Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology
Transcriptome analysis enables the study of gene expression in human tissues and is a valuable tool to characterise liver function and gene expression dynamics during liver disease, as well as to identify prognostic markers or signatures, and to facilitate discovery of new therapeutic targets. In co...
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description | Transcriptome analysis enables the study of gene expression in human tissues and is a valuable tool to characterise liver function and gene expression dynamics during liver disease, as well as to identify prognostic markers or signatures, and to facilitate discovery of new therapeutic targets. In contrast to whole tissue RNA sequencing analysis, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics enables the study of transcriptional activity at the single cell or spatial level. ScRNA-seq has paved the way for the discovery of previously unknown cell types and subtypes in normal and diseased liver, facilitating the study of rare cells (such as liver progenitor cells) and the functional roles of non-parenchymal cells in chronic liver disease and cancer. By adding spatial information to scRNA-seq data, spatial transcriptomics has transformed our understanding of tissue functional organisation and cell-to-cell interactions in situ. These approaches have recently been applied to investigate liver regeneration, organisation and function of hepatocytes and non-parenchymal cells, and to profile the single cell landscape of chronic liver diseases and cancer. Herein, we review the principles and technologies behind scRNA-seq and spatial transcriptomic approaches, highlighting the recent discoveries and novel insights these methodologies have yielded in both liver physiology and disease biology. |
doi_str_mv | 10.1016/j.jhep.2020.06.004 |
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In contrast to whole tissue RNA sequencing analysis, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics enables the study of transcriptional activity at the single cell or spatial level. ScRNA-seq has paved the way for the discovery of previously unknown cell types and subtypes in normal and diseased liver, facilitating the study of rare cells (such as liver progenitor cells) and the functional roles of non-parenchymal cells in chronic liver disease and cancer. By adding spatial information to scRNA-seq data, spatial transcriptomics has transformed our understanding of tissue functional organisation and cell-to-cell interactions in situ. These approaches have recently been applied to investigate liver regeneration, organisation and function of hepatocytes and non-parenchymal cells, and to profile the single cell landscape of chronic liver diseases and cancer. Herein, we review the principles and technologies behind scRNA-seq and spatial transcriptomic approaches, highlighting the recent discoveries and novel insights these methodologies have yielded in both liver physiology and disease biology.</description><identifier>ISSN: 0168-8278</identifier><identifier>EISSN: 1600-0641</identifier><identifier>DOI: 10.1016/j.jhep.2020.06.004</identifier><identifier>PMID: 32534107</identifier><language>eng</language><publisher>AMSTERDAM: Elsevier B.V</publisher><subject>Cell Communication - drug effects ; Cell Communication - physiology ; Cell interactions ; Cirrhosis ; Drug Discovery ; Fibrosis ; Gastroenterology & Hepatology ; Gene expression ; Gene Expression Profiling - methods ; Hepatocellular carcinoma ; Hepatocytes ; Human health and pathology ; Humans ; Life Sciences ; Life Sciences & Biomedicine ; Liver - pathology ; Liver - physiology ; Liver cancer ; Liver diseases ; Liver Diseases - diagnosis ; Liver Diseases - drug therapy ; Liver Diseases - genetics ; Liver Diseases - physiopathology ; Microenvironment ; Non-parenchymal cells ; Physiology ; Progenitor cells ; Ribonucleic acid ; RNA ; Science & Technology ; Sequence analysis ; Sequence Analysis, RNA - methods ; Signal Transduction - drug effects ; Signal Transduction - physiology ; Single-cell ; Single-Cell Analysis - methods ; Single-cell RNA sequencing ; Spatial transcriptomics ; Stem cells ; Therapeutic targets ; Transcription ; Transcriptomes ; Transcriptomics ; Zonation</subject><ispartof>Journal of hepatology, 2020-11, Vol.73 (5), p.1219-1230</ispartof><rights>2020 European Association for the Study of the Liver</rights><rights>Copyright © 2020 European Association for the Study of the Liver. 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Henderson, Neil C. ; Baumert, Thomas F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c583t-86a36b790569ed2d17821fc815cb4a83766f3340dd247f88cc71ab3b317768d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Cell Communication - drug effects</topic><topic>Cell Communication - physiology</topic><topic>Cell interactions</topic><topic>Cirrhosis</topic><topic>Drug Discovery</topic><topic>Fibrosis</topic><topic>Gastroenterology & Hepatology</topic><topic>Gene expression</topic><topic>Gene Expression Profiling - methods</topic><topic>Hepatocellular carcinoma</topic><topic>Hepatocytes</topic><topic>Human health and pathology</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Life Sciences & Biomedicine</topic><topic>Liver - pathology</topic><topic>Liver - physiology</topic><topic>Liver cancer</topic><topic>Liver diseases</topic><topic>Liver Diseases - diagnosis</topic><topic>Liver Diseases - drug therapy</topic><topic>Liver Diseases - genetics</topic><topic>Liver Diseases - physiopathology</topic><topic>Microenvironment</topic><topic>Non-parenchymal cells</topic><topic>Physiology</topic><topic>Progenitor cells</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>Science & Technology</topic><topic>Sequence analysis</topic><topic>Sequence Analysis, RNA - methods</topic><topic>Signal Transduction - drug effects</topic><topic>Signal Transduction - physiology</topic><topic>Single-cell</topic><topic>Single-Cell Analysis - methods</topic><topic>Single-cell RNA sequencing</topic><topic>Spatial transcriptomics</topic><topic>Stem cells</topic><topic>Therapeutic targets</topic><topic>Transcription</topic><topic>Transcriptomes</topic><topic>Transcriptomics</topic><topic>Zonation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saviano, Antonio</creatorcontrib><creatorcontrib>Henderson, Neil C.</creatorcontrib><creatorcontrib>Baumert, Thomas F.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of hepatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saviano, Antonio</au><au>Henderson, Neil C.</au><au>Baumert, Thomas F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology</atitle><jtitle>Journal of hepatology</jtitle><stitle>J HEPATOL</stitle><addtitle>J Hepatol</addtitle><date>2020-11-01</date><risdate>2020</risdate><volume>73</volume><issue>5</issue><spage>1219</spage><epage>1230</epage><pages>1219-1230</pages><issn>0168-8278</issn><eissn>1600-0641</eissn><abstract>Transcriptome analysis enables the study of gene expression in human tissues and is a valuable tool to characterise liver function and gene expression dynamics during liver disease, as well as to identify prognostic markers or signatures, and to facilitate discovery of new therapeutic targets. In contrast to whole tissue RNA sequencing analysis, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics enables the study of transcriptional activity at the single cell or spatial level. ScRNA-seq has paved the way for the discovery of previously unknown cell types and subtypes in normal and diseased liver, facilitating the study of rare cells (such as liver progenitor cells) and the functional roles of non-parenchymal cells in chronic liver disease and cancer. By adding spatial information to scRNA-seq data, spatial transcriptomics has transformed our understanding of tissue functional organisation and cell-to-cell interactions in situ. These approaches have recently been applied to investigate liver regeneration, organisation and function of hepatocytes and non-parenchymal cells, and to profile the single cell landscape of chronic liver diseases and cancer. Herein, we review the principles and technologies behind scRNA-seq and spatial transcriptomic approaches, highlighting the recent discoveries and novel insights these methodologies have yielded in both liver physiology and disease biology.</abstract><cop>AMSTERDAM</cop><pub>Elsevier B.V</pub><pmid>32534107</pmid><doi>10.1016/j.jhep.2020.06.004</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-7585-472X</orcidid><orcidid>https://orcid.org/0000-0002-8864-2168</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Cell Communication - drug effects Cell Communication - physiology Cell interactions Cirrhosis Drug Discovery Fibrosis Gastroenterology & Hepatology Gene expression Gene Expression Profiling - methods Hepatocellular carcinoma Hepatocytes Human health and pathology Humans Life Sciences Life Sciences & Biomedicine Liver - pathology Liver - physiology Liver cancer Liver diseases Liver Diseases - diagnosis Liver Diseases - drug therapy Liver Diseases - genetics Liver Diseases - physiopathology Microenvironment Non-parenchymal cells Physiology Progenitor cells Ribonucleic acid RNA Science & Technology Sequence analysis Sequence Analysis, RNA - methods Signal Transduction - drug effects Signal Transduction - physiology Single-cell Single-Cell Analysis - methods Single-cell RNA sequencing Spatial transcriptomics Stem cells Therapeutic targets Transcription Transcriptomes Transcriptomics Zonation |
title | Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology |
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