DOI: 10.6075/j0gb22j0
title: Dermomyotome-derived endothelial cells migrate to the dorsal aorta to support hematopoietic stem cell emergence

description: Development of the dorsal aorta is a key step in the establishment of the
 adult blood-forming system since hematopoietic stem and progenitor cells
 (HSPCs) arise from ventral aortic endothelium in all vertebrate animals
 studied. Work in zebrafish has demonstrated that arterial and venous
 endothelial precursors arise from distinct subsets of lateral plate
 mesoderm. Here, we profile the transcriptome of the earliest detectable
 endothelial cells (ECs) during zebrafish embryogenesis to demonstrate that
 tissue-specific EC programs initiate much earlier than previously
 appreciated, by the end of gastrulation. Classic studies in the chick
 embryo showed that paraxial mesoderm generates a subset of somite-derived
 endothelial cells (SDECs) that incorporate into the dorsal aorta to
 replace HSPCs as they exit the aorta and enter circulation. We describe a
 conserved program in the zebrafish, where a rare population of endothelial
 precursors delaminates from the dermomyotome to incorporate exclusively
 into the developing dorsal aorta. Although SDECs lack hematopoietic
 potential, they act as a local niche to support the emergence of HSPCs
 from neighboring hemogenic endothelium. Thus, at least three subsets of
 ECs contribute to the developing dorsal aorta: vascular ECs, hemogenic
 ECs, and SDECs. Taken together, our findings indicate that the distinct
 spatial origins of endothelial precursors dictate different cellular
 potentials within the developing dorsal aorta.
description: Single-cell
 RNA sample preparation After FACS,
 total cell concentration and viability were ascertained using a TC20
 Automated Cell Counter (Bio-Rad). Samples were then resuspended in 1XPBS
 with 10% BSA at a concentration between 800-3000 per ml. Samples were
 loaded on the 10X Chromium system and processed as per manufacturer’s
 instructions (10X Genomics). Single cell libraries were prepared as per
 the manufacturer’s instructions using the Single Cell 3’ Reagent Kit v2
 (10X Genomics). Single cell RNA-seq libraries and barcode amplicons were
 sequenced on an Illumina HiSeq platform. Single-cell
 RNA sequencing analysis The Chromium 3’ sequencing
 libraries were generated using Chromium Single Cell 3’ Chip kit v3 and
 sequenced with (actually, I don’t know:( what instrument was used?). The
 Ilumina FASTQ files were used to generate filtered matrices using
 CellRanger (10X Genomics) with default parameters and imported into R for
 exploration and statistical analysis using a Seurat package (La Manno et
 al., 2018). Counts were normalized according to total expression,
 multiplied by a scale factor (10,000), and log-transformed. For cell
 cluster identification and visualization, gene expression values were also
 scaled according to highly variable genes after controlling for unwanted
 variation generated by sample identity. Cell clusters were identified
 based on UMAP of the first 14 principal components of PCA using Seurat’s
 method, Find Clusters, with an original Louvain algorithm and resolution
 parameter value 0.5. To find cluster marker genes, Seurat’s method,
 FindAllMarkers. Only genes exhibiting significant (adjusted p-value
 &lt; 0.05) a minimal average absolute log2-fold change of 0.2 between
 each of the clusters and the rest of the dataset were considered as
 differentially expressed. To merge individual datasets and to remove batch
 effects, Seurat v3 Integration and Label Transfer standard workflow
 (Stuart et al., 2019)