.
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13
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Han Y, Huang C, Pan Y, Gu X. Single Cell Sequencing Technology and Its Application in Alzheimer's Disease. J Alzheimers Dis 2024; 97:1033-1050. [PMID: 38217599 DOI: 10.3233/jad-230861] [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: 01/15/2024]
Abstract
Alzheimer's disease (AD) involves degeneration of cells in the brain. Due to insidious onset and slow progression, AD is often not diagnosed until it gets progressed to a more severe stage. The diagnosis and treatment of AD has been a challenge. In recent years, high-throughput sequencing technologies have exhibited advantages in exploring the pathogenesis of diseases. However, the types of cells of the central nervous system are complex and traditional bulk sequencing cannot reflect their heterogeneity. Single-cell sequencing technology enables study at the individual cell level and has an irreplaceable advantage in the study of complex diseases. In recent years, this field has expanded rapidly and several types of single-cell sequencing technologies have emerged, including transcriptomics, epigenomics, genomics and proteomics. This review article provides an overview of these single-cell sequencing technologies and their application in AD.
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Affiliation(s)
- Yuru Han
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Congying Huang
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yuhui Pan
- Center for Disease Control and Prevention of Harbin, Harbin, China
| | - Xuefeng Gu
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
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14
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Kashima M, Komura R, Sato Y, Hashimoto C, Hirata H. A resource of single-cell gene expression profiles in a planarian Dugesia japonica. Dev Growth Differ 2024; 66:43-55. [PMID: 37779230 DOI: 10.1111/dgd.12893] [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: 02/21/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/03/2023]
Abstract
The freshwater planarian Dugesia japonica maintains an abundant heterogeneous cell population called neoblasts, which include adult pluripotent stem cells. Thus, it is an excellent model organism for stem cell and regeneration research. Recently, many single-cell RNA sequencing (scRNA-seq) databases of several model organisms, including other planarian species, have become publicly available; these are powerful and useful resources to search for gene expression in various tissues and cells. However, the only scRNA-seq dataset for D. japonica has been limited by the number of genes detected. Herein, we collected D. japonica cells, and conducted an scRNA-seq analysis. A novel, automatic, iterative cell clustering strategy produced a dataset of 3,404 cells, which could be classified into 63 cell types based on gene expression profiles. We introduced two examples for utilizing the scRNA-seq dataset in this study using D. japonica. First, the dataset provided results consistent with previous studies as well as novel functionally relevant insights, that is, the expression of DjMTA and DjP2X-A genes in neoblasts that give rise to differentiated cells. Second, we conducted an integrative analysis of the scRNA-seq dataset and time-course bulk RNA-seq of irradiated animals, demonstrating that the dataset can help interpret differentially expressed genes captured via bulk RNA-seq. Using the R package "Seurat" and GSE223927, researchers can easily access and utilize this dataset.
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Affiliation(s)
- Makoto Kashima
- College of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
- Department of Molecular Biology, Faculty of Science, Toho University, Funabashi, Japan
| | - Rei Komura
- College of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
| | - Yuki Sato
- JT Biohistory Research Hall, Takatsuki, Japan
| | - Chikara Hashimoto
- JT Biohistory Research Hall, Takatsuki, Japan
- Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Japan
| | - Hiromi Hirata
- College of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
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15
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Shima Y, Skibbe H, Sasagawa Y, Fujimori N, Iwayama Y, Isomura-Matoba A, Yano M, Ichikawa T, Nikaido I, Hattori N, Kato T. Distinctiveness and continuity in transcriptome and connectivity in the anterior-posterior axis of the paraventricular nucleus of the thalamus. Cell Rep 2023; 42:113309. [PMID: 37862168 DOI: 10.1016/j.celrep.2023.113309] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/20/2023] [Accepted: 10/04/2023] [Indexed: 10/22/2023] Open
Abstract
The paraventricular nucleus of the thalamus (PVT) projects axons to multiple areas, mediates a wide range of behaviors, and exhibits regional heterogeneity in both functions and axonal projections. Still, questions regarding the cell types present in the PVT and the extent of their differences remain inadequately addressed. We applied single-cell RNA sequencing to depict the transcriptomic characteristics of mouse PVT neurons. We found that one of the most significant variances in the PVT transcriptome corresponded to the anterior-posterior axis. While the single-cell transcriptome classified PVT neurons into five types, our transcriptomic and histological analyses showed continuity among the cell types. We discovered that anterior and posterior subpopulations had nearly non-overlapping projection patterns, while another population showed intermediate patterns. In addition, these subpopulations responded differently to appetite-related neuropeptides, with their activation showing opposing effects on food consumption. Our studies unveiled the contrasts and the continuity of PVT neurons that underpin their function.
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Affiliation(s)
- Yasuyuki Shima
- Neurodegenerative Disorders Collaborative Laboratory, RIKEN, Wako, Saitama 351-0198, Japan; Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan.
| | - Henrik Skibbe
- Brain Image Analysis Unit, RIKEN, Wako, Saitama 351-0198, Japan
| | - Yohei Sasagawa
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Noriko Fujimori
- Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan; Support Unit for Bio-Material Analysis, Research Resource Division, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan
| | - Yoshimi Iwayama
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Ayako Isomura-Matoba
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan
| | - Minoru Yano
- Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Takumi Ichikawa
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Itoshi Nikaido
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Nobutaka Hattori
- Neurodegenerative Disorders Collaborative Laboratory, RIKEN, Wako, Saitama 351-0198, Japan; Department of Neurology, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan
| | - Tadafumi Kato
- Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan; Department of Psychiatry, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan; Department of Molecular Pathology of Mood Disorders, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan.
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16
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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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17
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Zhang J, Ahmad M, Gao H. Application of single-cell multi-omics approaches in horticulture research. MOLECULAR HORTICULTURE 2023; 3:18. [PMID: 37789394 PMCID: PMC10521458 DOI: 10.1186/s43897-023-00067-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023]
Abstract
Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.
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Affiliation(s)
- Jun Zhang
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Mayra Ahmad
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hongbo Gao
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
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18
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Huang D, Ma N, Li X, Gou Y, Duan Y, Liu B, Xia J, Zhao X, Wang X, Li Q, Rao J, Zhang X. Advances in single-cell RNA sequencing and its applications in cancer research. J Hematol Oncol 2023; 16:98. [PMID: 37612741 PMCID: PMC10463514 DOI: 10.1186/s13045-023-01494-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023] Open
Abstract
Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.
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Affiliation(s)
- Dezhi Huang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Naya Ma
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xinlei Li
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Yang Gou
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Yishuo Duan
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Bangdong Liu
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Jing Xia
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xianlan Zhao
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Xiaoqi Wang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China
- Jinfeng Laboratory, Chongqing, 401329, China
| | - Qiong Li
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
| | - Jun Rao
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
| | - Xi Zhang
- Medical Center of Hematology, Xinqiao Hospital, State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 400037, China.
- Jinfeng Laboratory, Chongqing, 401329, China.
