Generation of human islet cell type-specific identity genesets
Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics m...
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| Vydáno v: | Nature communications Ročník 13; číslo 1; s. 2020 - 14 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Nature Publishing Group UK
19.04.2022
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| Abstract | Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits.
Cell therapy to replace β-cells is a potential therapeutic avenue to treat diabetes, but the production of insulin-secreting replacement cells requires reliable tools to assess islet cellular identity. Here the authors use single-cell transcriptomics meta-analysis to construct gene sets that describe the identity of human α-, β-, γ- and δ-cells. |
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| AbstractList | Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits.Cell therapy to replace β-cells is a potential therapeutic avenue to treat diabetes, but the production of insulin-secreting replacement cells requires reliable tools to assess islet cellular identity. Here the authors use single-cell transcriptomics meta-analysis to construct gene sets that describe the identity of human α-, β-, γ- and δ-cells. Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits. Cell therapy to replace β-cells is a potential therapeutic avenue to treat diabetes, but the production of insulin-secreting replacement cells requires reliable tools to assess islet cellular identity. Here the authors use single-cell transcriptomics meta-analysis to construct gene sets that describe the identity of human α-, β-, γ- and δ-cells. Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits. Abstract Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits. Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits.Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting replacement cells to treat diabetes require reliable tools to assess islet cellular identity. Here, we conduct a thorough single-cell transcriptomics meta-analysis to identify robustly expressed markers used to build genesets describing the identity of human α-, β-, γ- and δ-cells. These genesets define islet cellular identities better than previously published genesets. We show their efficacy to outline cell identity changes and unravel some of their underlying genetic mechanisms, whether during embryonic pancreas development or in experimental setups aiming at developing glucose-responsive insulin-secreting cells, such as pluripotent stem-cell differentiation or in adult islet cell reprogramming protocols. These islet cell type-specific genesets represent valuable tools that accurately benchmark gain and loss in islet cell identity traits. |
| ArticleNumber | 2020 |
| Author | Rodríguez, Iván Oropeza, Daniel Furuyama, Kenichiro van Gurp, Léon Bru-Tari, Eva Kaddis, John S. Thorel, Fabrizio Vu, Anh Nguyet Fodoulian, Leon Herrera, Pedro L. |
| Author_xml | – sequence: 1 givenname: Léon orcidid: 0000-0002-6281-5964 surname: van Gurp fullname: van Gurp, Léon organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva – sequence: 2 givenname: Leon surname: Fodoulian fullname: Fodoulian, Leon organization: Department of Genetics and Evolution, Faculty of Sciences, University of Geneva – sequence: 3 givenname: Daniel surname: Oropeza fullname: Oropeza, Daniel organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva – sequence: 4 givenname: Kenichiro orcidid: 0000-0003-4878-2841 surname: Furuyama fullname: Furuyama, Kenichiro organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Center for iPS Cell Research and Application (CiRA), Kyoto University – sequence: 5 givenname: Eva orcidid: 0000-0002-0452-3867 surname: Bru-Tari fullname: Bru-Tari, Eva organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva – sequence: 6 givenname: Anh Nguyet surname: Vu fullname: Vu, Anh Nguyet organization: Department of Diabetes & Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute – sequence: 7 givenname: John S. orcidid: 0000-0002-6752-7670 surname: Kaddis fullname: Kaddis, John S. organization: Department of Diabetes & Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute – sequence: 8 givenname: Iván orcidid: 0000-0002-6468-0565 surname: Rodríguez fullname: Rodríguez, Iván organization: Department of Genetics and Evolution, Faculty of Sciences, University of Geneva – sequence: 9 givenname: Fabrizio surname: Thorel fullname: Thorel, Fabrizio organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva – sequence: 10 givenname: Pedro L. orcidid: 0000-0003-0771-9504 surname: Herrera fullname: Herrera, Pedro L. email: pedro.herrera@unige.ch organization: Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35440614$$D View this record in MEDLINE/PubMed |
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| Snippet | Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting... Abstract Generation of surrogate cells with stable functional identities is crucial for developing cell-based therapies. Efforts to produce insulin-secreting... |
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| SubjectTerms | 13/106 13/31 38 38/32 38/91 631/337/2019 692/53/2423 692/699/2743/137 Beta cells Cell differentiation Cell Differentiation - genetics Cell therapy Diabetes Diabetes mellitus Differentiation (biology) Embryogenesis Humanities and Social Sciences Humans Insulin Insulin - genetics Insulin-Secreting Cells Islets of Langerhans Meta-analysis multidisciplinary Pluripotency Pluripotent Stem Cells Science Science (multidisciplinary) Stem cells Transcriptomics |
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| Title | Generation of human islet cell type-specific identity genesets |
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