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Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo
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Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo
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Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo
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Journal Article
Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo
2018
Overview
As embryos develop, numerous cell types with distinct functions and morphologies arise from pluripotent cells. Three research groups have used single-cell RNA sequencing to analyze the transcriptional changes accompanying development of vertebrate embryos (see the Perspective by Harland). Wagner et al. sequenced the transcriptomes of more than 90,000 cells throughout zebrafish development to reveal how cells differentiate during axis patterning, germ layer formation, and early organogenesis. Farrell et al. profiled the transcriptomes of tens of thousands of embryonic cells and applied a computational approach to construct a branching tree describing the transcriptional trajectories that lead to 25 distinct zebrafish cell types. The branching tree revealed how cells change their gene expression as they become more and more specialized. Briggs et al. examined whole frog embryos, spanning zygotic genome activation through early organogenesis, to map cell states and differentiation across all cell lineages over time. These data and approaches pave the way for the comprehensive reconstruction of transcriptional trajectories during development. Science , this issue p. 981 , p. eaar3131 , p. eaar5780 ; see also p. 967 Single-cell RNA sequencing reveals cell type trajectories and cell lineage in the developing zebrafish embryo. 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.
Publisher
The American Association for the Advancement of Science
