Re-exploring the inflammation-related core genes and modules in cerebral ischemia

Field: Neuroscience (Life Sciences)

Figure S1. (a) Clustering analysis and traits of all samples in DS1, bases on overlapped DEGs of DS1 and DS2. Colors range from light to dark red: Group – control, MCAO; Sample sites – cortex, penumbra, CA1 region of hippocampus, hemisphere, core, and striatum; ischemia time – 0 h, 0.17 h, 0.5 h, 0.75 h, 1 h, 2 h, 6 h; reperfusion time – 0 h, 2 h, 3 h, 8 h, 24 h, 48 h, 72 h. (b) Clustering analysis in 101 rat samples, bases on DEGs of rat samples. (c) Clustering analysis in DS2, bases on DS2 - DEGs, and on overlapped DEGs of DS1 and DS2. (d) Clustering analysis of the modules on eigengenes-based dissimilarity in DS1, the red line indicates the cutline, modules with dissimilarity <0.2 are merged for further analysis. (e) Correlations of Gene significance for group (A value of correlation between the group and gene expression) and Module Membership in modules (A value of correlation between a specific module and gene expression). The dots concentrated in the upper right corner represent a high correlation between modules and the group. For ¬¬group in (b) and (c): white bar - control, red bar - MCAO. Figure S2. (a) Clustering analysis of MCAO samples in DS1 on ‘TOM’-based dissimilarity. (b) Heatmap of relationships between modules and reperfusion time, the values are set as the ‘correlation coefficient (p-value)’. (c) Clustering analysis of the reperfusion time related modules on eigengenes-based dissimilarity in DS1 - MCAO samples, the red line indicates the cutline; all dissimilarities of modules > 0.8. (d) Correlations of Gene significance for ischemia time (A value of correlation between the ischemia time and gene expression) and Module Membership in modules (A value of correlation between a specific module and gene expression). The dots concentrated in the upper right corner represent a high correlation between modules and the reperfusion time. Figure S3. (a) The overlap of upregulated and downregulated DEGs in DS1 and the AD dataset GSE122063 (hypergeometric test), respectively. (b) The overlap of DS1-module genes and the AD frontal cortex DEGs in GSE122063 (hypergeometric test). (c) Heatmaps and bar-plots of eigengenes expression in the group-related-blue, turquoise, brown and purple module, respectively. (d) Venn diagrams of overall pathway and process enrichment analysis by GSEA, GSVA (DS1-DEGs as input data), and the module’s pathway and process enrichment analysis by metascape (module genes as input data). (e) Identification of core hubs in modules by overlap of module hubs and top 5% DS1-DEGs. Figure S4. (a-d) Metascape network plots of enriched terms in the blue, turquoise, brown, and purple modules, respectively. Each node represents an enriched term and is colored first by its cluster ID. Term labels are only shown for one term per cluster. Nodes marked with red border present overlapped terms of GSEA, GSVA, and metascape analysis. Figure S5. Expression of unreported core hubs in DS1. P value ≥ 0.05 is ns; 0.05>p value≥0.01 is *; 0.01>p value≥0.001 is **; 0.001>p value≥0.0001 is ***; p value<0. 0001 is ****. Table 1. Characteristics of studies in DS1, DS2 and primary cells. Table S2 Information of top 5% upregulated and downregulated DEGs in DS1. Table S3. DEGs that were obvious in both DS1 and DS2. Table S4. Module genes overlapped with cell type-specific markers and DEGs of primary cells in brain ischemia model. Table S5. Pathways and process of modules identified by metascape, GSEA and GSVA analysis. Table S6. Expression of core hub-genes of ischemia related modules. Table S7. Expression of core hub-genes of blue and turquoise modules in primary astrocyte, microglia, epithelium, macrophages from GEO datasets. Table S8. Primers in RT-qPCR analysis. Table S9. Previously-identified genes implicated in ischemic stroke and their distribution in modules or DS1-DEGs.