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      Spatial profiling of chromatin accessibility in mouse and human tissues

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          Abstract

          Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context 1 . The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping 25 , but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry 6 and microfluidic deterministic barcoding 5 . Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.

          Abstract

          Spatial-ATAC-seq—spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing—delineated tissue-region-specific epigenetic landscapes in mouse embryos and identified gene regulators involved in the development of the central nervous system and the lymphoid tissue.

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          Most cited references58

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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                Author and article information

                Contributors
                goncalo.castelo-branco@ki.se
                rong.fan@yale.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                17 August 2022
                17 August 2022
                2022
                : 609
                : 7926
                : 375-383
                Affiliations
                [1 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Biomedical Engineering, , Yale University, ; New Haven, CT USA
                [2 ]GRID grid.47100.32, ISNI 0000000419368710, Yale Stem Cell Center and Yale Cancer Center, , Yale School of Medicine, ; New Haven, CT USA
                [3 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, , Karolinska Institutet, ; Stockholm, Sweden
                [4 ]GRID grid.66859.34, ISNI 0000 0004 0546 1623, Klarman Cell Observatory, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [5 ]GRID grid.21729.3f, ISNI 0000000419368729, Department of Biomedical Engineering, , Columbia University, ; New York, NY USA
                [6 ]GRID grid.21729.3f, ISNI 0000000419368729, Department of Psychiatry, , Columbia University, ; New York, NY USA
                [7 ]GRID grid.413734.6, ISNI 0000 0000 8499 1112, Division of Molecular Imaging and Neuropathology, , New York State Psychiatric Institute, ; New York, NY USA
                [8 ]GRID grid.419383.4, ISNI 0000 0001 2183 7908, Macedonian Academy of Sciences & Arts, ; Skopje, Republic of Macedonia
                [9 ]GRID grid.21729.3f, ISNI 0000000419368729, Department of Pathology and Cell Biology, , Columbia University, ; New York, NY USA
                [10 ]GRID grid.21729.3f, ISNI 0000000419368729, Department of Radiology, , Columbia University, ; New York, NY USA
                [11 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Pathology, , Yale University School of Medicine, ; New Haven, CT USA
                [12 ]GRID grid.47100.32, ISNI 0000000419368710, Section of Hematology, Department of Internal Medicine, , Yale University School of Medicine, ; New Haven, CT USA
                [13 ]GRID grid.47100.32, ISNI 0000000419368710, Yale Center for RNA Science and Medicine, , Yale University School of Medicine, ; New Haven, CT USA
                [14 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Immunobiology, , Yale University School of Medicine, ; New Haven, CT USA
                [15 ]GRID grid.21729.3f, ISNI 0000000419368729, Department of Systems Biology, , Columbia University Irving Medical Center, ; New York, NY USA
                [16 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Ming Wai Lau Centre for Reparative Medicine, Stockholm node, , Karolinska Institutet, ; Stockholm, Sweden
                [17 ]GRID grid.47100.32, ISNI 0000000419368710, Human and Translational Immunology Program, , Yale School of Medicine, ; New Haven, CT USA
                Author information
                http://orcid.org/0000-0002-9975-8086
                http://orcid.org/0000-0002-9785-7929
                http://orcid.org/0000-0001-8466-9868
                http://orcid.org/0000-0003-1228-5923
                http://orcid.org/0000-0001-7878-4923
                http://orcid.org/0000-0002-0265-6586
                http://orcid.org/0000-0001-9513-245X
                http://orcid.org/0000-0002-2737-9810
                http://orcid.org/0000-0002-1368-6756
                http://orcid.org/0000-0003-3574-7641
                http://orcid.org/0000-0003-2247-9393
                http://orcid.org/0000-0001-7805-8059
                Article
                5094
                10.1038/s41586-022-05094-1
                9452302
                35978191
                aa764b46-cc5e-4f44-a4a8-1dce32fa47ac
                © The Author(s) 2022

                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
                : 5 August 2021
                : 8 July 2022
                Categories
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                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Uncategorized
                chromatin analysis,epigenomics,fluorescence imaging,next-generation sequencing,epigenetics in the nervous system

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