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      Identifying Hmga2 preserving visual function by promoting a shift of Müller glia cell fate in mice with acute retinal injury

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          Abstract

          Background

          Unlike in lower vertebrates, Müller glia (MG) in adult mammalian retinas lack the ability to reprogram into neurons after retinal injury or degeneration and exhibit reactive gliosis instead. Whether a transition in MG cell fate from gliosis to reprogramming would help preserve photoreceptors is still under exploration.

          Methods

          A mouse model of retinitis pigmentosa (RP) was established using MG cell lineage tracing mice by intraperitoneal injection of sodium iodate (SI). The critical time point for the fate determination of MG gliosis was determined through immunohistochemical staining methods. Then, bulk-RNA and single-cell RNA seq techniques were used to elucidate the changes in RNA transcription of the retina and MG at that time point, and new genes that may determine the fate transition of MG were screened. Finally, the selected gene was specifically overexpressed in MG cells through adeno-associated viruses (AAV) in the mouse RP model. Bulk-RNA seq technique, immunohistochemical staining methods, and visual function testing were used to elucidate and validate the mechanism of new genes function on MG cell fate transition and retinal function.

          Results

          Here, we found the critical time point for MG gliosis fate determination was 3 days post SI injection. Hmga2 was screened out as a candidate regulator for the cell fate transition of MG. After retinal injury caused by SI, the Hmga2 protein is temporarily and lowly expressed in MG cells. Overexpression of Hmga2 in MG down-regulated glial cell related genes and up-regulated photoreceptor related genes. Besides, overexpressing Hmga2 exclusively to MG reduced MG gliosis, made MG obtain cone’s marker, and retained visual function in mice with acute retinal injury.

          Conclusion

          Our results suggested the unique reprogramming properties of Hmga2 in regulating the fate transition of MG and neuroprotective effects on the retina with acute injury. This work uncovers the reprogramming ability of epigenetic factors in MG.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13287-024-03657-9.

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          Most cited references61

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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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            featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              Integrating single-cell transcriptomic data across different conditions, technologies, and species

              Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
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                Author and article information

                Contributors
                kyao21@outlook.com
                taozui_sure@163.com
                haiweixu2001@163.com
                Journal
                Stem Cell Res Ther
                Stem Cell Res Ther
                Stem Cell Research & Therapy
                BioMed Central (London )
                1757-6512
                27 February 2024
                27 February 2024
                2024
                : 15
                : 54
                Affiliations
                [1 ]GRID grid.410570.7, ISNI 0000 0004 1760 6682, Southwest Eye Hospital, Southwest Hospital, , Third Military Medical University (Army Medical University), ; Chongqing, 400038 China
                [2 ]Key Lab of Visual Damage and Regeneration and Restoration of Chongqing, Southwest Eye Hospital, Southwest Hospital, ( https://ror.org/02jn36537) Chongqing, 400038 China
                [3 ]Department of Physiology, College of Basic Medical Sciences, Third Military Medical University (Army Medical University), ( https://ror.org/05w21nn13) Chongqing, 400038 China
                [4 ]Institute of Visual Neuroscience and Stem Cell Engineering, College of Life Sciences and Health, Wuhan University of Science and Technology, ( https://ror.org/00e4hrk88) Wuhan, 430065 China
                Author information
                http://orcid.org/0000-0002-8840-7918
                Article
                3657
                10.1186/s13287-024-03657-9
                10900711
                38414051
                ac5d1d95-dd80-481f-a192-6efc23228f80
                © 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 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 21 November 2023
                : 5 February 2024
                Funding
                Funded by: National Key Research and Development Program of China
                Award ID: 2018YFA0107302
                Award ID: 2021YFA1101203
                Award Recipient :
                Funded by: Natural Science Foundation of China
                Award ID: 31930068
                Award ID: 31970930
                Award Recipient :
                Funded by: Hubei Natural Science Foundation
                Award ID: 2020CFA069
                Award ID: 2018CFB434
                Award Recipient :
                Funded by: Chongqing Natural Science Foundation
                Award ID: CSTB2022NSCQ-MSX0185
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Molecular medicine
                hmga2,müller glia,gliosis,reprogramming,epigenetic,proliferation,bulk-rna seq,scrna seq,visual restoration

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