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      PCMDB: a curated and comprehensive resource of plant cell markers

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          Abstract

          The advent of single-cell sequencing opened a new era in transcriptomic and genomic research. To understand cell composition using single-cell studies, a variety of cell markers have been widely used to label individual cell types. However, the specific database of cell markers for use by the plant research community remains very limited. To overcome this problem, we developed the Plant Cell Marker DataBase (PCMDB, http://www.tobaccodb.org/pcmdb/), which is based on a uniform annotation pipeline. By manually curating over 130 000 research publications, we collected a total of 81 117 cell marker genes of 263 cell types in 22 tissues across six plant species. Tissue- and cell-specific expression patterns can be visualized using multiple tools: eFP Browser, Bar, and UMAP/TSNE graph. The PCMDB also supports several analysis tools, including SCSA and SingleR, which allows for user annotation of cell types. To provide information about plant species currently unsupported in PCMDB, potential marker genes for other plant species can be searched based on homology with the supported species. PCMDB is a user-friendly hierarchical platform that contains five built-in search engines. We believe PCMDB will constitute a useful resource for researchers working on cell type annotation and the prediction of the biological function of individual cells.

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          Most cited references32

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          Integrated analysis of multimodal single-cell data

          Summary The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce “weighted-nearest neighbor” analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.
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            Massively parallel digital transcriptional profiling of single cells

            Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.
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              Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage

              Tissue fibrosis is a major cause of mortality that results from the deposition of matrix proteins by an activated mesenchyme. Macrophages accumulate in fibrosis, but the role of specific subgroups in supporting fibrogenesis has not been investigated in vivo. Here we used single-cell RNA sequencing (scRNA-seq) to characterize the heterogeneity of macrophages in bleomycin-induced lung fibrosis in mice. A novel computational framework for the annotation of scRNA-seq by reference to bulk transcriptomes (SingleR) enabled the subclustering of macrophages and revealed a disease-associated subgroup with a transitional gene expression profile intermediate between monocyte-derived and alveolar macrophages. These CX3CR1+SiglecF+ transitional macrophages localized to the fibrotic niche and had a profibrotic effect in vivo. Human orthologues of genes expressed by the transitional macrophages were upregulated in samples from patients with idiopathic pulmonary fibrosis. Thus, we have identified a pathological subgroup of transitional macrophages that are required for the fibrotic response to injury.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                07 January 2022
                28 October 2021
                28 October 2021
                : 50
                : D1
                : D1448-D1455
                Affiliations
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Hunan Industrial Co., Ltd. , Changsha 410007, China
                Molecular Genetics Key Laboratory of China Tobacco, Guizhou Academy of Tobacco Science , Guiyang 550081, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Hunan Industrial Co., Ltd. , Changsha 410007, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                China Tobacco Hunan Industrial Co., Ltd. , Changsha 410007, China
                China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou 450001, China
                Author notes
                To whom correspondence should be addressed. Tel: +86 371 67672071; Fax: +86 371 67672071; Email: peijiancao@ 123456163.com

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Author information
                https://orcid.org/0000-0001-9683-4402
                https://orcid.org/0000-0001-9991-423X
                Article
                gkab949
                10.1093/nar/gkab949
                8728192
                34718712
                236d8b77-6dcd-441d-a242-e9fa6ccef59b
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 02 October 2021
                : 29 September 2021
                : 30 July 2021
                Page count
                Pages: 8
                Funding
                Funded by: Zhengzhou Tobacco Research Institute of CNTC, DOI 10.13039/501100008560;
                Award ID: 110202001020(JY-03)
                Award ID: 110201901024(SJ-03)
                Funded by: Joint Laboratory of HNTI and ZTRI for Tobacco Gene Research and Utilization;
                Funded by: Guizhou Academy of Tobacco Science;
                Award ID: 110202001027(JY-10)
                Funded by: China Association for Science and Technology, DOI 10.13039/100010097;
                Award ID: 2016QNRC001
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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