title: Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types.
abstract: Pancreatic islets of Langerhans contain several specialized endocrine cell types, which are commonly identified by the expression of single marker genes. However, the established marker genes cannot capture the complete spectrum of cellular heterogeneity in human pancreatic islets, and existing bulk transcriptome datasets provide averages across several cell populations. To dissect the cellular composition of the human pancreatic islet and to establish transcriptomes for all major cell types, we performed single-cell RNA sequencing on 70 cells sorted from human primary tissue. We used this dataset to validate previously described marker genes at the single-cell level and to identify specifically expressed transcription factors for all islet cell subtypes. All data are available for browsing and download, thus establishing a useful resource of single-cell expression profiles for endocrine cells in human pancreatic islets.
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
authors.forename: Jin
authors.initials: J
authors.lastname: Li
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
authors.forename: Johanna
authors.initials: J
authors.lastname: Klughammer
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
authors.forename: Matthias
authors.initials: M
authors.lastname: Farlik
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
authors.forename: Thomas
authors.initials: T
authors.lastname: Penz
authors.affiliation: Medical University of Vienna Anna Spiegel Forschungsgebäude, Vienna, Austria.
authors.forename: Andreas
authors.initials: A
authors.lastname: Spittler
authors.affiliation: Department of Surgery, Cell Isolation and Transplantation Center, Geneva University Hospitals University of Geneva, Geneva, Switzerland.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Barbieux
authors.affiliation: Department of Surgery, Cell Isolation and Transplantation Center, Geneva University Hospitals University of Geneva, Geneva, Switzerland.
authors.forename: Ekaterine
authors.initials: E
authors.lastname: Berishvili
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria Max Planck Institute for Informatics, Saarbrücken, Germany cbock@cemm.oeaw.ac.at skubicek@cemm.oeaw.ac.at.
authors.forename: Christoph
authors.initials: C
authors.lastname: Bock
authors.affiliation: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria Christian Doppler Laboratory for Chemical Epigenetics and Antiinfectives, CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria cbock@cemm.oeaw.ac.at skubicek@cemm.oeaw.ac.at.
authors.forename: Stefan
authors.initials: S
authors.lastname: Kubicek
mesh_terms: D000328:Adult; D002478:Cells, Cultured; D020869:Gene Expression Profiling / Q000379:methods / Q000592:standards; D005819:Genetic Markers; D006801:Humans; D050417:Insulin-Secreting Cells / Q000145:classification / Q000378:metabolism*; D008297:Male; D059010:Single-Cell Analysis / Q000379:methods / Q000592:standards; D059467:Transcriptome
chemical_list: D005819:Genetic Markers
keywords: alpha cells; beta cells; diabetes; marker genes; single‐cell RNA‐seq