- National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
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19
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Ogura N, Sasagawa Y, Ito T, Tameshige T, Kawai S, Sano M, Doll Y, Iwase A, Kawamura A, Suzuki T, Nikaido I, Sugimoto K, Ikeuchi M. WUSCHEL-RELATED HOMEOBOX 13 suppresses de novo shoot regeneration via cell fate control of pluripotent callus. SCIENCE ADVANCES 2023; 9:eadg6983. [PMID: 37418524 PMCID: PMC10328406 DOI: 10.1126/sciadv.adg6983] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 06/05/2023] [Indexed: 07/09/2023]
Abstract
Plants can regenerate their bodies via de novo establishment of shoot apical meristems (SAMs) from pluripotent callus. Only a small fraction of callus cells is eventually specified into SAMs but the molecular mechanisms underlying fate specification remain obscure. The expression of WUSCHEL (WUS) is an early hallmark of SAM fate acquisition. Here, we show that a WUS paralog, WUSCHEL-RELATED HOMEOBOX 13 (WOX13), negatively regulates SAM formation from callus in Arabidopsis thaliana. WOX13 promotes non-meristematic cell fate via transcriptional repression of WUS and other SAM regulators and activation of cell wall modifiers. Our Quartz-Seq2-based single cell transcriptome revealed that WOX13 plays key roles in determining cellular identity of callus cell population. We propose that reciprocal inhibition between WUS and WOX13 mediates critical cell fate determination in pluripotent cell population, which has a major impact on regeneration efficiency.
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Affiliation(s)
- Nao Ogura
- Division of Biological Sciences, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma, Nara 630-0192, Japan
- Department of Biology, Faculty of Science, Niigata University, Niigata, Niigata 950-2181, Japan
| | - Yohei Sasagawa
- Department of Functional Genome Informatics, Division of Medical Genomics, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo, Japan
- RIKEN Center for Biosystems Dynamics Research, Wako, Saitama 351-0198, Japan
| | - Tasuku Ito
- Department of Biology, Faculty of Science, Niigata University, Niigata, Niigata 950-2181, Japan
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Toshiaki Tameshige
- Division of Biological Sciences, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma, Nara 630-0192, Japan
- Kihara Institute for Biological Research, Yokohama City University, 641-12 Maioka, Yokohama 244-0813, Japan
| | - Satomi Kawai
- Department of Biology, Faculty of Science, Niigata University, Niigata, Niigata 950-2181, Japan
| | - Masaki Sano
- Department of Biology, Faculty of Science, Niigata University, Niigata, Niigata 950-2181, Japan
| | - Yuki Doll
- Division of Biological Sciences, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma, Nara 630-0192, Japan
| | - Akira Iwase
- RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan
| | - Ayako Kawamura
- RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan
| | - Takamasa Suzuki
- Department of Biological Chemistry, College of Biosciences and Biotechnology, Chubu University, Kasugai, Aichi 487-8501, Japan
| | - Itoshi Nikaido
- Department of Functional Genome Informatics, Division of Medical Genomics, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo, Japan
- RIKEN Center for Biosystems Dynamics Research, Wako, Saitama 351-0198, Japan
| | - Keiko Sugimoto
- RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan
- Department of Biological Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 119-0033, Japan
| | - Momoko Ikeuchi
- Division of Biological Sciences, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma, Nara 630-0192, Japan
- Department of Biology, Faculty of Science, Niigata University, Niigata, Niigata 950-2181, Japan
- RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan
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20
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Takada H, Sasagawa Y, Yoshimura M, Tanaka K, Iwayama Y, Hayashi T, Isomura-Matoba A, Nikaido I, Kurisaki A. Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis. Nat Commun 2023; 14:3750. [PMID: 37386010 PMCID: PMC10310803 DOI: 10.1038/s41467-023-39113-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 05/30/2023] [Indexed: 07/01/2023] Open
Abstract
Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.
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Affiliation(s)
- Hitomi Takada
- Laboratory of Stem Cell Technologies, Graduate School of Science and Technology, Nara Institute of Science and Technology, Takayama-cho, Ikoma, Nara, Japan
| | - Yohei Sasagawa
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
- Department of Functional Genome Informatics, Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo, Japan
| | - Mika Yoshimura
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
| | - Kaori Tanaka
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
| | - Yoshimi Iwayama
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
- Department of Functional Genome Informatics, Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo, Japan
| | - Tetsutaro Hayashi
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
| | - Ayako Isomura-Matoba
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan
| | - Itoshi Nikaido
- Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research, Wako, Saitama, Japan.
- Department of Functional Genome Informatics, Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University, Bunkyo, Tokyo, Japan.
- Master's/Doctoral Program in Life Science Innovation (Bioinformatics), Degree Programs in Systems and Information Engineering, Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Ibaraki, Japan.
| | - Akira Kurisaki
- Laboratory of Stem Cell Technologies, Graduate School of Science and Technology, Nara Institute of Science and Technology, Takayama-cho, Ikoma, Nara, Japan.
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21
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Watanabe Y, Yamamoto H, Matsuba I, Watanabe K, Kunishima T, Takechi Y, Takuma T, Araki Y, Hirotsu N, Sakai H, Oikawa R, Danno H, Fukuda M, Sugino R, Futagami S, Wada K, Itoh F, Tateishi K, Oda I, Hatori Y, Degawa H. Time-series transcriptome analysis of peripheral blood mononuclear cells obtained from individuals who received the SARS-CoV-2 mRNA vaccine. J Med Virol 2023; 95:e28884. [PMID: 37342886 DOI: 10.1002/jmv.28884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/23/2023]
Abstract
Messenger ribonucleic acid (mRNA) vaccination against coronavirus disease 2019 (COVID-19) is an effective prevention strategy, despite a limited understanding of the molecular mechanisms underlying the host immune system and individual heterogeneity of the variable effects of mRNA vaccination. We assessed the time-series changes in the comprehensive gene expression profiles of 200 vaccinated healthcare workers by performing bulk transcriptome and bioinformatics analyses, including dimensionality reduction utilizing the uniform manifold approximation and projection (UMAP) technique. For these analyses, blood samples, including peripheral blood mononuclear cells (PBMCs), were collected from 214 vaccine recipients before vaccination (T1) and on Days 22 (T2, after second dose), 90, 180 (T3, before a booster dose), and 360 (T4, after a booster dose) after receiving the first dose of BNT162b2 vaccine (UMIN000043851). UMAP successfully visualized the main cluster of gene expression at each time point in PBMC samples (T1-T4). Through differentially expressed gene (DEG) analysis, we identified genes that showed fluctuating expression levels and gradual increases in expression levels from T1 to T4, as well as genes with increased expression levels at T4 alone. We also succeeded in dividing these cases into five types based on the changes in gene expression levels. High-throughput and temporal bulk RNA-based transcriptome analysis is a useful approach for inclusive, diverse, and cost-effective large-scale clinical studies.
