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Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations

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      Abstract

      The liver is the largest solid organ in the body and is critical for metabolic and immune functions. However, little is known about the cells that make up the human liver and its immune microenvironment. Here we report a map of the cellular landscape of the human liver using single-cell RNA sequencing. We provide the transcriptional profiles of 8444 parenchymal and non-parenchymal cells obtained from the fractionation of fresh hepatic tissue from five human livers. Using gene expression patterns, flow cytometry, and immunohistochemical examinations, we identify 20 discrete cell populations of hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, B cells, conventional and non-conventional T cells, NK-like cells, and distinct intrahepatic monocyte/macrophage populations. Together, our study presents a comprehensive view of the human liver at single-cell resolution that outlines the characteristics of resident cells in the liver, and in particular provides a map of the human hepatic immune microenvironment.

      Abstract

      The development of single cell RNA sequencing technologies has been instrumental in advancing our understanding of tissue biology. Here, MacParland et al. performed single cell RNA sequencing of human liver samples, and identify distinct populations of intrahepatic macrophages that may play specific roles in liver disease.

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      Most cited references 93

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      Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

      Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.
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        Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

        Background Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal. Principal Findings To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed “Enrichment Map”, a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results. Conclusions Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).
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          A lineage of myeloid cells independent of Myb and hematopoietic stem cells.

          Macrophages and dendritic cells (DCs) are key components of cellular immunity and are thought to originate and renew from hematopoietic stem cells (HSCs). However, some macrophages develop in the embryo before the appearance of definitive HSCs. We thus reinvestigated macrophage development. We found that the transcription factor Myb was required for development of HSCs and all CD11b(high) monocytes and macrophages, but was dispensable for yolk sac (YS) macrophages and for the development of YS-derived F4/80(bright) macrophages in several tissues, such as liver Kupffer cells, epidermal Langerhans cells, and microglia--cell populations that all can persist in adult mice independently of HSCs. These results define a lineage of tissue macrophages that derive from the YS and are genetically distinct from HSC progeny.
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            Author and article information

            Affiliations
            [1 ]ISNI 0000 0001 0661 1177, GRID grid.417184.f, Multi-Organ Transplant Program, , Toronto General Hospital Research Institute, ; Toronto, ON M5G 2C4 Canada
            [2 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Immunology, , University of Toronto, ; Toronto, ON M5S 1A8 Canada
            [3 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Laboratory Medicine and Pathobiology, , University of Toronto, ; Toronto, M5G 1L7 Canada
            [4 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, The Donnelly Centre, , University of Toronto, ; Toronto, ON M5S 3E1 Canada
            [5 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Molecular Genetics, , University of Toronto, ; Toronto, M5G 1A8 Canada
            [6 ]ISNI 0000 0004 0474 0428, GRID grid.231844.8, McEwen Centre for Regenerative Medicine, , University Health Network, ; Toronto, ON M5G 1L7 Canada
            [7 ]ISNI 0000 0004 0474 0428, GRID grid.231844.8, Princess Margaret Genomics Centre, , University Health Network, ; Toronto, ON M5G 1L7 Canada
            [8 ]ISNI 0000 0004 0473 9646, GRID grid.42327.30, Genetics and Genome Biology, , Hospital for Sick Children, ; Toronto, M5G 0A4 Canada
            [9 ]ISNI 0000 0001 0661 1177, GRID grid.417184.f, Division of Advanced Diagnostics, , Toronto General Hospital Research Institute, ; Toronto, ON M5G 2C4 Canada
            [10 ]ISNI 0000 0004 0474 0428, GRID grid.231844.8, Laboratory Medicine Program, , University Health Network, Toronto, ; Ontario, M5G 1L7 Canada
            [11 ]ISNI 0000 0004 0474 0428, GRID grid.231844.8, Princess Margaret Cancer Centre, , University Health Network, Toronto, ; Ontario, M5G 1L7 Canada
            [12 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Medical Biophysics, , University of Toronto, ; Toronto, ON M5G 1L7 Canada
            Contributors
            s.macparland@utoronto.ca
            ORCID: http://orcid.org/0000-0003-0185-8861, gary.bader@utoronto.ca
            Ian.McGilvray@uhn.ca
            Journal
            Nat Commun
            Nat Commun
            Nature Communications
            Nature Publishing Group UK (London )
            2041-1723
            22 October 2018
            22 October 2018
            2018
            : 9
            6197289 6318 10.1038/s41467-018-06318-7
            © The Author(s) 2018

            Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

            Funding
            Funded by: This work was supported in part by start-up funds from the Multi-organ Transplant Program at UHN to SAM. This research was funded in part by the University of Toronto’s Medicine by Design initiative, which receives funding from the Canada First Research Excellence Fund (CFREF) to GK, IDM. This work was supported by NRNB (U.S. National Institutes of Health, grant P41 GM103504) to GDB.
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