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1.
Figure 3

Figure 3. From: Comparative proteomic analysis of human embryonic stem cell-derived and primary human retinal pigment epithelium.

Distribution of proteins. A pie chart showing distribution of the proteins according to their biological process using Panther Classification System. The proteins were classified by their corresponding gene names. 852 of the 1041 proteins were classified into one or more of the 13 groups.

Heidi Hongisto, et al. Sci Rep. 2017;7:6016.
2.
Figure 5

Figure 5. From: Comparative proteomic analysis of human embryonic stem cell-derived and primary human retinal pigment epithelium.

Proteins involved in important RPE functions. (a) Relative mean expression levels of the 23 proteins involved in perception of light stimulus and (b) of selected important RPE proteins. Protein expression levels shown on log2 scale. Red dashed lines mark the borders for overexpression and underexpression (over 2-fold difference in expression). Error bars denote standard deviation. For the full protein names and expression values see Supplementary Table . *Quantification based on less than two peptides.

Heidi Hongisto, et al. Sci Rep. 2017;7:6016.
3.
Figure 4

Figure 4. From: Comparative proteomic analysis of human embryonic stem cell-derived and primary human retinal pigment epithelium.

Proteins involved in mitochondrial functions, stress, cytoskeleton, and proliferation. Relative expression of (a) mitochondrial, (b) cellular stress-related, (c) cytoskeletal, and (d) proliferation and cell cycle proteins in both hESC-RPE cell lines compared to hRPE. Each dot represents a single protein, presented as mean fold changes on a log2 scale, where y = 0 denotes equal protein expression. Red dashed lines mark the borders for over and under expression (2-fold difference in expression). For protein names and exact expression values in each class see Supplementary Tables –.

Heidi Hongisto, et al. Sci Rep. 2017;7:6016.
4.
Figure 1

Figure 1. From: Comparative proteomic analysis of human embryonic stem cell-derived and primary human retinal pigment epithelium.

Workflow of the study. (a) Study design of the iTRAQ proteomics. Human ESC-RPE samples from three independent differentiation experiments consisted of three replicate samples each. Human RPE samples were collected from three cadaveric donor eyes. Total protein was extracted and digested with trypsin. Peptides were labeled with iTRAQ 4-plex labels 114–117 shown in colors, and analyzed as technical duplicates with Nano-RPLC-Triple TOF instrumentation. For final data analyses the results were pooled togerther from all six LC-MS/MS analyses separately for 08/017 nad 08/023 hESC-RPE. (b) A Venn diagram illustrating the data processing before data analyses from total number of protein hits to 1041 proteins  accepted for final data analyses.

Heidi Hongisto, et al. Sci Rep. 2017;7:6016.
5.
Figure 2

Figure 2. From: Comparative proteomic analysis of human embryonic stem cell-derived and primary human retinal pigment epithelium.

Protein expression differences between hESC-RPE and hRPE. The proportions of upregulated (green) and downregulated (red) proteins according to relative expression levels of the proteins compared to hRPE for (a) 08/017 hESC-RPE and (c) 08/023 hESC-RPE. For the majority of proteins in both RPE lines, there were no differences in expression level between hESC-RPE cells and hRPE (grey). Number of proteins included = 1041. Default settings of IPA were used to conduct core pathway analysis for the over- and underexpressed proteins (188 proteins for 08/017 and 195 proteins for 08/023). Ten enriched pathways with lowest p-values for the differentially expressed proteins in (b) 08/017 and (d) 08/023 hESC-RPE compared to hRPE. Total number of genes/proteins in each pathway shown on top of each bar and percentage present in the data analysed on the y-axis (left). Up- and downregulation of the proteins in the data is shown in red and green colours respectively, and p-value (orange line) is shown in -log scale, y-axis (right). Figures in (b,c) created with IPA (Qiagen) software.

Heidi Hongisto, et al. Sci Rep. 2017;7:6016.

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