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Affiliation(s)
- Yoshiyuki Watanabe
- Kawasaki Physicians Association, Kawasaki, Japan
- Department of Internal Medicine, Kawasaki Rinko General Hospital, Kawasaki, Japan
- Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan
- Department of Internal Medicine, Division of Gastroenterology, Nippon Medical School, Tokyo, Japan
- Department of Otorhinolaryngology, Toho University Omori Medical Center, Tokyo, Japan
| | - Hiroyuki Yamamoto
- Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan
- Department of Bioinformatics, St. Marianna University Graduate School of Medicine, Kanagawa, Japan
| | | | - Karin Watanabe
- Department of Internal Medicine, Kawasaki Rinko General Hospital, Kawasaki, Japan
| | | | | | | | | | | | | | - Ritsuko Oikawa
- Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan
| | | | | | | | - Seiji Futagami
- Department of Internal Medicine, Division of Gastroenterology, Nippon Medical School, Tokyo, Japan
| | - Kota Wada
- Department of Otorhinolaryngology, Toho University Omori Medical Center, Tokyo, Japan
| | - Fumio Itoh
- Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Keisuke Tateishi
- Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Ichiro Oda
- Department of Internal Medicine, Kawasaki Rinko General Hospital, Kawasaki, Japan
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Kijima Y, Evans-Yamamoto D, Toyoshima H, Yachie N. A universal sequencing read interpreter. SCIENCE ADVANCES 2023; 9:eadd2793. [PMID: 36598975 PMCID: PMC9812397 DOI: 10.1126/sciadv.add2793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 11/30/2022] [Indexed: 06/17/2023]
Abstract
Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.
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Affiliation(s)
- Yusuke Kijima
- School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, The University of British Columbia, Vancouver, BC V6T 1Z3, Canada
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
- Department of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
| | - Daniel Evans-Yamamoto
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
- Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0035, Japan
| | - Hiromi Toyoshima
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
| | - Nozomu Yachie
- School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, The University of British Columbia, Vancouver, BC V6T 1Z3, Canada
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
- Twitter: @yachielab
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23
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Suzuki T. Overview of single-cell RNA sequencing analysis and its application to spermatogenesis research. Reprod Med Biol 2023; 22:e12502. [PMID: 36726594 PMCID: PMC9884325 DOI: 10.1002/rmb2.12502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 12/18/2022] [Accepted: 01/10/2023] [Indexed: 01/30/2023] Open
Abstract
Background Single-cell transcriptomics allows parallel analysis of multiple cell types in tissues. Because testes comprise somatic cells and germ cells at various stages of spermatogenesis, single-cell RNA sequencing is a powerful tool for investigating the complex process of spermatogenesis. However, single-cell RNA sequencing analysis needs extensive knowledge of experimental technologies and bioinformatics, making it difficult for many, particularly experimental biologists and clinicians, to use it. Methods Aiming to make single-cell RNA sequencing analysis familiar, this review article presents an overview of experimental and computational methods for single-cell RNA sequencing analysis with a history of transcriptomics. In addition, combining the PubMed search and manual curation, this review also provides a summary of recent novel insights into human and mouse spermatogenesis obtained using single-cell RNA sequencing analyses. Main Findings Single-cell RNA sequencing identified mesenchymal cells and type II innate lymphoid cells as novel testicular cell types in the adult mouse testes, as well as detailed subtypes of germ cells. This review outlines recent discoveries into germ cell development and subtypes, somatic cell development, and cell-cell interactions. Conclusion The findings on spermatogenesis obtained using single-cell RNA sequencing may contribute to a deeper understanding of spermatogenesis and provide new directions for male fertility therapy.
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Affiliation(s)
- Takahiro Suzuki
- RIKEN Center for Integrated Medical Science (IMS)Yokohama CityKanagawaJapan
- Graduate School of Medical Life ScienceYokohama City UniversityYokohama CityKanagawaJapan
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24
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Probst V, Simonyan A, Pacheco F, Guo Y, Nielsen FC, Bagger FO. Benchmarking full-length transcript single cell mRNA sequencing protocols. BMC Genomics 2022; 23:860. [PMID: 36581800 PMCID: PMC9801581 DOI: 10.1186/s12864-022-09014-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 11/14/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. RESULTS Here, we present a performance evaluation of four different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications taxing high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocols Genome & Transcriptome sequencing (G&T) and SMART-seq3 (SS3). G&T delivered the highest detection of genes per single cell. SS3 presented the highest gene detection per single cell at the lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between samples, but at the absolute highest price. NEB® delivered a lower detection of genes but remains an alternative to more expensive commercial kits. CONCLUSION For the tested kits we found that ease-of-use came at higher prices. Takara can be selected for its ease-of-use to analyse a few samples, but we recommend the cheaper G&T-seq or SS3 for laboratories where a substantial sample flow can be expected.
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Affiliation(s)
- Victoria Probst
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Arman Simonyan
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Felix Pacheco
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Yuliu Guo
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Finn Cilius Nielsen
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Frederik Otzen Bagger
- grid.475435.4Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
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25
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Battenberg K, Kelly ST, Ras RA, Hetherington NA, Hayashi M, Minoda A. A flexible cross-platform single-cell data processing pipeline. Nat Commun 2022; 13:6847. [PMID: 36369450 PMCID: PMC9652453 DOI: 10.1038/s41467-022-34681-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 11/02/2022] [Indexed: 11/13/2022] Open
Abstract
Single-cell RNA-sequencing analysis to quantify the RNA molecules in individual cells has become popular, as it can obtain a large amount of information from each experiment. We introduce UniverSC ( https://github.com/minoda-lab/universc ), a universal single-cell RNA-seq data processing tool that supports any unique molecular identifier-based platform. Our command-line tool, docker image, and containerised graphical application enables consistent and comprehensive integration, comparison, and evaluation across data generated from a wide range of platforms. We also provide a cross-platform application to run UniverSC via a graphical user interface, available for macOS, Windows, and Linux Ubuntu, negating one of the bottlenecks with single-cell RNA-seq analysis that is data processing for researchers who are not bioinformatically proficient.
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Affiliation(s)
- Kai Battenberg
- Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Center for Sustainable Resource Science, RIKEN, Yokohama, Japan
| | - S Thomas Kelly
- Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Radu Abu Ras
- Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Faculty of Automatics, Computers and Electronics, University of Craiova, Craiova, Romania
| | - Nicola A Hetherington
- Department of Cell Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
| | - Makoto Hayashi
- Center for Sustainable Resource Science, RIKEN, Yokohama, Japan
| | - Aki Minoda
- Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan.
- Department of Cell Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands.
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Qin R, Zhao H, He Q, Li F, Li Y, Zhao H. Advances in single-cell sequencing technology in the field of hepatocellular carcinoma. Front Genet 2022; 13:996890. [PMID: 36303541 PMCID: PMC9592975 DOI: 10.3389/fgene.2022.996890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/28/2022] [Indexed: 11/13/2022] Open
Abstract
Tumors are a class of diseases characterized by altered genetic information and uncontrolled growth. Sequencing technology provide researchers with a better way to explore specific tumor pathogenesis. In recent years, single-cell sequencing technology has shone in tumor research, especially in the study of liver cancer, revealing phenomena that were unexplored by previous studies. Single-cell sequencing (SCS) is a technique for sequencing the cellular genome, transcriptome, epigenome, proteomics, or metabolomics after dissociation of tissues into single cells. Compared with traditional bulk sequencing, single-cell sequencing can dissect human tumors at single-cell resolution, finely delineate different cell types, and reveal the heterogeneity of tumor cells. In view of the diverse pathological types and complex pathogenesis of hepatocellular carcinoma (HCC), the study of the heterogeneity among tumor cells can help improve its clinical diagnosis, treatment and prognostic judgment. On this basis, SCS has revolutionized our understanding of tumor heterogeneity, tumor immune microenvironment, and clonal evolution of tumor cells. This review summarizes the basic process and development of single-cell sequencing technology and its increasing role in the field of hepatocellular carcinoma.
