GeneChip analysis of human embryonic stem cell differentiation into hemangioblasts: an in silico dissection of mixed phenotypes

Abstract

Background: Microarrays are being used to understand human embryonic stem cell (hESC) differentiation. Most differentiation protocols use a multi-stage approach that induces commitment along a particular lineage. Therefore, each stage represents a more mature and less heterogeneous phenotype. Thus, characterizing the heterogeneous progenitor populations upon differentiation are of increasing importance. Here we describe a novel method of data analysis using a recently developed differentiation protocol involving the formation of functional hemangioblasts from hESCs. Blast cells are multipotent and can differentiate into multiple lineages of hematopoeitic cells (erythroid, granulocyte and macrophage), endothelial and smooth muscle cells.

Results: Large-scale transcriptional analysis was performed at distinct time points of hESC differentiation (undifferentiated hESCs, embryoid bodies, and blast cells, the last of which generates both hematopoietic and endothelial progenies). Identifying genes enriched in blast cells relative to hESCs revealed a genetic signature indicative of erythroblasts, suggesting that erythroblasts are the predominant cell type in the blast cell population. Because of the heterogeneity of blast cells, numerous comparisons were made to publicly available data sets in silico, some of which blast cells are capable of differentiating into, to assess and characterize the blast cell population. Biologically relevant comparisons masked particular genetic signatures within the heterogeneous population and identified genetic signatures indicating the presence of endothelia, cardiomyocytes, and hematopoietic lineages in the blast cell population.

Conclusion: The significance of this microarray study is in its ability to assess and identify cellular populations within a heterogeneous population through biologically relevant in silico comparisons of publicly available data sets. In conclusion, multiple in silico comparisons were necessary to characterize tissue-specific genetic signatures within a heterogeneous hemangioblast population.

Figure 1

Validation of differentially expressed genes by RT-PCR in human ESCs, EBs and BCs. (a) Total RNA from human ESCs, EBs and BCs was used to construct cDNA pools, and the expression of genes was examined by semi-quantitative PCR. The number at the top of each lane indicates the amount (microliters) of cDNA used in the 50 μL PCR reaction. M = 100 bp DNA ladder. (b) Direct and (c) indirect analysis of differentially expressed genes matched the expression patterns obtained by RT-PCR. The fold change data are presented on the y-axis using logarithm-base-10.

Figure 2

GenMAPP of complement and coagulation. Genes that are up-regulated in BCs (red), EBs (orange), and ESCs (green) compared to breast epithelia as baseline were mapped onto a pre-existing pathway. This pathway contains genes that are mostly up-regulated in BCs relative to breast epithelia.

Figure 3

GenMAPP of heme biosynthesis: Genes that are up-regulated in BCs (red), EBs (orange), and ESCs (green) compared to breast epithelia as baseline were mapped onto a heme biosynthesis pathway. This pathway contains genes that are up-regulated in BCs relative to breast epithelia.

Figure 4

Ingenuity pathway analysis shows a network of genes expressed in EB and BC data sets from the level II analysis. This network contains nodes (genes/gene products) and edges (relationships between the nodes). The shaded genes, known as focus genes, were identified by microarrays and are the starting point to generate the network. The asterisks indicate that duplicates were identified in each dataset. The EB data set contains a network of genes (VEGF, GATA4, BMP4) that are interconnected and involved in blood vessel development (VEGF), heart development (GATA4), and cellular development (BMP4). The BC data set identified a network of genes involved in cardiovascular development (SHH, RARB, TBX5, WNT11) acting through GATA4. The intensity of the node color indicates the degree of expression. Nodes are displayed using various shapes that represent the functional class of the gene product (diamond-enzymes, ovals-transcription factors, triangles-kinase, circles-others). A solid line indicates a direct interaction while a dashed line indicates an indirect interaction. A line without an arrowhead indicates binding and a plus sign indicates that othernetworks contain this gene product.

Figure 5

Ingenuity pathway analysis identified a network of genes expressed in EB and BC data sets associated with VEGF. In the EB data set, VEGF is associated with 35 'focus' genes, including KDR, FLT1, NRP1, and NRP2. In the BC data set, 13 focus genes were associated with VEGF, even though it is not present in the data set. The intensity of the node color indicates the degree of expression. Nodes are displayed using various shapes that represent the functional class of the gene product (diamond-enzymes, ovals-transcription factors, triangles-kinase, circles-others). A solid line indicates a direct interaction while a dashed line indicates an indirect interaction. A line without an arrowhead indicates binding and a plus sign indicates that othernetworks contain this gene product.

Figure 6

Ingenuity pathway analysis of a network of genes expressed in EB and BC data sets associated with GATA2. In the EB data set, the GATA2 network contained EPOR, TAL1, TCF3 and PITX2. In the BC data set, the GATA2 network contained the hemangioblastic and hematopoeitic genes TAL1, LMO2, FOG/ZFPM1, IGTA2B/CD41/GPIIb, and GATA1. The intensity of the node color indicates the degree of expression. Nodes are displayed using various shapes that represent the functional class of the gene product (diamond-enzymes, ovals-transcription factors, triangles-kinase, circles-others). A solid line indicates a direct interaction while a dashed line indicates an indirect interaction. A line without an arrowhead indicates binding and a plus sign indicates that othernetworks contain this gene product.