five

Systematic mapping of cell state trajectories, cell lineage, and perturbations in the zebrafish embryo using single cell transcriptomics

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112294
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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 chordin-deficient embryos. We provide web-based resources for further analysis of the single-cell data. Single-cell mRNA sequencing of zebrafish embryonic cells. Samples1-7: Single cell libraries from untreated embryos (4-24 hours post-fertilization). Samples8-12: Single cell libraries from embryos injected with TracerSeq lineage cassette at the 1-cell stage. Samples13-18: Single cell libraries from embryos injected with sgRNA + Cas9 at the 1-cell stage.
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2020-05-04
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