4.8 Article

The molecular landscape of neural differentiation in the developing Drosophila brain revealed by targeted scRNA-seq and multi-informatic analysis

期刊

CELL REPORTS
卷 35, 期 4, 页码 -

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CELL PRESS
DOI: 10.1016/j.celrep.2021.109039

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资金

  1. National Institutes of Health (NIH) [NIH 5P30CA046592-31]
  2. NIH [1R01NS107496, 1T32EB005582, 1F31NS11184701]
  3. University of Michigan (CDB IDEA Awards in Stem Cell Biology, MCubed2.0)
  4. Michigan Economic Development Corporation (Mi-TRAC)
  5. University of Michigan

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The study utilizes Drosophila type II neuroblast lineages as a model to investigate neurogenesis and differentiation processes through single-cell mRNA sequencing, revealing molecular landscapes and identifying markers for distinct maturation stages, stem cell origins, and neuronal subtypes. Additionally, the study provides annotated tables of gene-gene correlations and MiCV, a web tool for analyzing scRNA-seq datasets, advancing understanding of neural differentiation at the molecular level.
The Drosophila type II neuroblast lineages present an attractive model to investigate the neurogenesis and differentiation process as they adapt to a process similar to that in the human outer subventricular zone. We perform targeted single-cell mRNA sequencing in third instar larval brains to study this process of the type II NB lineage. Combining prior knowledge, in silico analyses, and in situ validation, our multi-informatic investigation describes the molecular landscape from a single developmental snapshot. 17 markers are identified to differentiate distinct maturation stages. 30 markers are identified to specify the stem cell origin and/or cell division numbers of INPs, and at least 12 neuronal subtypes are identified. To foster future discoveries, we provide annotated tables of pairwise gene-gene correlation in single cells and MiCV, a web tool for interactively analyzing scRNA-seq datasets. Taken together, these resources advance our understanding of the neural differentiation process at the molecular level.

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