HCA Data Explorer

A Single-Cell Transcriptome Atlas of the Human Pancreas.

Updated November 29, 2023

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.

Mauro J MuraroHubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrechtm.muraro@scdiscoveries.com
Alexander van OudenaardenHubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrechta.vanoudenaarden@hubrecht.eu
Mauro J Muraro (Experimental Scientist)1
Gitanjali Dharmadhikari2
Dominic Grün3
Nathalie Groen4
Tim Dielen2
Erik Jansen2
Leon van Gurp2
Marten A Engelse5
Francoise Carlotti4
Eelco J P de Koning6
Alexander van Oudenaarden (Principal Investigator)1
1Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht
2Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, Cancer Genomics Netherlands, 3584 CT Utrecht, the Netherlands.
3Hubrecht 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.
4Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
5Section of Nephrology and Section of Endocrinology, Department of Medicine, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
6Hubrecht 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.
Rachel Schwartz

To reference this project, please use the following link:

https://explore.data.humancellatlas.dev.clevercanary.com/projects/894ae6ac-5b48-41a8-a72f-315a9b60a62e
None
INSDC Project Accessions:GEO Series Accessions:INSDC Study Accessions:

Atlas

None

Analysis Portals

CZ CELLxGENECZ CELLxGENE

Project Label

pancreasCelSeq2

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

pancreas

Organ Part

islet of Langerhans

Selected Cell Types

Unspecified

Disease Status (Specimen)

normal

Disease Status (Donor)

normal

Development Stage

human adult stage

Library Construction Method

CEL-seq2

Nucleic Acid Source

single cell

Paired End

true

Analysis Protocol

cel_seq_analysis_1, cel_seq_analysis_2

File Format

3 file formats

Cell Count Estimate

12.3k

Donor Count

4
csv.gz2 file(s)fastq.gz62 file(s)xlsx1 file(s)