Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single cell zygote gives rise to millions of cells expressing a panoply of molecular programs, including much of the diversity that will subsequently be present in adult tissues. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here we set out to integrate several single cell RNA-seq datasets (scRNA-seq) that collectively span mouse gastrulation and organogenesis. To bridge technologies, these datasets were supplemented with new, intensive profiling of ~150,000 nuclei from somite-resolved E8.5 embryos with an improved combinatorial indexing protocol. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5, heuristically connect them to their pseudo-ancestors and pseudo-descendants, and for a subset of stages, deconvolve their approximate spatial distributions. Despite being constructed through automated procedures, the resulting trajectories of mammalian embryogenesis (TOME) are largely consistent with our contemporary understanding of mammalian development. We leverage TOME to nominate transcription factors (TF) and TF motifs as key regulators of each branch point at which a new cell type emerges. Finally, we apply the same procedures to single cell datasets of zebrafish and frog embryogenesis, and nominate “cell type homologs” based on shared regulators and transcriptional states.
For more details: https://www.nature.com/articles/s41588-022-01018-x
Single-cell data of each individual timepoint (Seurat object, including cell state & type columns)
Single-cell data of each individual timepoint (Seurat object, including cell state & type columns)
Single-cell data of each individual timepoint (Seurat object, including cell state & type columns)
https://github.com/ChengxiangQiu/tome_code
Department of Genome Sciences, University of Washington
Email: cxqiu@uw.edu