Additional file 1 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

Additional file 1: Figure S1. Study flow chart. Single-cell RNA-sequencing. Figure S2 a-g. Enriched functions of FBs, Eps, ECs, T cells, NK cells, M cells, ast cells and neutrophils by GO and KEGG analyses. Figure S3. Single-cell RNA-seq analysis revealed distinct characterization of cell populations in endometriosis lesions, eutopic endometrium and normal endometrium. (A) Similarity analyses of each cell population in endometriosis lesions, eutopic endometrium and normal endometrium. (B) Differential expression analysis was performed comparing whole cells from endometriosis lesions, eutopic endometrium and normal endometrium. (C) Representative significantly enriched GO and KEGG processes were performed with the significantly upregulated genes in endometriosis lesions, eutopic endometrium and normal endometrium. (D) Expression of selected pathway genes were shown for each cell of endometriosis, eutopic endometrium, or normal endometrium origin. Dot size corresponded to the percentage of cells in the cluster expressing a gene, and dot color corresponded to the average expression level for the gene in the cluster. Figure S4. DEG analysis compared cells from endometriosis lesions, eutopic endometrium, and normal endometrium within ECs and Eps by heatmap. Figure S5. Immunofluorescence in cells showed the C3, C7, StAR and S100A10 positive FBs in endometriosis lesions. Figure S6. (A) Contribution of each group to each cell state on Figure 2E. The majority of state 1 was occupied by FBs from the eutopic endometrium and normal endometrium. State 2 was primarily contained by ectopic and eutopic endometrium FBs, while state 3 contained FBs from all three groups. (B) Relative contributions of FBs from13 subclusters to each group. (C) Relative contributions of FBs from three groups to each cluster, as shown by the t-SNE plot. (D)Western blot analysis reflected si-StAR transfection efficiency. (E) Scratch wound healing determined the ability of migration between si-Ctrl and si- StAR FBs. (F) Transwell assays were used to compare the effects of si- StAR on migration and invasion. (G) Proliferative ability between si-Ctrl and si- StAR FBs. (H) Representative images of flow cytometric cell cycle analysis. (I) Apoptosis of si-Ctrl and si- StAR FBs by flow cytometric. Figure S7. (A) Bar plot demonstrated the relative ratio of each subcluster to the entire T cell population. (B) Relative contributions of T cells from three groups to each cluster. (C) Contribution of each CD4+ T cells group to each cell state on Figure 6B. The majority state 1 was occupied by CD4+ T cells from eutopic endometrium and normal endometrium. State 2 contained CD4+ T cells from all three groups while half of CD4+ T cells in state 3 were from endometriosis lesions. (D) Contribution of each CD8+ T cells group to each cell state on Figure 6F. The majority of state 1 was occupied by CD8+ T cells from endometriosis lesions. Eutopic endometrium and normal endometrium and half of CD8+ T cells in state 2 were from endometriosis lesions. State 3 and state 4 contained T cells from all three groups while normal endometrium CD8+ T cells accounted for most of state 4. State 5 was mostly occupied by CD8+ T cells from eutopic and normal endometrium. (E) Bar plot demonstrated the relative ratio of each subcluster to three NK cell groups. (F) Relative contributions of T cells from three groups to each cluster. (G) Bar plot demonstrated the relative ratio of each subcluster to three M cell groups. (H) Relative contributions of M cells from three groups to each cluster. (I) Heatmap showed average expression of specific genes of M1 and M2 including CD64, CD40, CD86, CD163 and CD206. Figure S8. Functional enrichment analysis with GO and KEGG analyses of M-1, M-3, M-4, M-5, M-6, M-7, and M-9. Figure S9. The dense network and multiple cellular connection in eutopic endometrium and normal endometrium. (A) Putative signaling between differentially expressed receptors in different cell types and their ligands. Compartments represented cell types, and their preferentially expressed receptors and ligands were labeled along the outer margin. The solid line indicated that there was a significant interaction, and the dashed line indicated that it was not significant. (B) Capacity for intercellular communication between FBs and immune cells. Each line color indicated the ligands expressed by the cell population represented in the same color (labeled). The lines connected to the cell types that expressed the cognate receptors. Figure S10. (A)Heatmap of average gene expression of ESR2, PGR, StAR, CYP19A1. (B) Relative contributions of each cluster to each sample. (C) t-SNE plots of cells from each sample profiled in this study, with each cell color coded to indicate the associated cell types.

