A single-cell molecular map of mouse gastrulation and early organogenesis

By Blanca Pijuan-Sala, J. Griffiths, C. Guibentif, T. Hiscock, W. Jawaid, F. Calero-Nieto, C. Mulas, Ximena Ibarra-Soria, R. Tyser, D. Ho and 6 more. Nature, 2019

873 citations recorded by the source corpus.

Across the animal kingdom, gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult organism. Here we report the transcriptional profiles of 116,312 single cells from mouse embryos collected at nine sequential time points ranging from 6.5 to 8.5 days post-fertilization. We construct a molecular map of cellular differentiation from pluripotency towards all major embryonic lineages, and explore the complex events involved in the convergence of visceral and primitive streak-derived endoderm. Furthermore, we use single-cell profiling to show that Tal1−/− chimeric embryos display defects in early mesoderm diversification, and we thus demonstrate how combining temporal and transcriptional information can illuminate gene function. Together, this comprehensive delineation of mammalian cell differentiation trajectories in vivo represents a baseline for understanding the effects of gene mutations during development, as well as a roadmap for the optimization of in vitro differentiation protocols for regenerative medicine. Single-cell profiling is used to create a molecular-level atlas of cell differentiation trajectories during gastrulation and early organogenesis in the mouse.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/49c0e0d7e5c189110aa133a2d53560a6582cd8f7

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Citations in the corpus

Orchestrating single-cell analysis with Bioconductor (2019, background): “As scRNA-seq approaches continue to gain in popularity and decrease in cost, large-scale projects that combine and integrate independently generated datasets will become standard [72].”
A molecular cell atlas of the human lung from single cell RNA sequencing (2019, background): “The 58 identified cell populations included 15 epithelial (clusters 1-15), 9 endothelial (16-24), 9 stromal (25-33), and 25 immune (34-58) populations, greater than the number of classical cell types in each compartment (11 epithelial, 5 endothelial, 7 stromal, 20 immune, and 2 neuronal cell types) ”
Computational principles and challenges in single-cell data integration (2021, neutral): “88 ).”
High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue (2020, positive): “Despite the latest advent of massively parallel single-cell RNA-sequencing (scRNA-seq) (Klein et al., 2015; Macosko et al., 2015) that revealed astonishing cellular heterogeneity in many tissue types, including the dissection of all major cell types in developing mouse embryos from E9 to E14(Cao et ”
A human cell atlas of fetal gene expression (2020, background): “Although the germinal and embryogenesis stages have been intensively profiled with single-cell methods in humans andmice (11, 180, 181), it has been more challenging to profile the fetal stage.”
Best practices for single-cell analysis across modalities (2023, neutral): “3).”