Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells

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 alpha-cells (5%), beta-cells (92%), delta-cells (1%) and PP-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 (23%), low sequencing quality (13%) or contamination resulting in the detection of more than one islet hormone (64%). 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. Single-cell RNA sequencing of mouse C57BL/6 pancreatic islet cells本研究针对Fluidigm C1平台（Fluidigm C1 platform）在小鼠胰岛单细胞RNA测序中的应用开展性能评估。该系统融合微流控技术与纳升级反应体系。我们共完成622个细胞的测序，成功鉴定出341个具备高质量基因表达谱的胰岛细胞。这些细胞可聚类为α细胞（5%）、β细胞（92%）、δ细胞（1%）与PP细胞（2%）四个亚群。我们鉴定出细胞类型特异性转录因子及主要参与营养感知、氧化反应与细胞信号传导的通路。出乎意料的是，共有281个细胞被排除在本次分析之外，其中因细胞活力低下占比23%、测序质量不佳占比13%，以及因检测到多种胰岛激素（提示样本污染）占比64%。综上，本研究提供了一套高质量基因表达数据集资源，有助于拓展对胰岛细胞类型相关基因与通路的认知。我们同时揭示了Fluidigm C1细胞捕获流程存在的局限性：捕获的细胞可能受到污染并出现基因表达模式异常，这提示在使用Fluidigm C1系统分析单细胞转录组数据时需谨慎。本研究针对C57BL/6小鼠胰腺胰岛细胞开展单细胞RNA测序