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Related Experiment Video

Updated: Dec 23, 2025

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets
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Patch-Seq Links Single-Cell Transcriptomes to Human Islet Dysfunction in Diabetes.

Joan Camunas-Soler1, Xiao-Qing Dai2, Yan Hang3

  • 1Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94518, USA.

Cell Metabolism
|April 18, 2020
PubMed
Summary

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This summary is machine-generated.

This study introduces patch-seq to link pancreatic islet cell function and gene expression. This method reveals gene networks associated with beta cell function and diabetes-related transcriptional changes.

Area of Science:

  • Endocrinology
  • Molecular Biology
  • Genomics

Background:

  • Pancreatic islet cell dysfunction significantly contributes to human metabolic diseases.
  • Directly correlating islet cell physiology with gene expression remains a challenge.

Purpose of the Study:

  • To establish a method linking single-cell physiological function with transcriptomes in human pancreatic islet cells.
  • To identify gene expression networks associated with functional heterogeneity and disease-related changes in islet cells.

Main Methods:

  • Utilized patch-seq (single-cell RNA sequencing combined with electrophysiological measurements) on 1,369 cells from 34 human donors.
  • Analyzed functional and gene expression networks to identify predictive gene sets.

Main Results:

Keywords:
T1DT2Dalpha cellbeta cellcryopreservationdiabetesisletpancreaspatch-seqsingle-cell RNA-seq

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  • Developed patch-seq to correlate endocrine physiology with transcriptomes at the single-cell level.
  • Identified a gene set linked to functional heterogeneity in beta cells, predicting electrophysiological properties.
  • Reported transcriptional programs associated with type 2 diabetes and applied the method to cryopreserved type 1 diabetes samples.

Conclusions:

  • Patch-seq is a powerful tool for dissecting islet cell heterogeneity and function in health and disease.
  • This approach provides insights into the molecular basis of metabolic dysregulation in diabetes.
  • Generated a valuable resource for future research on pancreatic islet cell biology and diabetes.