Additional file 3 of Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19
Creators: name: Ma, Yunlong
name: Qiu, Fei
name: Deng, Chunyu
name: Li, Jingjing
name: Huang, Yukuan
name: Wu, Zeyi
name: Zhou, Yijun
name: Zhang, Yaru
name: Xiong, Yichun
name: Yao, Yinghao
name: Zhong, Yigang
name: Qu, Jia
name: Su, Jianzhong
Publisher: name: figshare
Year: 2022
Subjects: subject: Immunology
subject: FOS: Clinical medicine

description: Additional file 3: Fig. S1. UMP projections of cells in PBMCs from normal controls, mild, moderate, and severe COVID-19 patients by using the Seurat R package (dataset #1). Fig. S2. Heatmap showing levels of well-known marker genes specific for each cell type in PBMCs. Fig. S3. Single-cell transcriptomes of PBMCs from normal controls, mild, moderate, and severe COVID-19 patients. Fig. S4. Hierarchical clustering using the PCC of a normalized transcriptome between controls and patients in cell type resolution. Fig. S5. Boxplots showing percentages of each cell type for PBMCs in donors from healthy control and COVID-19 patients. Fig. S6. scCODA determines the compositional differences of each cell type in PBMCs among donors from healthy control and COVID-19 patients. Fig. S7. Regional association plots for severe COVID-19-associated genetic loci based on meta-GWAS summary data. Fig. S8. Regional association plots for severe COVID-19-associated genetic loci based on meta-GWAS summary data. Fig. S9. Circus plot showing the results of MAGMA-based gene-level association analysis. Fig. S10. The 19 biological pathways enriched from the MAGMA-based pathway enrichment analysis. Fig. S11. High consistence results between MAGMA and S-MultiXcan analysis. Fig. S12. In silico permutation analysis of 100,000 times of random selections. Fig. S13. Multiple independent approaches identify genetics-relevant risk genes associated with severe COVID-19. Fig. S14. Plot of gene-drug interaction analysis for 34 risk genes. Fig. S15. The 10 biological pathways significantly enriched by 34 risk genes based on the KEGG database. Fig. S16. Barplots showing the results of RolyPoly among COVID-19 patients stratified by patient’s age. Fig. S17. Barplots showing the results of RolyPoly among COVID-19 patients stratified by patient’s sex. Fig. S18. Barplots showing the results of RolyPoly among COVID-19 patients stratified by patient’s BMI. Fig. S19. Barplots showing the results of RolyPoly COVID-19 patients stratified by patient’s smoking status. Fig. S20. Cell-ID-based enrichment in GWAS-identified gene signatures (34 genes) of CD16+monocytes and memory CD8+ T cells using scRNA-seq dataset. Fig. S21. Genetics-risk genes influenced three immune cell subsets for severe COVID-19. Fig. S22. Dot plot showing the expressed percent of three risk genes of CXCR6, CCR1, and ABO in each peripheral cell type in PBMCs among severe patients based on two scRNA-seq dataset of #2 and #3. Fig. S23. CCR1+ CD16+monocytes showing higher risk to cytokine storms among COVID-19 patients. Fig. S24. Boxplots showing the difference of inflammatory cytokine score and pathway activation score of CD16+ monocytes among normal controls and COVID-19 groups. Fig. S25. ABO+ megakaryocytes contribute higher risk to cytokine storms among severe COVID-19 patients. Fig. S26. Boxplots showing the difference of inflammatory cytokine score and pathway activation score of and megakaryocytes among normal controls and COVID-19 groups. Fig. S27. Evidence showing the multi-functionality of CXCR6+ memory CD8+T cells for severe COVID-19. Fig. S28. Boxplots showing the different score of several immunological features between CXCR6+ and CXCR6- memory CD8+T cells among normal controls and COVID-19 patients. Fig. S29. Cell-ID-based enrichment in functional terms of CD16+monocytes, megakaryocyte, and memory CD8+ T cells using scRNA-seq dataset. Fig. S30. Differences in the number of predicated cell-to-cell interactions in PBMCs. Fig. S31. Predicted cellular interaction of both CCR1+ CD16+ monocytes and CXCR6+ memory CD8+T cells with other immune cells in PBMCs. Fig. S32. Prediction of cell-to-cell interactions of cells in BALFs.