RUNX1 and the endothelial origin of blood

Abstract

The transcription factor RUNX1 is required in the embryo for formation of the adult hematopoietic system. Here, we describe the seminal findings that led to the discovery of RUNX1 and of its critical role in blood cell formation in the embryo from hemogenic endothelium (HE). We also present RNA-sequencing data demonstrating that HE cells in different anatomic sites, which produce hematopoietic progenitors with dissimilar differentiation potentials, are molecularly distinct. Hemogenic and non-HE cells in the yolk sac are more closely related to each other than either is to hemogenic or non-HE cells in the major arteries. Therefore, a major driver of the different lineage potentials of the committed erythro-myeloid progenitors that emerge in the yolk sac versus hematopoietic stem cells that originate in the major arteries is likely to be the distinct molecular properties of the HE cells from which they are derived. We used bioinformatics analyses to predict signaling pathways active in arterial HE, which include the functionally validated pathways Notch, Wnt, and Hedgehog. We also used a novel bioinformatics approach to assemble transcriptional regulatory networks and predict transcription factors that may be specifically involved in hematopoietic cell formation from arterial HE, which is the origin of the adult hematopoietic system.

Figure 1.. Isolation and functional characterization of hemogenic endothelial (HE) and endothelial (E) cells from the arteries and yolk sac.

A) FACS gating strategy to purify HE and E cells from the arteries. Shown are profiles from E10.5 embryos. B) Purification of HE and E from yolk sacs (YS), E10.5. C) Frequency of cells that produced endothelial tubes on OP9 cells cultured with vascular endothelial growth factor (VEGF). Data from E10.5 HE and E are shown. Average frequencies are indicated above the bars. Significance determined by ANOVA and Tukey’s multiple comparisons test (mean ± 95% CI, *P < 0.05, **P < 0.01, n=3 experiments). D) Frequency of HE and E cells that produced CD45⁺ hematopoietic cells following 8–10 days of culture on OP9 stromal cells in the presence of stem cell factor (SCF), interleukin 3 (IL-3), FLT3 ligand (Flt3L) and IL-7. Data from E10.5 HE and E are shown. Significance determined by ANOVA and Tukey’s multiple comparison tests (mean ± 95% CI, **P < 0.01, n=3 experiments). E) Methylcellulose assays to enumerate colony forming units - culture (CFU-C) in sorted populations of endothelial cells, and unfractionated yolk sac cells as a control, represented as the number of CFU-Cs per embryo equivalent. Data from E10.5 samples shown. Significance determined by ANOVA and Tukey’s multiple comparison tests (mean ± SD, P < 0.0001, n = 4–8 samples, data combined from 3 experiments).

Figure 2.. Global comparison of the transcriptomes of HE and E.

A) Principle component analysis of the transcriptome data. Also shown are fetal liver (FL) HSCs and adult bone marrow (BM) HSCs for comparison. The t-distributed stochastic neighbor embedding (t-SNE) algorithm [98] yielded the same result (not shown). B) Number of differentially expressed genes based on pairwise comparisons (false discovery rate of 0.05 and fold change of 1.5). C) Enriched pathways among differentially expressed genes from each pairwise comparison of E9.5 HE and E (false discovery rate of 0.05). D) A novel computational framework for condition-specific transcriptional regulatory network (TRN) construction and identification of key transcription factors. Nodes in the TRN represent genes, and edges represent regulatory relationship between TFs and target genes. The framework first constructs a consensus TRN for each cell type by using five methods, CLR (the context likelihood of relatedness) [99], a method based on Pearson correlation [99], GENIE3 (gene network inference with ensemble of trees) [100], Inferelator [101], and TIGRESS (trustful inference of gene regulation using stability selection) [102]. Next, the framework prioritizes key TFs based on their potentials of regulating the entire set of differentially expressed genes between the two TRNs compared. Details are provided in the Supplemental Methods. E) Prioritized key TFs for E9.5 HE (artery HE plus YS HE) versus E (artery plus YS E). Shown in blue are the four TFs used by Sandler et al. and Lis et al. to convert endothelial cells into blood cells [82, 83]. Analysis of comparable E10.5 samples also prioritized Pitx1, Spi1, Runx1, Tead3, Rhox6, Tbx2, Hox8, Hbp1, Mxd1, Znf512B, and Hoxc8 (not shown). F) Prioritized key TFs for E9.5 artery versus YS HE. TFs prioritized in both E9.5 and E10.5 artery versus YS HE include Tead2, Zfp423, Mecom, Sox7, Msx1, Etv4, Rcor2, Mycl, Tbx3, Twist1, Rhox6, Hoxa4, Tcf3, and Tcf7 (not shown). G–I) Expression levels of prioritized TFs in corresponding comparisons of E9.5 HE and E. FPKM, Fragments Per Kilobase of transcript per Million mapped reads.