Hu Peng, Fabyanic Emily, Kwon Deborah Y, Tang Sheng, Zhou Zhaolan, Wu Hao
Department of Genetics, University of Pennsylvania, Philadelphia PA 19104, USA; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA 19104, USA.
Department of Genetics, University of Pennsylvania, Philadelphia PA 19104, USA; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA 19104, USA.
Mol Cell. 2017 Dec 7;68(5):1006-1015.e7. doi: 10.1016/j.molcel.2017.11.017.
Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo.
大规模平行单细胞RNA测序能够以低成本、高通量的方式精确解析细胞多样性，但从诸如成年哺乳动物大脑等复杂组织中无偏差地分离完整单细胞颇具挑战性。在此，我们将蔗糖梯度辅助的细胞核纯化与微滴微流控技术相结合，开发出一种高度可扩展的单核RNA测序方法（sNucDrop-seq），该方法无需酶解和细胞核分选。通过对从成年小鼠皮质组织分离出的约18,000个细胞核进行分析，我们证明sNucDrop-seq不仅能以高灵敏度准确揭示神经元和非神经元亚型组成，还能在体内以单细胞分辨率深入分析由神经元活动驱动的瞬时转录状态。
