five

Deciphering human macrophage development at single-cell resolution

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE133345
下载链接
链接失效反馈
官方服务:
资源简介:
Macrophages are the earliest emerging cells of the nascent immune system during embryonic development, and as innate immune cells constitutes an important first-line barrier against foreign organisms and pathogens. Rodent macrophages have been shown to infiltrate multiple organs at an early stage, developing symbiotically alongside these organs becoming tissue-resident macrophages (TRM) supporting tissue development and homeostasis. However, knowledge of the development and specialization of macrophages in the early human embryo is still limited. In order to study the spatiotemporal distribution and dynamic process of macrophage development in the early human embryo, we applied single-cell transcriptomic sequencing to generate a map of all CD45+CD235a- hematopoietic cells in human embryos of successive developmental stages from Carnegie stage (CS) 11 to 23. Here, we unravelled for the first time a map of macrophage heterogeneity across multiple anatomical sites and identified multiple macrophage subsets in the early human embryo, including various types of embryonic TRM (head, liver, lung and skin), and traced their developmental trajectories from yolk sac/embryonic liver-derived macrophages to their TRM specification in the head and liver based on core transcriptional factors. Altogether, our analyses provide a comprehensive characterization of the spatial and temporal dynamics of macrophage development in the early human embryo, and provides a reference for future study into human TRM function and embryonic development. We sorted CD45+CD235a- hematopoietic cells using flow cytometry from human embryos at multiple Carnegie stages (CS11, CS12, CS13, CS15, CS17, CS20 and CS23) and sites (yolk sac, head, liver, blood, lung and skin), and then performed a modified single cell tagged reverse transcription (STRT) protocol.
创建时间:
2020-06-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作