资源环境科技发展态势分析平台

Macrophages are the first cells of the nascent immune system to emerge during embryonic development. In mice, embryonic macrophages infiltrate developing organs, where they differentiate symbiotically into tissue-resident macrophages (TRMs)(1). However, our understanding of the origins and specialization of macrophages in human embryos is limited. Here we isolated CD45(+) haematopoietic cells from human embryos at Carnegie stages 11 to 23 and subjected them to transcriptomic profiling by single-cell RNA sequencing, followed by functional characterization of a population of CD45(+)CD34(+)CD44(+) yolk sac-derived myeloid-biased progenitors (YSMPs) by single-cell culture. We also mapped macrophage heterogeneity across multiple anatomical sites and identified diverse subsets, including various types of embryonic TRM (in the head, liver, lung and skin). We further traced the specification trajectories of TRMs from either yolk sac-derived primitive macrophages or YSMP-derived embryonic liver monocytes using both transcriptomic and developmental staging information, with a focus on microglia. Finally, we evaluated the molecular similarities between embryonic TRMs and their adult counterparts. Our data represent a comprehensive characterization of the spatiotemporal dynamics of early macrophage development during human embryogenesis, providing a reference for future studies of the development and function of human TRMs.

Single-cell RNA sequencing of haematopoietic cells from human embryos at different developmental stages sheds light on the development and specification of macrophages in different tissues.

Cortical organoids are self-organizing three-dimensional cultures that model features of the developing human cerebral cortex(1,2). However, the fidelity of organoid models remains unclear(3-5). Here we analyse the transcriptomes of individual primary human cortical cells from different developmental periods and cortical areas. We find that cortical development is characterized by progenitor maturation trajectories, the emergence of diverse cell subtypes and areal specification of newborn neurons. By contrast, organoids contain broad cell classes, but do not recapitulate distinct cellular subtype identities and appropriate progenitor maturation. Although the molecular signatures of cortical areas emerge in organoid neurons, they are not spatially segregated. Organoids also ectopically activate cellular stress pathways, which impairs cell-type specification. However, organoid stress and subtype defects are alleviated by transplantation into the mouse cortex. Together, these datasets and analytical tools provide a framework for evaluating and improving the accuracy of cortical organoids as models of human brain development.

Single-cell RNA sequencing clarifies the development and specification of neurons in the human cortex and shows that cell stress impairs this process in cortical organoids.

Cancer develops through a process of somatic evolution(1,2). Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes(3). Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)(4), we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.