A lineage-resolved molecular atlas of C. elegans embryogenesis at single cell resolution

Abstract

C. elegans is an animal with few cells, but a striking diversity of cell types. Here, we characterize the molecular basis for their specification by profiling the transcriptomes of 84,625 single embryonic cells. We identify 284 terminal and pre-terminal cell types, mapping most single cell transcriptomes to their exact position in C. elegans' invariant lineage. We use these annotations to perform the first quantitative analysis of the relationship between lineage and the transcriptome for a whole organism. We find that a strong lineage-transcriptome correlation in the early embryo breaks down in the final two cell divisions as cells adopt their terminal fates and that most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state. Users can explore our data with a graphical application "VisCello". Main text:To understand how cell fates are specified during development, it is essential to know the temporal sequence of gene expression in cells during their trajectories from uncommitted precursors to differentiated terminal cell types. Gene expression patterns near branch points in these trajectories can help identify candidate regulators of cell fate decisions (1). Single cell RNA sequencing (sc-RNA-seq) has made it possible to obtain comprehensive measurements of Fig 3. Developmental trajectories of ciliated neurons. (A) UMAP of ciliated neurons and precursors.Colors correspond to cell identity. Text labels indicate terminal cells. Numbers 1-13 indicate parents of 1 ADE-ADA, 2 CEP-URX 3 IL1 4 OLL 5 OLQ 6 ASJ-AUA 7 ASE 8 ASI 9 ASK 10 ADF-AWB 11 ASG-AWA 12 ADL 13 AFD-RMD. 3-5, 7-9, and 12 are listed as parents of only one cell type as the sister cells die. Numbers 14-17 indicate grandparents of 14 IL1 (= IL2 parent) 15 OLQ-URY 16, 17 ASE-ASJ-AUA. 18 indicates a progenitor cluster that includes the AWC-SAAVx and BAG-SMDVx parents, which were identified in a separate UMAP (Fig. S12C). This latter analysis also tentatively identified a few cells near the base of the ASH trajectory as the ASH-RIB parent. Late stage AUA cells cluster with non-ciliated neurons and are not included in this UMAP but are included in the heatmap in panel D. The tiny cluster of cells labeled with an asterisk (*) is putatively AWC-ON based on srt-28 expression. (B) UMAP plot colored by embryo time (colors matched to Fig. 1A) and gene expression (red indicates >0 reads for the listed gene). mcm-7 is gene associated with the cell cycle. unc-130 is known to be expressed in the ASG-AWA neuroblast but neither terminal cell (40) (C) Cartoon illustrating the lineage of the ASE, ASJ, and AUA neurons. (D) Heatmap showing patterns of differential transcription factor expression associated with branches in the ASE-ASJ-AUA lineage. Expression values are log-transformed, then centered and scaled by standard deviation for each row (gene).

Developmental trajectory of pre-hematopoietic stem cell formation from endothelium

“…Data and analysis from this study can be interactively explored using a single cell EHT data explorer based on VisCello (Packer et al, 2019) and R shiny (Chang et al, 2019) (https://github.com/qinzhu/VisCello.eht).…”

“…Data generated during this study have been deposited in the Gene Expression Omnibus (GEO) with the accession number GSE137117. The EHT atlas can be interactively explored using VisCello (Packer et al, 2019) (https://github.com/qinzhu/VisCello.eht). The Department specifically disclaims responsibility for any analyses, interpretations or conclusions.…”

scATAC-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data

“…To enable interactive exploration of data in scATAC-pro, we provide an interface to VisCello [19], a visualization tool for single-cell omics data. To do this, we annotate the peaks with its nearest gene, and mark genes with their TSSs located within the peak.…”

“…Using VisCello [19], we can display chromatin accessibility values of TSS regions of several marker genes across cell clusters ( Figure 5A and Supplementary Figure 4A), such as MS4A1 (CD20) for B cells, GNLY and NKG7 for natural killer (NK) cells, CD3E for T cells, CD14, LYZ, and FCGR3A (CD16) for monocyte cells, and CST3 for dendritic cells (DC) [38]. We also displayed UCSC genome browser tracks for two example genes, CD14 ( Figure 5B) and the FCER1A (Supplementary Figure 4B).…”

“…Summary reports for both quality assessment and downstream analysis are automatically generated. Interface to an interactive single-cell data visualization tool VisCello [19] is also provided.…”