Single-cell transcriptome and accessible chromatin dynamics during endocrine pancreas development

Abstract

Delineating gene regulatory networks that orchestrate cell-type specification is a continuing challenge for developmental biologists. Single-cell analyses offer opportunities to address these challenges and accelerate discovery of rare cell lineage relationships and mechanisms underlying hierarchical lineage decisions. Here, we describe the molecular analysis of mouse pancreatic endocrine cell differentiation using single-cell transcriptomics, chromatin accessibility assays coupled to genetic labeling, and cytometry-based cell purification. We uncover transcription factor networks that delineate β-, α-, and δ-cell lineages. Through genomic footprint analysis, we identify transcription factor-regulatory DNA interactions governing pancreatic cell development at unprecedented resolution. Our analysis suggests that the transcription factor Neurog3 may act as a pioneer transcription factor to specify the pancreatic endocrine lineage. These findings could improve protocols to generate replacement endocrine cells from renewable sources, like stem cells, for diabetes therapy.

Keywords: ATAC-seq; Neurog3; pancreas; scRNA-seq.

Fig. 1.

(A) t-SNE plot showing single-cell clusters, colored by cluster. Each dot is a single cell. Cluster names are indicated on the graph. (B) Marker gene expression levels overlaid onto the t-SNE plot: Cpa1 (exocrine), Neurog3 (endocrine progenitor), and Chga (pan-endocrine). (C) Alignment of single cells onto a pseudotime trajectory beginning with duct cells and ending with hormone-producing endocrine cells. Colors represent the clusters in A. (D) Heat map representation of >2,500 differentially expressed genes during pancreatic endocrine cell differentiation, organized into different clusters. Rows represent genes, and columns represent single cells ordered by the pseudotime order. (E) Graphs representing expression trends per cluster determined by fitting a LOESS curve of average gene expression per cluster, plotted over pseudotime. Each point represents the average expression of genes within each cluster for a single cell along pseudotime. Associated GO terms are listed in the text boxes.

Fig. 2.

(A) t-SNE plot showing Neurog3-expressing cell subsets. Each dot is a single cell, colored by clusters or by (B) Neurog3 expression. (C) Box plots show normalized Neurog3 and Chga expression in each cluster. (D) Box plots show normalized hormone transcripts detected in each cluster. (E) Stacked bar plot showing the percent of cells within each cluster expressing zero, one, two, or three hormone transcripts (Ins1 or Ins2, Gcg, Sst). (F) t-SNE projection of Neurog3-expressing cells colored by the embryonic day they were isolated. (G) Pseudotime trajectory of Neurog3-expressing cells colored by the embryonic day they were isolated.

Fig. 3.

(A) (Top) t-SNE plots showing semisupervised clustering of single cells, first iteration to resolve β-lineage. Each dot is a single cell, colored by marker gene expression. (Bottom) Trajectory of cells beginning at the arrow; each dot is a single cell and is colored by marker gene expression. High expression of Ins1 and Ins2 is seen in cells at the end of the β-branch. (B) (Top) t-SNE plots showing semisupervised clustering of single cells, second iteration to resolve the α- and δ-lineages. Each dot is a single cell, colored by marker gene expression. (Bottom) Trajectory of cells beginning at the arrow; each dot is a single cell and is colored by marker gene expression. High expression of Gcg is seen on the α-branch, and Sst is seen in cells at the end of the δ-branch. (C) Bar graph indicating the percent of endocrine cells that were assigned in the appropriate branch: 88% for β-, 100% for α-, and 80% for δ-cells (D) Network showing the relationship between TF expression and cell state. The edges represent the expression specificity of TFs in each state. Thickness and color of the edges directly correspond to the expression specificity scores (ESSs) (SI Appendix, Methods). ESS values range from 0 to 1, where ESS = 1 means TF is exclusively expressed in that cell type, and ESS = 0 means no expression. Ubiquitous expression is ESS = 0.166.

Fig. 4.

(A) ATAC-seq workflow used in this study. (B) Representative FACS plots showing sorted cell populations and gating strategy. Three mouse genotypes were used to collect four types of cell populations from E15.5 embryos. (C) ATAC-seq reads obtained from different cell populations visualized on the genome browser near the gene loci: Ptf1a, Neurog3, Neurod1, Ins1. (D) Pearson’s correlation matrix showing the similarity of ATAC-seq samples. A value of 1 indicates high correlation, 0 indicates no correlation, and −1 indicates anticorrelation. The samples are colored as in A. (E) A parsimonious model for endocrine pancreas differentiation, where Neurog3 functions as a pioneer factor to shift cells from the default ductal lineage to the endocrine lineage.

Fig. 5.

(A) Heat map showing differentially open chromatin regions. Each column is an ATAC-seq sample, and each row is an open chromatin region, organized by k-means clustering. Three groups of open regions were identified and indicated on the graph. (B) Bar graphs show significant GO terms associated with open regions identified in A. (C) Position weight matrices of enriched TF motifs found in each of the three open chromatin groups.

Fig. 6.

(A) Cartoon describing how FPD and FA are calculated from ATAC-seq data. (B) Guide to interpret pairwise comparisons using a bagplot. (C–E) Bagplots displaying TFs with upregulated activity when comparing two samples. Outliers are marked by red squares, TFs in the fence are marked by blue circles, and TFs in the bag are marked by gray diamonds. Bolded TFs correspond to the de novo motifs found in the HOMER analysis. (F) Heat map showing average expression levels of outlier TFs in duct, progenitor, or endocrine cells. TFs are ordered by hierarchical clustering, and expression levels are scaled to each row. Each TF is detected in at least 25% of cells in each group.