1. Volume 20, Issue 7, Pages 1597-1608 (August 2017)
Chromatin and Transcriptional Analysis of Mesoderm Progenitor Cells Identifies HOPX as a Regulator of Primitive Hematopoiesis 
Nathan J. Palpant, Yuliang Wang, Brandon Hadland, Rebecca J. Zaunbrecher, Meredith Redd, Daniel Jones, Lil Pabon, Rajan Jain, Jonathan Epstein, Walter L. Ruzzo, Ying Zheng, Irwin Bernstein, Adam Margolin, Charles E. Murry 
Cell Reports 
Volume 20, Issue 7, Pages (August 2017)
DOI: /j.celrep
Copyright © 2017 The Author(s) Terms and Conditions

2. Figure 1
Gene Expression and Chromatin Dynamics Show Fidelity to Lineage-Specific Developmental Fates
(A) Schematic diagram showing lineages generated by directed differentiation of hESCs. Day 5 progenitor populations for cardiac and 2 different endothelial lineages were isolated for ChIP-seq and RNA-seq analysis.
(B) Genome-wide distribution of chromatin states into non-labeled, H3K4me3, H3K27me3, or bivalently labeled in CPCs, C-ECs, and H-ECs.
(C) Two-dimensional principal-component analysis of CPCs, C-ECs, and H-ECs as determined by expression, H3K4me3, and H3K27me3. The top 5 genes contributing to PCA1 are listed below each graph.
(D) Heatmaps for expression, H3K4me3, and H3K27me3 for a hand-collated list of known regulators of endothelial (left) and cardiac (right) fate showing appropriate lineage specificity of gene sets.
(E) Average signal for H3K4me3 and H3K27me3 chromatin dynamics 5 kb surrounding the TSS for known lineage specific structure/function genes (blue) versus lineage regulators (red) for the cardiac lineage (left) and endothelial lineage (right).
(F) Raw RNA-seq and ChIP-seq data from all 3 mesodermal progenitor populations showing the myofilament protein TNNI1 representing a structure/function gene for the cardiac lineage and the transcription factors NKX2-5 and TAL1 representing lineage regulators for the cardiac and endothelial lineages, respectively.
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3. Figure 2
Lineage-Specific Molecules Involved in Cell Fate Determination Are Enriched by Hierarchical Ranking of Genes Based on Chromatin Dynamics and Gene Expression
(A and B) Heatmap of all genes analyzed (A), which was reduced to those genes (expression and chromatin heatmaps shown) that are >2-fold higher in a given population (B). In this example, genes greater than 2-fold higher in C-ECs and H-ECs versus CPCs are shown.
(C) Equations used to generate scoring for regulator list hierarchy.
(D) Raw data and correlative score generated based on analysis of the TAL1 gene.
(E and F) Regulator lists generated using ranking algorithm outlined in (A)–(D) were analyzed by gene ontology analysis with data shown for CPCs (E) and pan-ECs (F). (i and ii) Data are presented as (i) lineage map of population under evaluation and (ii) genes ranked on the basis of cumulative score for regulators based on expression (green) or expression plus chromatin (orange). The number of genes in each regulator list is shown to the side of each graph. (iii and iv) Statistical analysis of gene ontology enrichment categories for Biological Process (iii) and Molecular Function (iv) as a comparison of regulators identified by expression alone (green) or expression plus chromatin (orange).
(G) H3K4me3 chromatin breadth 5,000 bp upstream and downstream of the TSS for putative regulators identified by expression alone (green) or expression plus chromatin (orange) in CPCs, C-ECs, and H-ECs. Raw H3K4me3 deposition around the TSS for all genes in the list are shown to the right of each graph.
Values are presented as mean ± SEM. ∗p < 0.05.
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4. Figure 3
Lineage Regulators Identified by Integrated Analysis of Chromatin Dynamics and Gene Expression and Their Temporal Expression Dynamics during Directed Differentiation
(A) Table of regulators showing those with known roles in development or disease and those with no known previous role in lineage specification.
(B and C) qRT-PCR analysis between days 2 and 5 of differentiation for all 3 mesodermal lineages. (B) NKX2-5 and TAL1 were assessed to show appropriate regulation of known regulators in a time-dependent and lineage-specific manner. (C) Assessment of the top 5 regulators in each category. All PCR products were confirmed by sequencing. n = 4–8 per time point. Values are presented as mean ± SEM.
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5. Figure 4
HOPX Identified as a Regulator of Cell Fate Determination in Hemato-endothelial Differentiation
(A) Chromatin dynamics and gene expression of the HOPX locus in day 5 C-ECs, H-ECs, and CPCs.
(B) Sashimi isoform analysis of the HOPX locus in endothelial versus cardiac differentiation showing distinct transcript profiles that differ between these lineages. Orange arrow denotes common translational start site.
(C) Construct for CRISPR/Cas9 gene targeting of a tdTomato reporter to the HOPX translational start site.
(D) FACS analysis of tdTomato mean fluorescence intensity in day 2 mesoderm cells and day 5 KDR+/CD34+ H-ECs normalized to time-matched WT cells. Raw FACS plots shown to the right. n ≥ 3 per group. Values are presented as mean ± SEM. ∗p < 0.05.
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6. Figure 5
HOPX Is Expressed during Hemato-endothelial Differentiation In Vivo
(A) Expression profiling of KDR+ cells during mouse development from days 7 to 7.75 showing upregulation of HOPX in coordination with TAL1 and ETV2.
(B) Heatmap showing key genes representing cells clustered into ten cell groups during the time course of three developmental stages, Head Fold, Neural Plate, and Primitive Streak.
(C) tSNE analysis of Neural Plate and Head Fold stage cells excluding E6.5 Epiblast cells. Color coding is as described in (A) for all cell types. HOPX expression profiling across these cell populations is shown to the right.
(D and E) The fraction of cells with expression of HOPX (D) and relative expression of HOPX (E) in different subpopulations of cells throughout hemato-endothelial development. Cell populations are color coded as described in (B).
(F) Expression analysis at single-cell level ordered by pseudotime showing downregulated (T) and upregulated (HBB-BH1) genes relative to HOPX.
Values are presented as mean ± SEM.
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7. Figure 6 HOPX Is Functionally Required for Primitive Hematopoiesis
(A) Fate specification of CD31 endothelial cells is not effected by HOPX KO.
(B–E) HOPX KO does not impact functional endothelial lumen formation assays in collagen. Scale bars, 200 μm.
(C–E) Hematopoiesis analysis of CD43+/CD235a+ derivatives in day 5 H-ECs (B) with representative FACS plots (C) and colony-forming assays in methylcellulose assaying for Ery-P (D) and macrophage CFUs (E) in WT versus HOPX KO cells. Representative CFU images are shown to the right for primitive erythroid (Ery-P), and macrophage (Mac) colonies.
(F and G) qRT-PCR analysis of HOPX and genes involved in hematoendothelial cell fate specification (SCL) and function (GATA1 and RUNX1) (F), as well as Wnt/β-catenin target genes AXIN2 and TROY1 in WT versus HOPX KO cells (G).
(H) Wnt-dependent regulation of CD43+/CD235a+ primitive hematopoiesis assessed by treatment of cells with the Wnt agonist CHIR or the Wnt antagonist XAV-939.
(I) Differentiation of HOPX KO and WT cells into H-ECs showing that addition of the Wnt inhibitor XAV-939 partially rescues hematopoietic deficiencies observed in HOPX KO cells. n = 4–8 per group. Values are presented as mean ± SEM. ∗p < 0.05 versus WT. #p < 0.05 versus HOPX KO cells.
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8. Cell Reports 2017 20, 1597-1608DOI: (10.1016/j.celrep.2017.07.067)
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