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Cell Syst. 2016 Oct 26;3(4):385-394.e3. doi: 10.1016/j.cels.2016.09.002. Epub 2016 Sep 29.

A Single-Cell Transcriptome Atlas of the Human Pancreas.

Author information

1
Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht, the Netherlands.
2
Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht, the Netherlands; Max Planck Institute of Immunobiology and Epigenetics, 79108 Freiburg, Germany.
3
Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
4
Section of Nephrology and Section of Endocrinology, Department of Medicine, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
5
Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht, the Netherlands; Section of Nephrology and Section of Endocrinology, Department of Medicine, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. Electronic address: e.koning@hubrecht.eu.
6
Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht, the Netherlands. Electronic address: a.vanoudenaarden@hubrecht.eu.

Abstract

To understand organ function, it is important to have an inventory of its cell types and of their corresponding marker genes. This is a particularly challenging task for human tissues like the pancreas, because reliable markers are limited. Hence, transcriptome-wide studies are typically done on pooled islets of Langerhans, obscuring contributions from rare cell types and of potential subpopulations. To overcome this challenge, we developed an automated platform that uses FACS, robotics, and the CEL-Seq2 protocol to obtain the transcriptomes of thousands of single pancreatic cells from deceased organ donors, allowing in silico purification of all main pancreatic cell types. We identify cell type-specific transcription factors and a subpopulation of REG3A-positive acinar cells. We also show that CD24 and TM4SF4 expression can be used to sort live alpha and beta cells with high purity. This resource will be useful for developing a deeper understanding of pancreatic biology and pathophysiology of diabetes mellitus.

KEYWORDS:

islets of Langerhans; pancreas; sequencing; single-cell transcriptomics

PMID:
27693023
PMCID:
PMC5092539
DOI:
10.1016/j.cels.2016.09.002
[Indexed for MEDLINE]
Free PMC Article

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