A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages
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ABSTRACT:
ORGANISM(S): Xenopus tropicalis Xenopus laevis
PROVIDER: GSE198494 | GEO | 2024/03/29
REPOSITORIES: GEO
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Project description:A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages
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2024-03-29 | GSE198493 | GEO
Project description:Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of molecular choices governing the emergence of neural crest heterogeneity from the ectoderm remains elusive. Gene regulatory networks govern these steps of embryonic development and cell specification towards definitive neural crest. Here, we combine ultra-dense single cell transcriptomes with machine-learning strategies and experimental validation to provide a comprehensive gene regulatory network driving vertebrate neural crest fate diversification, from induction to early migration stages. Transcription factor connectome and bifurcation analyses demonstrate emergence of early neural crest fates at the neural plate stage, alongside an unbiased multipotent neural crest lineage persisting until after epithelial-mesenchymal transition. We also define a new and transient neural border zone state, preceding choice between neural crest and placodes during gastrulation. Theis combination of experimental tests, with Machine Learning broadly applicable to single cell transcriptomics, deciphers the circuits driving cranial and vagal neural crest formation and provides a general model for investigating vertebrate GRNs in development, evolution and disease.
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Project description:Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of molecular choices governing the emergence of neural crest heterogeneity from the ectoderm remains elusive. Gene regulatory networks govern these steps of embryonic development and cell specification towards definitive neural crest. Here, we combine ultra-dense single cell transcriptomes with machine-learning strategies and experimental validation to provide a comprehensive gene regulatory network driving vertebrate neural crest fate diversification, from induction to early migration stages. Transcription factor connectome and bifurcation analyses demonstrate emergence of early neural crest fates at the neural plate stage, alongside an unbiased multipotent neural crest lineage persisting until after epithelial-mesenchymal transition. We also define a new and transient neural border zone state, preceding choice between neural crest and placodes during gastrulation. Theis combination of experimental tests, with Machine Learning broadly applicable to single cell transcriptomics, deciphers the circuits driving cranial and vagal neural crest formation and provides a general model for investigating vertebrate GRNs in development, evolution and disease.
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