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Affiliation(s)
- Rongyi Qin
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Haichao Zhao
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
| | - Qizu He
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Feng Li
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Yanjun Li
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- *Correspondence: Yanjun Li, ; Haoliang Zhao,
| | - Haoliang Zhao
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- *Correspondence: Yanjun Li, ; Haoliang Zhao,
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Habibey R, Rojo Arias JE, Striebel J, Busskamp V. Microfluidics for Neuronal Cell and Circuit Engineering. Chem Rev 2022; 122:14842-14880. [PMID: 36070858 PMCID: PMC9523714 DOI: 10.1021/acs.chemrev.2c00212] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.
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Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
| | - Jesús Eduardo Rojo Arias
- Wellcome─MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0AW, United Kingdom
| | - Johannes Striebel
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
| | - Volker Busskamp
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
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28
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Xiao H, Xiao H, Zhang Y, Guo L, Dou Z, Liu L, Zhu L, Feng W, Liu B, Hu B, Chen T, Liu G, Wen T. High-throughput sequencing unravels the cell heterogeneity of cerebrospinal fluid in the bacterial meningitis of children. Front Immunol 2022; 13:872832. [PMID: 36119025 PMCID: PMC9478118 DOI: 10.3389/fimmu.2022.872832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
Bacterial meningitis (BM) is a common life-threatening infection in children that occurs in the central nervous system (CNS). The cytologic examination of cerebrospinal fluid (CSF) is a key parameter in the diagnosis of BM, but the heterogeneity of cells in the CSF has not been elucidated, which limits the current understanding of BM neuroinflammation. In this study, CSF samples were collected from a number of BM patients who were in different stages of disease progression. Single-cell RNA-sequencing (scRNA-seq), with additional bulk transcriptome sequencing, was conducted to decipher the characteristics of CSF cells in BM progression. A total of 18 immune cell clusters in CSF were identified, including two neutrophils, two monocytes, one macrophage, four myeloid dendritic cells, five T cells, one natural killer cell, one B cell, one plasmacytoid dendritic cell, and one plasma cell subtype. Their population profiles and dynamics in the initial onset, remission, and recovery stages during BM progression were also characterized, which showed decreased proportions of myeloid cells and increased proportions of lymphoid cells with disease progression. One novel neutrophil subtype, FFAR2+TNFAIP6+ neutrophils, and one novel monocyte subtype, THBS1+IL1B+ monocytes, were discovered, and their quantity changes positively correlated with the intensity of the inflammatory response in the CSF during BM. In addition, the CSF of BM patients with unsatisfactory therapeutic responses presented with different cell heterogeneity compared to the CSF of BM patients with satisfactory therapeutic responses, and their CSF featured altered intercellular communications and increased proportions of type II myeloid dendritic cells and plasmacytoid dendritic cells. Moreover, the bulk transcriptome profiles of autologous CSF cells and peripheral blood leukocytes of BM patients showed that the immune cells in these two physiological compartments exhibited distinct immune responses under different onset conditions. In particular, the CSF cells showed a high expression of macrophage characteristic genes and a low expression of platelet characteristic genes compared with peripheral blood leukocytes. Our study conducted an in-depth exploration of the characteristics of CSF cells in BM progression, which provided novel insights into immune cell engagement in acute CNS infection.
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Affiliation(s)
- Haihan Xiao
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Haijuan Xiao
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Yun Zhang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Lingyun Guo
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Zhenzhen Dou
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Linlin Liu
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Liang Zhu
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Wenya Feng
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Bing Liu
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Bing Hu
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Tianming Chen
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Gang Liu
- Department of Infectious Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
- *Correspondence: Tingyi Wen, ; Gang Liu,
| | - Tingyi Wen
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Tingyi Wen, ; Gang Liu,
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Kashima M, Kamitani M, Nomura Y, Mori-Moriyama N, Betsuyaku S, Hirata H, Nagano AJ. DeLTa-Seq: direct-lysate targeted RNA-Seq from crude tissue lysate. PLANT METHODS 2022; 18:99. [PMID: 35933383 PMCID: PMC9356424 DOI: 10.1186/s13007-022-00930-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/24/2022] [Indexed: 06/09/2023]
Abstract
BACKGROUND Quantification of gene expression such as RNA-Seq is a popular approach to study various biological phenomena. Despite the development of RNA-Seq library preparation methods and sequencing platforms in the last decade, RNA extraction remains the most laborious and costly step in RNA-Seq of tissue samples of various organisms. Thus, it is still difficult to examine gene expression in thousands of samples. RESULTS Here, we developed Direct-RT buffer in which homogenization of tissue samples and direct-lysate reverse transcription can be conducted without RNA purification. The DTT concentration in Direct-RT buffer prevented RNA degradation but not RT in the lysates of several plant tissues, yeast, and zebrafish larvae. Direct reverse transcription on these lysates in Direct-RT buffer produced comparable amounts of cDNA to those synthesized from purified RNA. To maximize the advantage of the Direct-RT buffer, we integrated Direct-RT and targeted RNA-Seq to develop a cost-effective, high-throughput quantification method for the expressions of hundreds of genes: DeLTa-Seq (Direct-Lysate reverse transcription and Targeted RNA-Seq). The DeLTa-Seq method could drastically improve the efficiency and accuracy of gene expression analysis. DeLTa-Seq analysis of 1056 samples revealed the temperature-dependent effects of jasmonic acid and salicylic acid in Arabidopsis thaliana. CONCLUSIONS The DeLTa-Seq method can realize large-scale studies using thousands of animal, plant, and microorganism samples, such as chemical screening, field experiments, and studies focusing on individual variability. In addition, Direct-RT is also beneficial for gene expression analysis in small tissues from which it is difficult to purify enough RNA for the experiments.