附加文件1：图S1 研究流程图。单细胞RNA测序（single-cell RNA-sequencing）。
图S2 a-g：通过基因本体（Gene Ontology, GO）和京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）分析，对成纤维细胞（Fibroblasts, FBs）、上皮细胞（Epithelial cells, Eps）、内皮细胞（Endothelial cells, ECs）、T细胞、自然杀伤细胞（Natural killer cells, NK cells）、巨噬细胞（Macrophages, M cells）、星形细胞（ast cells）及中性粒细胞开展功能富集分析。
图S3：单细胞RNA测序分析揭示子宫内膜异位症病灶、在位子宫内膜与正常子宫内膜的细胞群特征差异。(A) 子宫内膜异位症病灶、在位子宫内膜与正常子宫内膜各细胞群的相似性分析。(B) 对比子宫内膜异位症病灶、在位子宫内膜与正常子宫内膜的全部细胞，进行差异表达分析。(C) 针对上述三类样本中显著上调的基因，开展代表性显著富集的GO和KEGG通路分析。(D) 展示子宫内膜异位症、在位子宫内膜或正常子宫内膜来源的各细胞中选定通路基因的表达情况：点的大小代表该细胞簇中表达目标基因的细胞占比，点的颜色代表该细胞簇中目标基因的平均表达水平。
图S4：通过热图对内皮细胞（ECs）和上皮细胞（Eps）亚群内的子宫内膜异位症病灶、在位子宫内膜与正常子宫内膜细胞进行差异表达基因（Differentially Expressed Genes, DEG）分析。
图S5：细胞免疫荧光（immunofluorescence）检测显示，子宫内膜异位症病灶中存在C3、C7、StAR及S100A10阳性的成纤维细胞（FBs）。
图S6：(A) 各分组对图2E中各细胞状态的贡献度分析。状态1主要由在位子宫内膜与正常子宫内膜来源的成纤维细胞（FBs）占据。状态2主要包含异位与在位子宫内膜来源的成纤维细胞，而状态3则包含来自全部三个分组的成纤维细胞。(B) 13个成纤维细胞亚群对各分组的相对贡献度。(C) 三个分组来源的成纤维细胞对各细胞簇的相对贡献度，结果以t分布邻域嵌入（t-distributed Stochastic Neighbor Embedding, t-SNE）图展示。(D) 蛋白质印迹（Western blot）分析验证si-StAR的转染效率。(E) 划痕愈合实验检测si-Ctrl与si-StAR处理的成纤维细胞的迁移能力。(F) Transwell小室实验对比si-StAR对细胞迁移与侵袭能力的影响。(G) 检测si-Ctrl与si-StAR处理的成纤维细胞的增殖能力。(H) 流式细胞术（flow cytometry）细胞周期分析的代表性图像。(I) 流式细胞术检测si-Ctrl与si-StAR处理的成纤维细胞的凋亡情况。
图S7：(A) 柱状图展示各T细胞亚群占整个T细胞群的相对比例。(B) 三个分组来源的T细胞对各细胞簇的相对贡献度。(C) 各CD4+ T细胞分组对图6B中各细胞状态的贡献度分析。状态1主要由在位子宫内膜与正常子宫内膜来源的CD4+ T细胞占据。状态2包含来自全部三个分组的CD4+ T细胞，而状态3中半数CD4+ T细胞来源于子宫内膜异位症病灶。(D) 各CD8+ T细胞分组对图6F中各细胞状态的贡献度分析。状态1主要由子宫内膜异位症病灶来源的CD8+ T细胞占据。在位子宫内膜与正常子宫内膜来源的CD8+ T细胞，以及状态2中半数CD8+ T细胞均来源于子宫内膜异位症病灶。状态3与状态4包含来自全部三个分组的T细胞，而正常子宫内膜来源的CD8+ T细胞占状态4的绝大多数。状态5主要由在位与正常子宫内膜来源的CD8+ T细胞占据。(E) 柱状图展示各亚群占三个NK细胞分组的相对比例。(F) 三个分组来源的T细胞对各细胞簇的相对贡献度。(G) 柱状图展示各亚群占三个巨噬细胞（M cells）分组的相对比例。(H) 三个分组来源的巨噬细胞对各细胞簇的相对贡献度。(I) 热图展示M1型与M2型巨噬细胞的特异性基因平均表达水平，包括CD64、CD40、CD86、CD163及CD206。
图S8：对M-1、M-3、M-4、M-5、M-6、M-7及M-9开展GO与KEGG功能富集分析。
图S9：在位子宫内膜与正常子宫内膜中的密集网络及多细胞互作。(A) 不同细胞类型中差异表达的受体与其配体之间的潜在信号通路。每个区域代表一种细胞类型，其偏好表达的受体与配体标注于外缘。实线代表存在显著相互作用，虚线代表相互作用不显著。(B) 成纤维细胞与免疫细胞之间的细胞间通讯能力。每条线条的颜色代表对应颜色标注的细胞群所表达的配体，线条连接至表达相应同源受体的细胞类型。
图S10：(A) ESR2、PGR、StAR、CYP19A1的平均基因表达热图。(B) 各细胞簇对每个样本的相对贡献度。(C) 本研究中所有样本来源细胞的t-SNE图，每个细胞按其所属细胞类型进行颜色编码。