Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
Science. 2018 Jun 1;360(6392):981-987. doi: 10.1126/science.aar4362. Epub 2018 Apr 26.
High-throughput mapping of cellular differentiation hierarchies from single-cell data promises to empower systematic interrogations of vertebrate development and disease. Here we applied single-cell RNA sequencing to >92,000 cells from zebrafish embryos during the first day of development. Using a graph-based approach, we mapped a cell-state landscape that describes axis patterning, germ layer formation, and organogenesis. We tested how clonally related cells traverse this landscape by developing a transposon-based barcoding approach (TracerSeq) for reconstructing single-cell lineage histories. Clonally related cells were often restricted by the state landscape, including a case in which two independent lineages converge on similar fates. Cell fates remained restricted to this landscape in embryos lacking the gene. We provide web-based resources for further analysis of the single-cell data.
高通量单细胞数据解析细胞分化谱系有望实现对脊椎动物发育和疾病的系统研究。本研究利用单细胞 RNA 测序技术，对斑马鱼胚胎发育第一天的超过 92000 个细胞进行了分析。通过基于图的方法，我们构建了一个描述胚胎轴形成、胚层形成和器官发生的细胞状态图谱。我们通过开发基于转座子的条形码方法（TracerSeq）来重建单细胞谱系历史，测试了克隆相关细胞如何穿越这个状态图谱。克隆相关细胞经常受到状态图谱的限制，包括两个独立谱系趋同于相似命运的情况。在缺乏基因的胚胎中，细胞命运仍然受到这种状态图谱的限制。我们提供了基于网络的单细胞数据分析资源。