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Affiliation(s)
- Makoto Kashima
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
- Department of Chemistry and Biological Science, College of Science and Engineering, Aoyama Gakuin University, Fuchinobe 5-10-1, Chuoku, , Sagamihara 252-5258 Japan
| | - Mari Kamitani
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
- Center for Ecological Research, Kyoto University, Hirano 2-509-3, Otsu, Shiga 520-2113 Japan
| | - Yasuyuki Nomura
- Research Institute for Food and Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
| | - Natsumi Mori-Moriyama
- Faculty of Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
| | - Shigeyuki Betsuyaku
- Faculty of Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
| | - Hiromi Hirata
- Department of Chemistry and Biological Science, College of Science and Engineering, Aoyama Gakuin University, Fuchinobe 5-10-1, Chuoku, , Sagamihara 252-5258 Japan
| | - Atsushi J. Nagano
- Faculty of Agriculture, Ryukoku University, Yokotani 1-5, Seta Oe-cho, Otsu, Shiga 520-2194 Japan
- Institute for Advanced Biosciences, Keio University, 403-1 Nipponkoku, Daihouji, Tsuruoka, Yamagata 997-0017 Japan
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Abstract
The single-cell revolution in the field of genomics is in full bloom, with clever new molecular biology tricks appearing regularly that allow researchers to explore new modalities or scale up their projects to millions of cells and beyond. Techniques abound to measure RNA expression, DNA alterations, protein abundance, chromatin accessibility, and more, all with single-cell resolution and often in combination. Despite such a rapidly changing technology landscape, there are several fundamental principles that are applicable to the majority of experimental workflows to help users avoid pitfalls and exploit the advantages of the chosen platform. In this overview article, we describe a variety of popular single-cell genomics technologies and address some common questions pertaining to study design, sample preparation, quality control, and sequencing strategy. As the majority of relevant publications currently revolve around single-cell RNA-seq, we will prioritize this genomics modality in our discussion. © 2022 Wiley Periodicals LLC.
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Affiliation(s)
- Claire Regan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York
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31
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A common epigenetic mechanism across different cellular origins underlies systemic immune dysregulation in an idiopathic autism mouse model. Mol Psychiatry 2022; 27:3343-3354. [PMID: 35491410 DOI: 10.1038/s41380-022-01566-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 04/05/2022] [Accepted: 04/06/2022] [Indexed: 11/08/2022]
Abstract
Immune dysregulation plays a key role in the pathogenesis of autism. Changes occurring at the systemic level, from brain inflammation to disturbed innate/adaptive immune in the periphery, are frequently observed in patients with autism; however, the intrinsic mechanisms behind them remain elusive. We hypothesize a common etiology may lie in progenitors of different types underlying widespread immune dysregulation. By single-cell RNA sequencing (sc-RNA seq), we trace the developmental origins of immune dysregulation in a mouse model of idiopathic autism. It is found that both in aorta-gonad-mesonephros (AGM) and yolk sac (YS) progenitors, the dysregulation of HDAC1-mediated epigenetic machinery alters definitive hematopoiesis during embryogenesis and downregulates the expression of the AP-1 complex for microglia development. Subsequently, these changes result in the dysregulation of the immune system, leading to gut dysbiosis and hyperactive microglia in the brain. We further confirm that dysregulated immune profiles are associated with specific microbiota composition, which may serve as a biomarker to identify autism of immune-dysregulated subtypes. Our findings elucidate a shared mechanism for the origin of immune dysregulation from the brain to the gut in autism and provide new insight to dissecting the heterogeneity of autism, as well as the therapeutic potential of targeting immune-dysregulated autism subtypes.
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32
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TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq. Commun Biol 2022; 5:602. [PMID: 35760847 PMCID: PMC9245575 DOI: 10.1038/s42003-022-03536-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 05/27/2022] [Indexed: 12/22/2022] Open
Abstract
Single-cell RNA-sequencing (scRNA-seq) is valuable for analyzing cellular heterogeneity. Cell composition accuracy is critical for analyzing cell–cell interaction networks from scRNA-seq data. However, droplet- and plate-based scRNA-seq techniques have cell sampling bias that could affect the cell composition of scRNA-seq datasets. Here we developed terminator-assisted solid-phase cDNA amplification and sequencing (TAS-Seq) for scRNA-seq based on a terminator, terminal transferase, and nanowell/bead-based scRNA-seq platform. TAS-Seq showed high tolerance to variations in the terminal transferase reaction, which complicate the handling of existing terminal transferase-based scRNA-seq methods. In murine and human lung samples, TAS-Seq yielded scRNA-seq data that were highly correlated with flow-cytometric data, showing higher gene-detection sensitivity and more robust detection of important cell–cell interactions and expression of growth factors/interleukins in cell subsets than 10X Chromium v2 and Smart-seq2. Expanding TAS-Seq application will improve understanding and atlas construction of lung biology at the single-cell level. Terminator-assisted solid-phase cDNA amplification and sequencing (TASseq) uses a terminator, terminal transferase and bead-based platform to improve generation of single-cell RNA-seq libraries.
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Kind D, Baskaran P, Ramirez F, Giner M, Hayes M, Santacruz D, Koss CK, el Kasmi KC, Wijayawardena B, Viollet C. Automation enables high-throughput and reproducible single-cell transcriptomics library preparation. SLAS Technol 2022; 27:135-142. [DOI: 10.1016/j.slast.2021.10.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Kraus G, Weigelt M, Reinhardt S, Petzold A, Dahl A, Bonifacio E. Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment. J Immunol Methods 2022; 502:113227. [PMID: 35031279 DOI: 10.1016/j.jim.2022.113227] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 12/04/2021] [Accepted: 01/10/2022] [Indexed: 10/19/2022]
Abstract
10x Genomics is a highly accessible single cell RNA sequencing platform that allows for simultaneous gene expression analysis and identification of receptor chain combinations in cells of the adaptive immune system. Here, we asked whether the gene and receptor expression measurements in peripheral blood mononuclear cells (PBMC) are influenced by technical, cell freezing, FACS-processing, and day to day biological variation. No differentially expressed gene was observed between 1. triplicates aliquots taken from the same vial of frozen PBMC; 2. triplicate vials of frozen PBMC; and 3. triplicate aliquots taken from the same vial of frozen PBMC and processed separately for FACS staining and sorting of different PBMC populations. A small number of differentially expressed genes were observed between PBMC sampled, isolated and frozen from the same donor on different days, and these differences were more pronounced in the memory B cells than other cell populations. T cell receptors were recovered in all replicates when at least 5 cells per clonotype were identified. These findings show high reproducibility of 10x Genomics single cell RNA sequencing data in the immune cell context.
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Affiliation(s)
- Gloria Kraus
- Faculty of Medicine, DFG Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Marc Weigelt
- Faculty of Medicine, DFG Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Susanne Reinhardt
- DRESDEN-Concept Genome Center c/o Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
| | - Andreas Petzold
- DRESDEN-Concept Genome Center c/o Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
| | - Andreas Dahl
- DRESDEN-Concept Genome Center c/o Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
| | - Ezio Bonifacio
- Faculty of Medicine, DFG Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany,; German Center for Diabetes Research (DZD), Paul Langerhans Institute Dresden, Technische Universität Dresden, Dresden, Germany,; Institute of Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
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35
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Verma D, Nayak N, Singh A, Singh AK, Garg N. Advancement of Single-Cell Sequencing in Medulloblastoma. Methods Mol Biol 2022; 2423:65-83. [PMID: 34978689 DOI: 10.1007/978-1-0716-1952-0_7] [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: 06/14/2023]
Abstract
Single-cell sequencing is a promising attempt to investigate the genomic, transcriptomic, and multiomic level of individual cell in the larger population of cells. The outward evolution of the technique from a manual method to the automation of single-cell sequencing is cogent. Lately, single-cell sequencing is widely used in various fields of science and has applications in neurobiology, immunity, cancer, microbiology, reproduction, and digestion. This chapter introduces the reader to the details of single-cell sequencing, currently used in several small-scale and commercial platforms. The advancement of single-cell sequencing in brain cancer sheds light on questions unanswered so far in the field of oncology.
