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Combinatorial transcription factor profiles predict mature and functional human islet α and β cells.
- Source :
-
JCI insight [JCI Insight] 2021 Sep 22; Vol. 6 (18). Date of Electronic Publication: 2021 Sep 22. - Publication Year :
- 2021
-
Abstract
- Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic α and β cells, and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled more than 40,000 cells from normal human islets by single-cell RNA-Seq and stratified α and β cells based on combinatorial TF expression. Subpopulations of islet cells coexpressing ARX/MAFB (α cells) and MAFA/MAFB (β cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-Seq, MAFA/MAFB-coexpressing β cells showed enhanced electrophysiological activity. Thus, these results indicate that combinatorial TF expression in islet α and β cells predicts highly functional, mature subpopulations.
- Subjects :
- Adult
Electrophysiological Phenomena
Gene Expression
Glucagon-Secreting Cells physiology
Homeodomain Proteins genetics
Homeodomain Proteins metabolism
Humans
Insulin metabolism
Insulin-Secreting Cells physiology
Maf Transcription Factors, Large genetics
Maf Transcription Factors, Large metabolism
MafB Transcription Factor genetics
MafB Transcription Factor metabolism
Middle Aged
Sequence Analysis, RNA
Single-Cell Analysis
Transcriptome
Young Adult
Glucagon-Secreting Cells metabolism
Insulin-Secreting Cells metabolism
Transcription Factors genetics
Transcription Factors metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 2379-3708
- Volume :
- 6
- Issue :
- 18
- Database :
- MEDLINE
- Journal :
- JCI insight
- Publication Type :
- Academic Journal
- Accession number :
- 34428183
- Full Text :
- https://doi.org/10.1172/jci.insight.151621