| Literature DB >> 26951663 |
Yurong Xin1, Jinrang Kim1, Min Ni1, Yi Wei1, Haruka Okamoto1, Joseph Lee1, Christina Adler1, Katie Cavino1, Andrew J Murphy1, George D Yancopoulos2, Hsin Chieh Lin1, Jesper Gromada2.
Abstract
This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of α-cells (5%), β-cells (92%), δ-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.Entities:
Keywords: Fluidigm C1; glucagon; insulin; pancreatic islet cells; single-cell RNA sequencing
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Year: 2016 PMID: 26951663 PMCID: PMC4812709 DOI: 10.1073/pnas.1602306113
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205