Kidder Benjamin L
Department of Oncology, Wayne State University School of Medicine, Detroit, MI, USA.
Karmanos Cancer Institute, Wayne State University School of Medicine, Detroit, MI, USA.
Nucleic Acids Res. 2024 Apr 24;52(7):3589-3606. doi: 10.1093/nar/gkae021.
Teratoma formation is key for evaluating differentiation of human pluripotent stem cells into embryonic germ layers and serves as a model for understanding stem cell differentiation and developmental processes. Its potential for insights into epigenome and transcriptome profiling is significant. This study integrates the analysis of the epigenome and transcriptome of hESC-generated teratomas, comparing transcriptomes between hESCs and teratomas. It employs cell type-specific expression patterns from single-cell data to deconvolve RNA-Seq data and identify cell types within teratomas. Our results provide a catalog of activating and repressive histone modifications, while also elucidating distinctive features of chromatin states. Construction of an epigenetic signature matrix enabled the quantification of diverse cell populations in teratomas and enhanced the ability to unravel the epigenetic landscape in heterogeneous tissue contexts. This study also includes a single cell multiome atlas of expression (scRNA-Seq) and chromatin accessibility (scATAC-Seq) of human teratomas, further revealing the complexity of these tissues. A histology-based digital staining tool further complemented the annotation of cell types in teratomas, enhancing our understanding of their cellular composition. This research is a valuable resource for examining teratoma epigenomic and transcriptomic landscapes and serves as a model for epigenetic data comparison.
畸胎瘤形成是评估人类多能干细胞向胚胎胚层分化的关键,也是理解干细胞分化和发育过程的模型。其在深入了解表观基因组和转录组图谱方面具有重要潜力。本研究整合了人胚胎干细胞衍生的畸胎瘤的表观基因组和转录组分析,比较了人胚胎干细胞和畸胎瘤之间的转录组。它利用单细胞数据中的细胞类型特异性表达模式对RNA测序数据进行反卷积,并识别畸胎瘤内的细胞类型。我们的结果提供了激活和抑制组蛋白修饰的目录,同时也阐明了染色质状态的独特特征。表观遗传特征矩阵的构建能够对畸胎瘤中的多种细胞群体进行定量,并增强了在异质组织环境中解析表观遗传景观的能力。本研究还包括人类畸胎瘤的单细胞多组学表达图谱(scRNA-Seq)和染色质可及性图谱(scATAC-Seq),进一步揭示了这些组织的复杂性。一种基于组织学的数字染色工具进一步补充了畸胎瘤中细胞类型的注释,增强了我们对其细胞组成的理解。这项研究是检查畸胎瘤表观基因组和转录组景观的宝贵资源,也是表观遗传数据比较的模型。