1949_PancreaticIslet_SingleCellRNAseq
Single cell RNA sequencing (scRNA-seq) was performed on islets isolated from 15 SM/J mice representing 6 cohorts: 20wk high-fat females (n=3), 20wk high-fat males (n=3), 30wk high-fat females (n=3), 30wk high-fat males (n=2), 20wk low-fat females (n=2), and 20wk low-fat males (n=2). Isolated islets were dissociated into single cell suspensions using Accumax cell/tissue dissociation solution (Innovative Cell Technologies). Libraries were prepped using the Chromium Single Cell 3 GEM, Library & Gel Bead Kit v3 (10xGenomics) and sequenced at 2x150 paired end reads using a NovaSeq S4. After sequencing, reads were de-multiplexed and assigned to individual samples. Reads were aligned using 10x Genomics CellRanger (3.1.0) against our custom SM/J reference22. Samples that were prepped together were aggregated into batches using CellRanger aggregate. In the R environment (4.0.0), each aggregated batch was run through SoupX (1.5.0)23 to estimate and correct for ambient RNA contamination. A contamination fraction of 0.05 was chosen. Removal of Ins2 ambient RNA shown in Supplemental Figure 1D-E. Adjusted counts were imported into Seurat (3.2.2)24, where cells were filtered for number of features detected (500-3000), total counts detected (1000-30000), percent mitochondrial genes (0-30), visualized in Supplemental Figure 1A. For additional quality control, we excluded cells where nCount was not predictive of nFeature; the predictive error (residual) of a cell had to be within 3 standard deviations of the mean predictive error (~0). Cell counts for samples from one batch shown before and after filtering step shown in Supplemental Figure 1B-C. Expression was then normalized in Seurat (normalization.method = LogNormalize), batches were integrated, and clustered using a shared nearest neighbor approach. Using the top 10 principal components of the filtered expression data and a resolution of 0.14, we identified 9 clusters of cells using Clustree (0.4.3)25. Cell types were assigned by identifying top over-expressed genes for each cluster relative to all other clusters using a Wilcoxon rank sum test, with an average log-fold-change threshold of >=0.25 and requiring at least 25% of cells express the gene. Identities were assigned by comparing top over-expressed genes for each cluster with known cell-type specific markers for islet cells.