bioRxivCell Biology
Defining the chromatin and transcriptional landscape of stem cell-derived islets
P. Augsornworawat, N. J. Hogrebe, M. Ishahak, E. Marquez, M. M. Maestas, M. D. Schmidt, D. A. Veronese-Paniagua, S. E. Gale, J. R. Miller, L. Velazco-Cruz, J. R. Millman
Abstract
Transplantation of insulin-secreting {beta}-cells differentiated from human pluripotent stem cells holds great potential as a cell therapy for treating insulin-dependent diabetes. While these stem cell-derived islets (SC-islets) are able to reverse diabetes in animal models, they are not fully equivalent to their in vivo counterparts. To better define the state of the cell types generated within these SC-islets and provide a resource for identifying deficiencies in lineage specification, we used single-cell multiomic sequencing to simultaneously measure the chromatin accessibility and transcriptional profiles of SC-islets at multiple time points as well as primary human islets. The integrated analysis of both the transcriptional and chromatin landscape for each cell provided greater resolution for defining cell identity, allowing us to derive novel gene lists for identifying each islet cell type. Furthermore, this multiomic analysis revealed that the difference between SC-{beta} cells and enterochromaffin-like cells, which are a major off-target from in vitro differentiation, is a gradient of progressive cell states rather than a stark difference in identity. The chromatin landscape of primary human islets was much more restricted, suggesting that stem cell-derived cells are not fully locked into their cell fate. While long term culture of SC-islets both in vitro and in vivo does close overall chromatin state, only in vivo transplantation directs cells toward their correct identities. Collectively, our multiomic analysis demonstrates that both the chromatin and transcriptional landscapes play significant roles in islet cell identity, and these data can be used as a resource to identify specific deficiencies in the chromatin and transcriptional state of SC-islet cell types.
- organism: human
- assay: scRNA-seq
- assay: ATAC-seq
- research focus: cell type annotation
- approach: deep learning
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Improving stem cell-derived pancreatic islets using single-cell multiome-inferred regulomes
- Comparative and Integrative Single Cell Analysis Reveals New Insights into the Transcriptional Immaturity of Stem Cell-Derived β Cells
M. D. Schmidt, M. Ishahak, … J. R. Millman·bioRxiv·Nov 15, 2023
- High-purity stem cell-derived β-cells recapitulate key transcriptional and functional features of human islets
Rémi Fiancette, Junyue Huang, … İldem Akerman·bioRxiv·May 26, 2026
- Functional, metabolic and transcriptional maturation of stem cell derived beta cells
Diego Balboa, Tom Barsby, … Timo Otonkoski·Nature BiotechnologyPeer-reviewed·Mar 3, 2022
- Single-cell multiome analysis supports α-to-β transdifferentiation in human pancreas
Michelle Y. Y. Lee, Omar Guessoum, … Klaus H. Kaestner·bioRxiv·Feb 14, 2025
- IAPP Marks Mono-hormonal Stem-cell Derived β Cells that Maintain Stable Insulin Production in vitro and in vivo
Jeffrey C Davis, Maria Ryaboshapkina, … Douglas A. Melton·bioRxiv·Apr 10, 2024