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      Cells of the human intestinal tract mapped across space and time

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      Nature
      Nature Publishing Group UK
      Cellular signalling networks, Developmental biology, Crohn's disease

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          Abstract

          The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung’s disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease.

          Abstract

          Cells from embryonic, fetal, paediatric and adult human intestinal tissue are analysed at different locations along the intestinal tract to construct a single-cell atlas of the developing and adult human intestinal tract, encompassing all cell lineages.

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            Proteomics. Tissue-based map of the human proteome.

            Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.
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              Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

              To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.
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                Author and article information

                Contributors
                k.james@garvan.org.au
                st9@sanger.ac.uk
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                8 September 2021
                8 September 2021
                2021
                : 597
                : 7875
                : 250-255
                Affiliations
                [1 ]GRID grid.10306.34, ISNI 0000 0004 0606 5382, Wellcome Sanger Institute, Wellcome Genome Campus, ; Hinxton, UK
                [2 ]GRID grid.42475.30, ISNI 0000 0004 0605 769X, Molecular Immunity Unit, Department of Medicine, University of Cambridge, , MRC Laboratory of Molecular Biology, ; Cambridge, UK
                [3 ]GRID grid.4868.2, ISNI 0000 0001 2171 1133, Centre for Immunobiology, Blizard Institute, , Queen Mary University of London, ; London, UK
                [4 ]GRID grid.5335.0, ISNI 0000000121885934, Department of Paediatrics, , University of Cambridge, ; Cambridge, UK
                [5 ]GRID grid.1006.7, ISNI 0000 0001 0462 7212, Biosciences Institute, Faculty of Medical Sciences, , Newcastle University, ; Newcastle upon Tyne, UK
                [6 ]GRID grid.83440.3b, ISNI 0000000121901201, Structural and Molecular Biology, Division of Biosciences, , University College London, ; London, UK
                [7 ]GRID grid.24029.3d, ISNI 0000 0004 0383 8386, Department of Histopathology, , Cambridge University Hospitals NHS Foundation Trust, ; Cambridge, UK
                [8 ]GRID grid.52788.30, ISNI 0000 0004 0427 7672, European Molecular Biology Laboratory, European Bioinformatics Institute, , Wellcome Genome Campus, ; Cambridge, UK
                [9 ]GRID grid.5335.0, ISNI 0000000121885934, Cancer Research UK Cambridge Institute, , University of Cambridge, ; Cambridge, UK
                [10 ]GRID grid.5335.0, ISNI 0000000121885934, John van Geest Centre for Brain Repair, Department of Clinical Neurosciences and Wellcome-MRC Cambridge Stem Cell Institute, , University of Cambridge, ; Cambridge, UK
                [11 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Translational Gastroenterology Unit, John Radcliffe Hospital, , University of Oxford, ; Oxford, UK
                [12 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Paediatrics, , University of Oxford, ; Oxford, UK
                [13 ]GRID grid.454382.c, NIHR Oxford Biomedical Research Centre, ; Oxford, UK
                [14 ]GRID grid.454369.9, Department of Surgery, , University of Cambridge and NIHR Cambridge Biomedical Research Centre, ; Cambridge, UK
                [15 ]GRID grid.24029.3d, ISNI 0000 0004 0383 8386, Department of Paediatric Gastroenterology, Hepatology and Nutrition, , Cambridge University Hospitals Trust, ; Cambridge, UK
                [16 ]GRID grid.5335.0, ISNI 0000000121885934, Wellcome-MRC Cambridge Stem Cell Institute, Anne McLaren Laboratory, , University of Cambridge, ; Cambridge, UK
                [17 ]GRID grid.420004.2, ISNI 0000 0004 0444 2244, Department of Dermatology and NIHR Newcastle Biomedical Research Centre, , Newcastle Hospitals NHS Foundation Trust, ; Newcastle upon Tyne, UK
                [18 ]GRID grid.5335.0, ISNI 0000000121885934, Theory of Condensed Matter Group, Cavendish Laboratory/Department of Physics, , University of Cambridge, ; Cambridge, UK
                [19 ]GRID grid.410697.d, Present Address: Garvan Institute of Medical Research, , The Kinghorn Cancer Centre, ; Darlinghurst, New South Wales Australia
                Author information
                http://orcid.org/0000-0001-7366-5466
                http://orcid.org/0000-0002-3557-0375
                http://orcid.org/0000-0001-6155-0821
                http://orcid.org/0000-0002-7400-7438
                http://orcid.org/0000-0001-5972-8926
                http://orcid.org/0000-0001-7293-0774
                http://orcid.org/0000-0002-1021-3021
                http://orcid.org/0000-0003-1463-8622
                http://orcid.org/0000-0001-9992-8375
                http://orcid.org/0000-0003-4306-0102
                http://orcid.org/0000-0002-8684-4655
                http://orcid.org/0000-0001-9595-4605
                http://orcid.org/0000-0002-2586-9576
                http://orcid.org/0000-0003-0757-0711
                http://orcid.org/0000-0001-9092-0852
                http://orcid.org/0000-0001-6055-277X
                http://orcid.org/0000-0001-5906-1498
                http://orcid.org/0000-0002-6111-7355
                http://orcid.org/0000-0002-1327-2334
                http://orcid.org/0000-0002-0633-3696
                http://orcid.org/0000-0002-7272-0547
                http://orcid.org/0000-0002-3927-2084
                http://orcid.org/0000-0002-7107-0650
                http://orcid.org/0000-0002-6294-6366
                Article
                3852
                10.1038/s41586-021-03852-1
                8426186
                34497389
                e76834fe-bf78-4dbb-af9f-4ab007761422
                © The Author(s) 2021

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 November 2020
                : 26 July 2021
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                © The Author(s), under exclusive licence to Springer Nature Limited 2021

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                cellular signalling networks,developmental biology,crohn's disease
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                cellular signalling networks, developmental biology, crohn's disease

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