Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Center for Stem Cell and Regenerative Medicine, and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China; Zhejiang Provincial Key Laboratory for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, Zhejiang 310058, China.
Stem Cell Reports. 2023 Dec 12;18(12):2464-2481. doi: 10.1016/j.stemcr.2023.10.018. Epub 2023 Nov 22.
In vivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the in vivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.
体内人多能干细胞（hPSCs）的分化具有独特的优势，如多能性分化、血管生成和紧密的细胞间相互作用。为了系统地研究 hPSCs 的多能性分化机制，我们使用畸胎瘤模型构建了包含 239670 个细胞的体内 hPSC 分化图谱。我们鉴定了 43 种细胞类型，推断了 18 种细胞分化轨迹，并在转录组和表观遗传水平上对 hPSC 分化过程中的共同和特定基因调控模式进行了特征描述。此外，我们开发了发育单细胞基本局部比对搜索工具（dscBLAST），这是一种基于 R 的细胞识别工具，用于简化发育细胞的识别过程。使用 dscBLAST，我们将多个分化模型中的细胞与正常发育细胞进行比对，以进一步了解它们的分化状态。总之，我们的研究为干细胞分化和人类胚胎发育提供了新的见解；dscBLAST 显示出良好的细胞识别性能，为发育细胞提供了一种强大的识别工具。
