大规模并行单细胞转录组谱分析定义了脊髓神经元及其在行为过程中的活动。
Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior.
机构信息
Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20892, USA.
Bioinformatics Section, Information Technology Program, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20892, USA.
出版信息
Cell Rep. 2018 Feb 20;22(8):2216-2225. doi: 10.1016/j.celrep.2018.02.003.
To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease.
为了理解行为的细胞基础，有必要了解存在于神经系统中的细胞类型及其对功能的贡献。脊髓网络对于感觉处理和运动行为至关重要，并且为鉴定行为的细胞相关性提供了一个强大的系统。在这里，我们使用大规模平行的单细胞 RNA 测序（snRNA-seq）来创建成年小鼠腰椎脊髓的图谱。我们鉴定并分子表征了 43 种神经元群体。接下来，我们利用 snRNA-seq 方法，通过神经元活性的转录特征，对感觉和运动行为后活跃的神经元群体进行了无偏鉴定。这种方法可以在未来将单细胞基因表达数据与对行为、损伤和疾病的动态生物学反应联系起来。
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