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Affiliation(s)
- Deepanshu Verma
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Namyashree Nayak
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Ashuthosh Singh
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Ashutosh Kumar Singh
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Neha Garg
- Department of Medicinal Chemistry, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
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Song Q, Liu L. Single-Cell RNA-Seq Technologies and Computational Analysis Tools: Application in Cancer Research. Methods Mol Biol 2022; 2413:245-255. [PMID: 35044670 DOI: 10.1007/978-1-0716-1896-7_23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The recent maturation of single-cell RNA sequencing (scRNA-seq) provides unique opportunities for researchers to uncover new and potentially unexpected biological discoveries and to understand the complexity of tissues by transcriptomic profiling in individual cells. This review introduces the latest scRNA-seq techniques and platforms as well as their advantages and disadvantages. Moreover, we review computational tools and pipelines for analyzing scRNA-seq data, and their applications in cancer research, highlighting the important role of scRNA-seq techniques in this area.
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Affiliation(s)
- Qianqian Song
- Department of Cancer Biology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA
| | - Liang Liu
- Department of Cancer Biology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA.
- Center for Cancer Genomics and Precision Oncology, Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA.
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Multi-Omics Profiling of the Tumor Microenvironment. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1361:283-326. [DOI: 10.1007/978-3-030-91836-1_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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38
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Dong Z, Wang Y, Yin D, Hang X, Pu L, Zhang J, Geng J, Chang L. Advanced techniques for gene heterogeneity research: Single‐cell sequencing and on‐chip gene analysis systems. VIEW 2022. [DOI: 10.1002/viw.20210011] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Zaizai Dong
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University Beijing China
| | - Yu Wang
- Department of Laboratory Medicine State Key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University/Collaborative Innovation Center Chengdu China
| | - Dedong Yin
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University Beijing China
| | - Xinxin Hang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University Beijing China
| | - Lei Pu
- Department of Laboratory Medicine State Key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University/Collaborative Innovation Center Chengdu China
| | - Jianfu Zhang
- Department of Laboratory Medicine State Key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University/Collaborative Innovation Center Chengdu China
| | - Jia Geng
- Department of Laboratory Medicine State Key Laboratory of Biotherapy and Cancer Center West China Hospital Sichuan University/Collaborative Innovation Center Chengdu China
| | - Lingqian Chang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University Beijing China
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Li Z, Lin F, Zhong CH, Wang S, Xue X, Shao Y. Single-Cell Sequencing to Unveil the Mystery of Embryonic Development. Adv Biol (Weinh) 2021; 6:e2101151. [PMID: 34939365 DOI: 10.1002/adbi.202101151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 11/05/2021] [Indexed: 12/21/2022]
Abstract
Embryonic development is a fundamental physiological process that can provide tremendous insights into stem cell biology and regenerative medicine. In this process, cell fate decision is highly heterogeneous and dynamic, and investigations at the single-cell level can greatly facilitate the understanding of the molecular roadmap of embryonic development. Rapid advances in the technology of single-cell sequencing offer a perfectly useful tool to fulfill this purpose. Despite its great promise, single-cell sequencing is highly interdisciplinary, and successful applications in specific biological contexts require a general understanding of its diversity as well as the advantage versus limitations for each of its variants. Here, the technological principles of single-cell sequencing are consolidated and its applications in the study of embryonic development are summarized. First, the technology basics are presented and the available tools for each step including cell isolation, library construction, sequencing, and data analysis are discussed. Then, the works that employed single-cell sequencing are reviewed to investigate the specific processes of embryonic development, including preimplantation, peri-implantation, gastrulation, and organogenesis. Further, insights are provided on existing challenges and future research directions.
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Affiliation(s)
- Zida Li
- Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China.,Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China
| | - Feng Lin
- Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, 100871, China
| | - Chu-Han Zhong
- International Center for Applied Mechanics, State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Shue Wang
- Department of Chemistry, Chemical, and Biomedical Engineering, Tagliatela College of Engineering, University of New Haven, West Haven, CT, 06561, USA
| | - Xufeng Xue
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yue Shao
- Institute of Biomechanics and Medical Engineering, Department of Engineering Mechanics, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China
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40
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Unravelling glioblastoma heterogeneity by means of single-cell RNA sequencing. Cancer Lett 2021; 527:66-79. [PMID: 34902524 DOI: 10.1016/j.canlet.2021.12.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/11/2022]
Abstract
Glioblastoma (GBM) is the most invasive and deadliest brain cancer in adults. Its inherent heterogeneity has been designated as the main cause of treatment failure. Thus, a deeper understanding of the diversity that shapes GBM pathobiology is of utmost importance. Single-cell RNA sequencing (scRNA-seq) technologies have begun to uncover the hidden composition of complex tumor ecosystems. Herein, a semi-systematic search of reference literature databases provided all existing publications using scRNA-seq for the investigation of human GBM. We compared and discussed findings from these works to build a more robust and unified knowledge base. All aspects ranging from inter-patient heterogeneity to intra-tumoral organization, cancer stem cell diversity, clonal mosaicism, and the tumor microenvironment (TME) are comprehensively covered in this report. Tumor composition not only differs across patients but also involves a great extent of heterogeneity within itself. Spatial and cellular heterogeneity can reveal tumor evolution dynamics. In addition, the discovery of distinct cell phenotypes might lead to the development of targeted treatment approaches. In conclusion, scRNA-seq expands our knowledge of GBM heterogeneity and helps to unravel putative therapeutic targets.
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Kashima M, Shida Y, Yamashiro T, Hirata H, Kurosaka H. Intracellular and Intercellular Gene Regulatory Network Inference From Time-Course Individual RNA-Seq. FRONTIERS IN BIOINFORMATICS 2021; 1:777299. [PMID: 36303726 PMCID: PMC9580923 DOI: 10.3389/fbinf.2021.777299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 10/26/2021] [Indexed: 11/13/2022] Open
Abstract
Gene regulatory network (GRN) inference is an effective approach to understand the molecular mechanisms underlying biological events. Generally, GRN inference mainly targets intracellular regulatory relationships such as transcription factors and their associated targets. In multicellular organisms, there are both intracellular and intercellular regulatory mechanisms. Thus, we hypothesize that GRNs inferred from time-course individual (whole embryo) RNA-Seq during development can reveal intercellular regulatory relationships (signaling pathways) underlying the development. Here, we conducted time-course bulk RNA-Seq of individual mouse embryos during early development, followed by pseudo-time analysis and GRN inference. The results demonstrated that GRN inference from RNA-Seq with pseudo-time can be applied for individual bulk RNA-Seq similar to scRNA-Seq. Validation using an experimental-source-based database showed that our approach could significantly infer GRN for all transcription factors in the database. Furthermore, the inferred ligand-related and receptor-related downstream genes were significantly overlapped. Thus, the inferred GRN based on whole organism could include intercellular regulatory relationships, which cannot be inferred from scRNA-Seq based only on gene expression data. Overall, inferring GRN from time-course bulk RNA-Seq is an effective approach to understand the regulatory relationships underlying biological events in multicellular organisms.
