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  • 标题:Single-cell transcriptomics of the developing lateral geniculate nucleus reveals insights into circuit assembly and refinement
  • 本地全文:下载
  • 作者:Brian T. Kalish ; Lucas Cheadle ; Sinisa Hrvatin
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2018
  • 卷号:115
  • 期号:5
  • 页码:E1051-E1060
  • DOI:10.1073/pnas.1717871115
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Coordinated changes in gene expression underlie the early patterning and cell-type specification of the central nervous system. However, much less is known about how such changes contribute to later stages of circuit assembly and refinement. In this study, we employ single-cell RNA sequencing to develop a detailed, whole-transcriptome resource of gene expression across four time points in the developing dorsal lateral geniculate nucleus (LGN), a visual structure in the brain that undergoes a well-characterized program of postnatal circuit development. This approach identifies markers defining the major LGN cell types, including excitatory relay neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells. Most cell types exhibit significant transcriptional changes across development, dynamically expressing genes involved in distinct processes including retinotopic mapping, synaptogenesis, myelination, and synaptic refinement. Our data suggest that genes associated with synapse and circuit development are expressed in a larger proportion of nonneuronal cell types than previously appreciated. Furthermore, we used this single-cell expression atlas to identify the Prkcd-Cre mouse line as a tool for selective manipulation of relay neurons during a late stage of sensory-driven synaptic refinement. This transcriptomic resource provides a cellular map of gene expression across several cell types of the LGN, and offers insight into the molecular mechanisms of circuit development in the postnatal brain.
  • 关键词:lateral geniculate nucleus ; LGN ; retinogeniculate ; transcriptomics ; refinement
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