Literature DB >> 29700227

The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution.

James A Briggs1, Caleb Weinreb1, Daniel E Wagner1, Sean Megason1, Leonid Peshkin1, Marc W Kirschner2, Allon M Klein2.   

Abstract

Time series of single-cell transcriptome measurements can reveal dynamic features of cell differentiation pathways. From measurements of whole frog embryos spanning zygotic genome activation through early organogenesis, we derived a detailed catalog of cell states in vertebrate development and a map of differentiation across all lineages over time. The inferred map recapitulates most if not all developmental relationships and associates new regulators and marker genes with each cell state. We find that many embryonic cell states appear earlier than previously appreciated. We also assess conflicting models of neural crest development. Incorporating a matched time series of zebrafish development from a companion paper, we reveal conserved and divergent features of vertebrate early developmental gene expression programs.
Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Year:  2018        PMID: 29700227      PMCID: PMC6038144          DOI: 10.1126/science.aar5780

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  48 in total

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Journal:  Science       Date:  2017-08-18       Impact factor: 47.728

4.  The Drosophila embryo at single-cell transcriptome resolution.

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  149 in total

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4.  Blood and brain gene expression trajectories mirror neuropathology and clinical deterioration in neurodegeneration.

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Review 7.  Revolutionizing immunology with single-cell RNA sequencing.

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8.  Chloride channels regulate differentiation and barrier functions of the mammalian airway.

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9.  Centriole Number and the Accumulation of Microtubules Modulate the Timing of Apical Insertion during Radial Intercalation.

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10.  Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT.

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