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Affiliation(s)
- Makoto Kashima
- College of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
- *Correspondence: Makoto Kashima,
| | - Yuki Shida
- Department of Orthodontics and Dentofacial Orthopedics, Osaka University, Suita, Japan
| | - Takashi Yamashiro
- Department of Orthodontics and Dentofacial Orthopedics, Osaka University, Suita, Japan
| | - Hiromi Hirata
- College of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
| | - Hiroshi Kurosaka
- Department of Orthodontics and Dentofacial Orthopedics, Osaka University, Suita, Japan
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Asada K, Takasawa K, Machino H, Takahashi S, Shinkai N, Bolatkan A, Kobayashi K, Komatsu M, Kaneko S, Okamoto K, Hamamoto R. Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research. Biomedicines 2021; 9:biomedicines9111513. [PMID: 34829742 PMCID: PMC8614827 DOI: 10.3390/biomedicines9111513] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/06/2021] [Accepted: 10/19/2021] [Indexed: 01/14/2023] Open
Abstract
In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; technologies that are centered on single-cell RNA sequencing (scRNA-seq) have been reported to analyze cancer constituent cells, identify cell groups responsible for therapeutic resistance, and analyze gene signatures of resistant cell groups. However, although single-cell analysis is a powerful tool, various issues have been reported, including batch effects and transcriptional noise due to gene expression variation and mRNA degradation. To overcome these issues, machine learning techniques are currently being introduced for single-cell analysis, and promising results are being reported. In addition, machine learning has also been used in various ways for single-cell analysis, such as single-cell assay of transposase accessible chromatin sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq) analysis, and multi-omics analysis; thus, it contributes to a deeper understanding of the characteristics of human diseases, especially cancer, and supports clinical applications. In this review, we present a comprehensive introduction to the implementation of machine learning techniques in medical research for single-cell analysis, and discuss their usefulness and future potential.
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Affiliation(s)
- Ken Asada
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
- Correspondence: (K.A.); (R.H.); Tel.: +81-3-3547-5271 (R.H.)
| | - Ken Takasawa
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
| | - Hidenori Machino
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
| | - Satoshi Takahashi
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
| | - Norio Shinkai
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Amina Bolatkan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; (K.K.); (S.K.)
| | - Kazuma Kobayashi
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; (K.K.); (S.K.)
| | - Masaaki Komatsu
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan; (K.T.); (H.M.); (S.T.); (N.S.); (A.B.); (M.K.)
| | - Syuzo Kaneko
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; (K.K.); (S.K.)
| | - Koji Okamoto
- Division of Cancer Differentiation, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan;
| | - Ryuji Hamamoto
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; (K.K.); (S.K.)
- Correspondence: (K.A.); (R.H.); Tel.: +81-3-3547-5271 (R.H.)
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Zheng J, Ye Y, Xu Q, Xu W, Zhang W, Chen X. A Modified SMART-Seq Method for Single-Cell Transcriptomic Analysis of Embryoid Body Differentiation. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2021; 2520:233-259. [PMID: 34661880 DOI: 10.1007/7651_2021_435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Embryoid bodies (EBs) are aggregate of cells that contain three embryonic germ layers. They can be formed by direct differentiation from pluripotent embryonic stem cells (ESCs), which serves as a useful model for understanding early embryo development. Due to the mixture of different cell types, it is necessary to investigate EBs at the single-cell level. Here, we describe a robust and straightforward method for single-cell gene expression profiling during mouse EB differentiation from mouse ESCs (mESCs). The protocol is modified from a widely used method in the SMART-seq family, which only requires standard molecular biology techniques and lab equipment. It allows for accurate 3' counting of transcript at the single-cell level, which helps reveal cellular identities during EB formation. Combined with perturbation experiments, the method provides an opportunity for mechanistic studies of embryo development at the single-cell level.
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Affiliation(s)
- Jianqun Zheng
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Ying Ye
- Cam-Su Genomic Resource Center, Soochow University, Suzhou, China
| | - Qiushi Xu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Wei Xu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Wensheng Zhang
- Department of Physiology, School of Basic Medical Sciences, Binzhou Medical University, Yantai, China. .,Cam-Su Genomic Resource Center, Soochow University, Suzhou, China.
| | - Xi Chen
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
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44
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Samad T, Wu SM. Single cell RNA sequencing approaches to cardiac development and congenital heart disease. Semin Cell Dev Biol 2021; 118:129-135. [PMID: 34006454 PMCID: PMC8434959 DOI: 10.1016/j.semcdb.2021.04.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/26/2021] [Accepted: 04/26/2021] [Indexed: 12/27/2022]
Abstract
The development of single cell RNA sequencing technologies has accelerated the ability of scientists to understand healthy and disease states of the cardiovascular system. Congenital heart defects occur in approximately 40,000 births each year and 1 out of 4 children are born with critical congenital heart disease requiring surgical interventions and a lifetime of monitoring. An understanding of how the normal heart develops and how each cell contributes to normal and pathological anatomy is an important goal in pediatric cardiovascular research. Single cell sequencing has provided the tools to increase the ability to discover rare cell types and novel genes involved in normal cardiac development. Knowledge of gene expression of single cells within cardiac tissue has contributed to the understanding of how each cell type contributes to the anatomic structures of the heart. In this review, we summarize how single cell RNA sequencing has been utilized to understand cardiac developmental processes and congenital heart disease. We discuss the advantages and disadvantages of whole cell versus single nuclei RNA sequencing and describe the approaches to analyze the interactomes, transcriptomes, and differentiation trajectory from single cell data. We summarize the currently available single cell RNA sequencing technologies and technical aspects of performing single cell analysis and how to overcome common obstacles. We also review data from the recently published human and mouse fetal heart atlases and advancements that have occurred within the field due to the application of these single cell tools. Finally we highlight the potential for single cell technologies to uncover novel mechanisms of disease pathogenesis by leveraging findings from genome wide association studies.
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Affiliation(s)
- Tahmina Samad
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA, USA; Clinical and Translational Research Program, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Sean M Wu
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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45
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Abstract
Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.
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46
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Ying P, Huang C, Wang Y, Guo X, Cao Y, Zhang Y, Fu S, Chen L, Yi G, Fu M. Single-Cell RNA Sequencing of Retina:New Looks for Gene Marker and Old Diseases. Front Mol Biosci 2021; 8:699906. [PMID: 34395530 PMCID: PMC8362665 DOI: 10.3389/fmolb.2021.699906] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 07/01/2021] [Indexed: 01/20/2023] Open
Abstract
The retina is composed of 11 types of cells, including neurons, glial cells and vascular bed cells. It contains five types of neurons, each with specific physiological, morphological, and molecular definitions. Currently, single-cell RNA sequencing (sRNA-seq) is emerging as one of the most powerful tools to reveal the complexity of the retina. The continuous discovery of retina-related gene targets plays an important role in helping us understand the nature of diseases. The revelation of new cell subpopulations can focus the occurrence and development of diseases on specific biological activities of specific cells. In addition, sRNA-seq performs high-throughput sequencing analysis of epigenetics, transcriptome and genome at the single-cell level, with the advantages of high-throughput and high-resolution. In this paper, we systematically review the development history of sRNA-seq technology, and summarize the new subtypes of retinal cells and some specific gene markers discovered by this technology. The progress in the diagnosis of retinal related diseases is also discussed.
