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      Airway epithelial cell identity and plasticity are constrained by Sox2 during lung homeostasis, tissue regeneration, and in human disease

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          Abstract

          Maintenance of the cellular boundary between airway and alveolar compartments during homeostasis and after injury is essential to prohibit pathological plasticity which can reduce respiratory function. Lung injury and disease can induce either functional alveolar epithelial regeneration or dysplastic formation of keratinized epithelium which does not efficiently contribute to gas exchange. Here we show that Sox2 preserves airway cell identity and prevents fate changes into either functional alveolar tissue or pathological keratinization following lung injury. Loss of Sox2 in airway epithelium leads to a loss of airway epithelial identity with a commensurate gain in alveolar and basal cell identity, in part due to activation of Wnt signaling in secretory cells and increased Trp63 expression in intrapulmonary basal-like progenitors. In idiopathic pulmonary fibrosis, loss of SOX2 expression correlates with increased WNT signaling activity in dysplastic keratinized epithelium. SOX2-deficient dysplastic epithelial cells are also observed in COVID-19 damaged lungs. Thus, Sox2 provides a molecular barrier that suppresses airway epithelial plasticity to prevent acquisition of alveolar or basal cell identity after injury and help guide proper epithelial fate and regeneration.

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Wnt/β-Catenin Signaling, Disease, and Emerging Therapeutic Modalities.

            The WNT signal transduction cascade is a main regulator of development throughout the animal kingdom. Wnts are also key drivers of most types of tissue stem cells in adult mammals. Unsurprisingly, mutated Wnt pathway components are causative to multiple growth-related pathologies and to cancer. Here, we describe the core Wnt/β-catenin signaling pathway, how it controls stem cells, and contributes to disease. Finally, we discuss strategies for Wnt-based therapies.
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              Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

              Background Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. Results We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods. Conclusions Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression. Electronic supplementary material The online version of this article (10.1186/s12864-018-4772-0) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                emorrise@pennmedicine.upenn.edu
                Journal
                NPJ Regen Med
                NPJ Regen Med
                NPJ Regenerative Medicine
                Nature Publishing Group UK (London )
                2057-3995
                5 January 2024
                5 January 2024
                2024
                : 9
                : 2
                Affiliations
                [1 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Medicine, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [2 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Penn-CHOP Lung Biology Institute, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [3 ]Penn Cardiovascular Institute, University of Pennsylvania, ( https://ror.org/00b30xv10) Philadelphia, PA 19104 USA
                [4 ]Department of Biomedical Sciences, School of Veterinary Medicine, University of Pennsylvania, ( https://ror.org/00b30xv10) Philadelphia, PA 19104 USA
                [5 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Institute for Regenerative Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [6 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Division of Cardiovascular Surgery, Department of Surgery, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [7 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Cell and Developmental Biology, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                Author information
                http://orcid.org/0000-0002-8043-6036
                http://orcid.org/0000-0001-5740-643X
                Article
                344
                10.1038/s41536-023-00344-w
                10770358
                38182591
                b945f0e8-cfed-4201-91ea-61844b843ac0
                © The Author(s) 2024

                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/.

                History
                : 20 April 2023
                : 14 December 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000050, U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI);
                Funded by: FundRef https://doi.org/10.13039/100008732, Uehara Memorial Foundation;
                Funded by: FundRef https://doi.org/10.13039/501100007263, Astellas Foundation for Research on Metabolic Disorders;
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
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                © Springer Nature Limited 2024

                regeneration,stem-cell differentiation
                regeneration, stem-cell differentiation

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