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      A single-cell atlas of the myometrium in human parturition

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          Abstract

          Parturition is a well-orchestrated process characterized by increased uterine contractility, cervical ripening, and activation of the chorioamniotic membranes; yet, the transition from a quiescent to a contractile myometrium heralds the onset of labor. However, the cellular underpinnings of human parturition in the uterine tissues are still poorly understood. Herein, we performed a comprehensive study of the human myometrium during spontaneous term labor using single-cell RNA sequencing (scRNA-Seq). First, we established a single-cell atlas of the human myometrium and unraveled the cell type–specific transcriptomic activity modulated during labor. Major cell types included distinct subsets of smooth muscle cells, monocytes/macrophages, stromal cells, and endothelial cells, all of which communicated and participated in immune (e.g., inflammation) and nonimmune (e.g., contraction) processes associated with labor. Furthermore, integrating scRNA-Seq and microarray data with deconvolution of bulk gene expression highlighted the contribution of smooth muscle cells to labor-associated contractility and inflammatory processes. Last, myometrium-derived single-cell signatures can be quantified in the maternal whole-blood transcriptome throughout pregnancy and are enriched in women in labor, providing a potential means of noninvasively monitoring pregnancy and its complications. Together, our findings provide insights into the contributions of specific myometrial cell types to the biological processes that take place during term parturition.

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          Most cited references146

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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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            Single-cell reconstruction of the early maternal–fetal interface in humans

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              Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

              It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT.
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                Author and article information

                Contributors
                Journal
                JCI Insight
                JCI Insight
                JCI Insight
                JCI Insight
                American Society for Clinical Investigation
                2379-3708
                8 March 2022
                8 March 2022
                8 March 2022
                : 7
                : 5
                : e153921
                Affiliations
                [1 ]Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services (NICHD/NIH/DHHS), Bethesda, Maryland, and Detroit, Michigan, USA.
                [2 ]Department of Obstetrics and Gynecology and
                [3 ]Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan, USA.
                [4 ]Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan, USA.
                [5 ]Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA.
                [6 ]Detroit Medical Center, Detroit, Michigan, USA.
                [7 ]Department of Computer Science, Wayne State University College of Engineering, Detroit, Michigan, USA.
                [8 ]Department of Physiology and
                [9 ]Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, Michigan, USA.
                Author notes
                Address correspondence to: Nardhy Gomez-Lopez, Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Perinatology Research Branch, NICHD/NIH/DHHS, 275 E. Hancock, Detroit, Michigan 48201, USA. Phone: 313.577.8904; Email: nardhy.gomez-lopez@ 123456wayne.edu . Or to: Roger Pique-Regi, Center for Molecular Medicine and Genetics, Department of Obstetrics and Gynecology, Wayne State University, 540 E. Canfield Ave., Detroit, Michigan 48201, USA. Phone: 313.577.0719; Email: rpique@ 123456wayne.edu . Or to: Roberto Romero, Perinatology Research Branch, NICHD/NIH/DHHS, Hutzel Women’s Hospital, 3990 John R St., Detroit, Michigan 48201, USA. Phone: 313.993.2700; Email: prbchiefstaff@ 123456med.wayne.edu .
                Author information
                http://orcid.org/0000-0002-1262-2275
                http://orcid.org/0000-0003-3243-1780
                http://orcid.org/0000-0002-2333-4746
                http://orcid.org/0000-0002-8160-8581
                http://orcid.org/0000-0002-5812-7771
                http://orcid.org/0000-0003-2014-0775
                http://orcid.org/0000-0002-8818-796X
                http://orcid.org/0000-0003-1519-5501
                http://orcid.org/0000-0003-0897-0039
                http://orcid.org/0000-0002-3406-5262
                Article
                153921
                10.1172/jci.insight.153921
                8983148
                35260533
                647ac083-bc9e-49e6-aeec-b3f90df8f15c
                © 2022 Pique-Regi et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 August 2021
                : 26 January 2022
                Funding
                Funded by: Eunice Kennedy Shriver National Institute of Child Health and Human Development, https://doi.org/10.13039/100009633;
                Award ID: HHSN275201300006C
                Funded by: Wayne State University
                Award ID: Wayne State University Perinatal Initiative in Maternal Perinatal
                Award ID: Child Health
                Categories
                Research Article

                cell biology,reproductive biology,bioinformatics,obstetrics/gynecology

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