Additional file 1 of Chromatin accessibility landscapes of immune cells in rheumatoid arthritis nominate monocytes in disease pathogenesis
Creators: name: Zong, Dandan
name: Huang, Beibei
name: Li, Young
name: Lu, Yichen
name: Xiang, Nan
name: Guo, Chuang
name: Liu, Qian
name: Sha, Qing
name: Du, Pengcheng
name: Yu, Qiaoni
name: Zhang, Wen
name: Cai, Pengfei
name: Sun, Yanping
name: Tao, Jinhui
name: Li, Xiaomei
name: Cai, Shanbao
name: Qu, Kun
Publisher: name: figshare
Year: 2021
Subjects: subject: Immunology
subject: FOS: Clinical medicine

description: Additional file 1: Figure S1. Immune cell sorting strategy and quality control of ATAC-seq profiles. a Gating strategy for flow cytometry. b Purity of cells after sorting by flow cytometry. c Repeatability between two replicates for ATAC-seq data. d Within 2 kb of the promoter, the reads in the ATAC-seq data were concentrated in the TSS region. e Analysis of ATAC-seq data to display representative cell markers of immune cells. OA, osteoarthritis; RA, rheumatoid arthritis. Figure S2. The chromatin accessibilities profiles for immune cells from OA patients, RA patients, and healthy donors. a Flow cytometry analysis of the proportion of monocyte subpopulations in patients with OA (n = 5) and RA (n = 8). P values were assessed using an unpaired Student’s t-test, ns: p &gt; 0.05. Error bars represent standard error of the mean (SEM). b Heatmap of chromatin dysregulation peaks obtained by comparing the ATAC-seq profiles of B cells and T cells from HDs, OA patients, and RA patients (|log2FD| &gt; 1, p &lt; 0.001 and FDR &lt; 0.1). Each column is a sample; each row is a dysregulated chromatin region. The elements were organized based on unsupervised clustering. c Representation of selected top disease ontology categories obtained from the analysis of Cluster 1–2 regions using GREAT. Samples from the same group are marked with the same colour. HD, healthy donors; OA, osteoarthritis; RA, rheumatoid arthritis; C1, cluster 1; C2, cluster 2; C3, cluster 3. Figure S3. The functional genomic characteristics of Cluster 3. a Normalized ATAC-seq profiles at the IL-1B and JAK1 loci in HD, OA and RA. Shaded regions indicate peaks that are more accessible in RA patients. b Distribution of genomic features of Cluster 3 peaks. Different genomic features are annotated with different colours. HD, healthy donor; OA, osteoarthritis; RA, rheumatoid arthritis. Figure S4. Principal component analysis based on the Cluster 1 (a) and Cluster 2 (b) regions for HDs, OA patients, and RA patients. Each dot is a sample, the samples in the figure are coloured by disease states. HD, healthy donors; OA, osteoarthritis; RA, rheumatoid arthritis. Figure S5. The relationship between peak clusters and the clinical status of patients. a, b Linear regression analysis was used to correlate RAAS with DAS28-ESR (a), TCJ, SCJ, RF, ESR, and Anti-CCP(b). The shading areas represent the 95% confidence intervals. The solid line was fit from linear regression, and the p value and the square of the coefficient of correlation (R2) were calculated using the ‘OLS’ function in the statsmodels package in Python. P value &lt; 0.05 were considered as significant. DAS28_ESR: disease activity score DAS28 based on erythrocyte sedimentation rate; SJC, joint swelling count; TJC, tender joint count; ESR, erythrocyte sedimentation rate; Anti-CCP, anti-cyclic citrullinated peptide; RF, rheumatoid factor; RAAS, RA-associated ATAC-seq score. Figure S6. Quality control of RNA-seq and ATAC-seq of CRP stimulated monocytes in vitro. a Within 2kb of the promoter, the reads in the ATAC-seq data were concentrated in the TSS region. b Repeatability between two replicates for ATAC-seq data. c Box plot showing the distribution of normalized counts for RNA-seq data. Each bar represents a sample. d Principal component analysis of CRPstim and control group based on expression of all genes. Each point is a sample, and the samples in the figure are coloured by groups. CRPstim, CRP stimulation. Figure S7. CRP stimulation promotes OC-differentiation and proinflammation in OA-derived monocytes. a Heatmap showing changes in gene expression in monocytes stimulated with CRP (10 μg/mL) for 12 hours (paired t-test p &lt; 0.05 and fold change &gt; 2). RNA-seq was performed for three independent biological replicates (monocytes derived from three different patients with OA). (right) Metascape was used to annotate genes; enriched GO terms after CRP stimulation. b, c Heatmaps show the expression levels of genes in the proinflammation (b) and regulation of OC-differentiation (c) gene sets. d Heatmap showing the expression levels of the genes of cluster 3 regions annotated by GREAT (identified in Fig. 2c). CRPstim, CRP stimulation; OC, osteoclast; C3, cluster 3. Figure S8. The functional genomic characteristics of differential regions after CRP stimulation. a Enriched GO terms of genes related to the peaks upregulated after CRP stimulation by GREAT. b Normalized ATAC-seq profiles at the CSF1R and SCIN loci in the control and CRPstim groups. Shaded regions indicate peaks that are more accessible in CRPstim. c Enriched GO terms among genes related to the peaks that became less accessible after CRP stimulation by GREAT. d Distribution of genomic features in the upregulated (left) and downregulated (right) regions after CRP stimulation. Different genomic features are annotated with different colours. Figure S9. Transcription factor motifs enrich in cluster 3. a Enrichment of transcription factor motifs in C3 for all samples. Each row is a motif, and each column is a sample. Values in the matrix indicate the significance of enrichment estimated by Genomica in terms of –Log10 p. The top ranked motifs are shown. The colour bar indicates the category of each sample: HD, healthy donor; OA, osteoarthritis; RA, rheumatoid arthritis. b Transcription factor motifs enriched in the Cluster 3 peaks using HOMER and ranked by p value.