Figure 1.
Control ECs and low VWF ECFCs display global transcriptional differences. Endothelial cells from 8 cell lines (5 low VWF and 3 control lines) were sequenced via scRNA-seq (10X Genomics/Illumina). (A) After filtering and normalization, a TSNE plot was generated to determine cells that were of an endothelial vs nonendothelial nature. Endothelial cells (orange) were determined to be a cell that was positive for CDH5, PECAM1, ROBO4, ESAM, TIE1, or NOTCH4. Cells that were negative for any EC marker are shown in purple. (B) Bar graph demonstrating the overall distribution of endothelial vs nonendothelial cells (as determined by any positivity for CDH5, PECAM1, ROBO4, ESAM, TIE1, or NOTCH4) in each cell line. Bar graph represents the raw value of the number of endothelial vs nonendothelial cells in each cell line. (C) After exclusion of nonendothelial cells, a TSNE plot was regenerated to show clustering broken down by individual cell line, displayed to determine overall differences in transcriptional profiles. Each cell line is displayed in a different color. (D) After exclusion of nonendothelial cells, a TSNE plot was regenerated with endothelial cells highlighted as either control EC (red) or low VWF ECFC (blue) to determine transcriptional differences between the 2 populations. (E) Volcano plot demonstrating differential expression between control ECs and low VWF ECFCs. The y axis is the log10 of the P value, and the x axis is the −log2 value of fold change. Each individual dot represents a statistically significant differential expressed gene (P < .05) as measured by P value adjusted for multiple comparisons. Genes shown in blue are more highly expressed in control ECs compared with low VWF ECFCs, and genes shown in red are more highly expressed in low VWF ECFCs compared with control ECs. (F) IPA showing the most highly implicated pathways between control ECs and low VWF ECFCs. Pathways are ordered by the statistical strength of the activation z-score (which measures how differentially regulated a pathway is between the 2 cohorts). A positive z-score (as denoted by the darker blue on the scale) suggests that the pathway is activated in low VWF ECFCs compared with control ECs. For some pathways, shown in gray, IPA was unable to predict a directionality to the change in regulation (activation or inhibition), but there was a high degree of differentially expressed genes in that particular pathway. (G) Heatmap of the top 250 most differentially expressed genes between control ECs and low VWF ECFCs, demonstrating hierarchical clustering of the 3 control cell lines closely together.

Control ECs and low VWF ECFCs display global transcriptional differences. Endothelial cells from 8 cell lines (5 low VWF and 3 control lines) were sequenced via scRNA-seq (10X Genomics/Illumina). (A) After filtering and normalization, a TSNE plot was generated to determine cells that were of an endothelial vs nonendothelial nature. Endothelial cells (orange) were determined to be a cell that was positive for CDH5, PECAM1, ROBO4, ESAM, TIE1, or NOTCH4. Cells that were negative for any EC marker are shown in purple. (B) Bar graph demonstrating the overall distribution of endothelial vs nonendothelial cells (as determined by any positivity for CDH5, PECAM1, ROBO4, ESAM, TIE1, or NOTCH4) in each cell line. Bar graph represents the raw value of the number of endothelial vs nonendothelial cells in each cell line. (C) After exclusion of nonendothelial cells, a TSNE plot was regenerated to show clustering broken down by individual cell line, displayed to determine overall differences in transcriptional profiles. Each cell line is displayed in a different color. (D) After exclusion of nonendothelial cells, a TSNE plot was regenerated with endothelial cells highlighted as either control EC (red) or low VWF ECFC (blue) to determine transcriptional differences between the 2 populations. (E) Volcano plot demonstrating differential expression between control ECs and low VWF ECFCs. The y axis is the log10 of the P value, and the x axis is the −log2 value of fold change. Each individual dot represents a statistically significant differential expressed gene (P < .05) as measured by P value adjusted for multiple comparisons. Genes shown in blue are more highly expressed in control ECs compared with low VWF ECFCs, and genes shown in red are more highly expressed in low VWF ECFCs compared with control ECs. (F) IPA showing the most highly implicated pathways between control ECs and low VWF ECFCs. Pathways are ordered by the statistical strength of the activation z-score (which measures how differentially regulated a pathway is between the 2 cohorts). A positive z-score (as denoted by the darker blue on the scale) suggests that the pathway is activated in low VWF ECFCs compared with control ECs. For some pathways, shown in gray, IPA was unable to predict a directionality to the change in regulation (activation or inhibition), but there was a high degree of differentially expressed genes in that particular pathway. (G) Heatmap of the top 250 most differentially expressed genes between control ECs and low VWF ECFCs, demonstrating hierarchical clustering of the 3 control cell lines closely together.

Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal