Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

TLDR

High‑throughput mapping of cellular differentiation hierarchies from single‑cell data promises to empower systematic interrogations of vertebrate development and disease. The study aims to test how clonally related cells traverse the developmental landscape using a transposon‑based barcoding method (TracerSeq) and to provide web‑based resources for data analysis. The authors performed scRNA‑seq on over 92,000 zebrafish embryonic cells, mapped a graph‑based cell‑state landscape of axis patterning, germ layer formation, and organogenesis, and applied TracerSeq to reconstruct single‑cell lineage histories. They found that clonally related cells are largely constrained by the cell‑state landscape, with independent lineages converging on similar fates, and that this restriction persists even in chordin‑deficient embryos.

Abstract

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 chordin gene. We provide web-based resources for further analysis of the single-cell data.