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Neuron. 2019 Jun 19;102(6):1111-1126.e5. doi: 10.1016/j.neuron.2019.04.010. Epub 2019 May 22.

Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification.

Author information

1
Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
2
Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Institute for Data Intensive Engineering and Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
3
Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
4
Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
5
Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
6
Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
7
Department of Biochemistry, Genetics, Genomics and Bioinformatics Graduate Program, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA.
8
Department of Oncology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Institute for Data Intensive Engineering and Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Institute for Computational Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Mathematical Institute for Data Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
9
Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205, USA.
10
Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Human Systems Biology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: sblack@jhmi.edu.

Abstract

Precise temporal control of gene expression in neuronal progenitors is necessary for correct regulation of neurogenesis and cell fate specification. However, the cellular heterogeneity of the developing CNS has posed a major obstacle to identifying the gene regulatory networks that control these processes. To address this, we used single-cell RNA sequencing to profile ten developmental stages encompassing the full course of retinal neurogenesis. This allowed us to comprehensively characterize changes in gene expression that occur during initiation of neurogenesis, changes in developmental competence, and specification and differentiation of each major retinal cell type. We identify the NFI transcription factors (Nfia, Nfib, and Nfix) as selectively expressed in late retinal progenitor cells and show that they control bipolar interneuron and Müller glia cell fate specification and promote proliferative quiescence.

KEYWORDS:

CoGAPS; Müller glia; cell fate; development; neural progenitor; neurogenesis; photoreceptor; proliferation; retina; scRNA-seq; single-cell RNA-sequencing

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