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Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes

机译:电生理记录与单细胞RNA-seq数据的整合可识别神经元亚型

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Traditionally, neuroscientists have defined the identity of neurons by the cells' location, morphology, connectivity and excitability. However, the direct relationship between these parameters and the molecular phenotypes has remained largely unexplored. Here, we present a method for obtaining full transcriptome data from single neocortical pyramidal cells and interneurons after whole-cell patch-clamp recordings in mouse brain slices. In our approach, termed Patch-seq, a patch-clamp stimulus protocol is followed by the aspiration of the entire somatic compartment into the recording pipette, reverse transcription of RNA including addition of unique molecular identifiers, cDNA amplification, Illumina library preparation and sequencing. We show that Patch-seq reveals a close link between electrophysiological characteristics, responses to acute chemical challenges and RNA expression of neurotransmitter receptors and channels. Moreover, it distinguishes neuronal subpopulations that correspond to both well-established and, to our knowledge, hitherto undescribed neuronal subtypes. Our findings demonstrate the ability of Patch-seq to precisely map neuronal subtypes and predict their network contributions in the brain.
机译:传统上,神经科学家通过细胞的位置,形态,连通性和兴奋性来定义神经元的身份。但是,这些参数与分子表型之间的直接关系在很大程度上尚待探索。在这里,我们提出了一种从单个新皮质锥体细胞和中间神经元在小鼠脑切片中进行全细胞膜片钳记录后获得完整转录组数据的方法。在我们称为Patch-seq的方法中,使用膜片钳刺激方案,然后将整个体细胞室抽吸到记录移液管中,对RNA进行逆转录,包括添加独特的分子标识符,cDNA扩增,Illumina文库制备和测序。我们显示,Patch-seq揭示了电生理特征,对急性化学挑战的反应以及神经递质受体和通道的RNA表达之间的密切联系。此外,它区分了既有完善的神经元亚型,也有我们所知的迄今未描述的神经元亚型。我们的发现表明,Patch-seq能够准确定位神经元亚型并预测其在大脑中的网络贡献。

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