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Affiliation(s)
- Peixi Ying
- The Second Clinical School, Southern Medical University, Guangzhou, China
| | - Chang Huang
- Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.,NHC Key Laboratory of Myopia, Fudan University, Shanghai, China.,Key Laboratory of Myopia, Chinese Academy of Medical Sciences, Shanghai, China.,Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, China
| | - Yan Wang
- Department of Ophthalmology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, China
| | - Xi Guo
- Medical College of Rehabiliation, Southern Medical University, Guangzhou, China
| | - Yuchen Cao
- The Second Clinical School, Southern Medical University, Guangzhou, China
| | - Yuxi Zhang
- The Second Clinical School, Southern Medical University, Guangzhou, China
| | - Sheng Fu
- The University of South China, Hengyang, China
| | - Lin Chen
- Department of Anesthesiology, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Guoguo Yi
- Department of Ophthalmology, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Min Fu
- Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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Cardona-Alberich A, Tourbez M, Pearce SF, Sibley CR. Elucidating the cellular dynamics of the brain with single-cell RNA sequencing. RNA Biol 2021; 18:1063-1084. [PMID: 33499699 PMCID: PMC8216183 DOI: 10.1080/15476286.2020.1870362] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 12/17/2020] [Accepted: 12/24/2020] [Indexed: 12/18/2022] Open
Abstract
Single-cell RNA-sequencing (scRNA-seq) has emerged in recent years as a breakthrough technology to understand RNA metabolism at cellular resolution. In addition to allowing new cell types and states to be identified, scRNA-seq can permit cell-type specific differential gene expression changes, pre-mRNA processing events, gene regulatory networks and single-cell developmental trajectories to be uncovered. More recently, a new wave of multi-omic adaptations and complementary spatial transcriptomics workflows have been developed that facilitate the collection of even more holistic information from individual cells. These developments have unprecedented potential to provide penetrating new insights into the basic neural cell dynamics and molecular mechanisms relevant to the nervous system in both health and disease. In this review we discuss this maturation of single-cell RNA-sequencing over the past decade, and review the different adaptations of the technology that can now be applied both at different scales and for different purposes. We conclude by highlighting how these methods have already led to many exciting discoveries across neuroscience that have furthered our cellular understanding of the neurological disease.
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Affiliation(s)
- Aida Cardona-Alberich
- Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Sciences, Edinburgh University, Edinburgh, UK
| | - Manon Tourbez
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - Sarah F. Pearce
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - Christopher R. Sibley
- Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Sciences, Edinburgh University, Edinburgh, UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
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48
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Nguyen TH, Vicidomini R, Choudhury SD, Coon SL, Iben J, Brody T, Serpe M. Single-Cell RNA Sequencing Analysis of the Drosophila Larval Ventral Cord. Curr Protoc 2021; 1:e38. [PMID: 33620770 DOI: 10.1002/cpz1.38] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Drosophila provides a powerful genetic system and an excellent model to study the development and function of the nervous system. The fly's small brain and complex behavior has been instrumental in mapping neuronal circuits and elucidating the neural basis of behavior. The fast pace of fly development and the wealth of genetic tools has enabled systematic studies on cell differentiation and fate specification, and has uncovered strategies for axon guidance and targeting. The accessibility of neuronal structures and the ability to edit and manipulate gene expression in selective cells and/or synaptic compartments has revealed mechanisms for synapse assembly and neuronal connectivity. Recent advances in single-cell RNA sequencing (scRNA-seq) have further enhanced our appreciation and understanding of neuronal diversity in a fly brain. However, due to the small size of the fly brain and its constituent cells, scRNA-seq methodologies require a few adaptations. Here, we describe a set of protocols optimized for scRNA-seq analysis of the Drosophila larval ventral nerve cord, starting from tissue dissection and cell dissociation to cDNA library preparation, sequencing, and data analysis. We apply this workflow to three separate samples and detail the technical challenges associated with successful application of scRNA-seq to studies on neuronal diversity. An accompanying article (Vicidomini, Nguyen, Choudhury, Brody, & Serpe, 2021) presents a custom multistage analysis pipeline that integrates modules contained in different R packages to ensure high-flexibility, high-quality RNA-seq data analysis. These protocols are developed for Drosophila larval ventral nerve cord, but could easily be adapted to other tissues and model organisms. © 2021 U.S. Government. Basic Protocol 1: Dissection of larval ventral nerve cords and preparation of single-cell suspensions Basic Protocol 2: Preparation and sequencing of single-cell transcriptome libraries Basic Protocol 3: Alignment of raw sequencing data to indexed genome and generation of count matrices.
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Affiliation(s)
- Tho Huu Nguyen
- Section on Cellular Communication, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - Rosario Vicidomini
- Section on Cellular Communication, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - Saumitra Dey Choudhury
- Section on Cellular Communication, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - Steven L Coon
- Molecular Genomics Core, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - James Iben
- Molecular Genomics Core, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - Thomas Brody
- Section on Cellular Communication, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
| | - Mihaela Serpe
- Section on Cellular Communication, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland
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49
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Ma SX, Lim SB. Single-Cell RNA Sequencing in Parkinson's Disease. Biomedicines 2021; 9:368. [PMID: 33916045 PMCID: PMC8066089 DOI: 10.3390/biomedicines9040368] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 03/28/2021] [Accepted: 03/30/2021] [Indexed: 02/07/2023] Open
Abstract
Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson's disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global view of cellular composition and phenotype of PD at the single-cell resolution. Here, we reviewed recent sc/snRNA-seq efforts that have successfully characterized diverse cell-type populations and identified cell type-specific disease associations in PD. We also examined how these studies have employed computational and analytical tools to analyze and interpret the rich information derived from sc/snRNA-seq. Finally, we highlighted important limitations and emerging technologies for addressing key technical challenges currently limiting the integration of new findings into clinical practice.
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Affiliation(s)
- Shi-Xun Ma
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA;
| | - Su Bin Lim
- Department of Biochemistry and Molecular Biology, Ajou University School of Medicine, Suwon 16499, Korea
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50
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Novel Technologies in Studying Brain Immune Response. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2021; 2021:6694566. [PMID: 33791073 PMCID: PMC7997736 DOI: 10.1155/2021/6694566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/25/2021] [Accepted: 03/05/2021] [Indexed: 12/13/2022]
Abstract
Over the past few decades, the immune system, including both the adaptive and innate immune systems, proved to be essential and critical to brain damage and recovery in the pathogenesis of several diseases, opening a new avenue for developing new immunomodulatory therapies and novel treatments for many neurological diseases. However, due to the specificity and structural complexity of the central nervous system (CNS), and the limit of the related technologies, the biology of the immune response in the brain is still poorly understood. Here, we discuss the application of novel technologies in studying the brain immune response, including single-cell RNA analysis, cytometry by time-of-flight, and whole-genome transcriptomic and proteomic analysis. We believe that advancements in technology related to immune research will provide an optimistic future for brain repair.
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