Single-nucleus and single-cell transcriptomes compared in matched cortical cell types
Single-nucleus and single-cell transcriptomes compared in matched cortical cell types
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DOI：
10.1371/journal.pone.0209648
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发表时间：
2018-12-26
期刊：
影响因子：
3.7
通讯作者：
Tasic, Bosiljka
中科院分区：
文献类型：
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作者：
Bakken, Trygve E.;Hodge, Rebecca D.;Tasic, Bosiljka
通过单核RNA测序（snRNA-seq）对复杂组织进行转录组学分析提供了优于单细胞RNA测序（scRNA-seq）的一些优势。snRNA-seq提供了更少的细胞覆盖偏差，似乎不会遭受基于细胞分离的转录伪影，并且可以应用于存档的冷冻标本。我们使用来自小鼠视觉皮层的匹配良好的snRNA-seq和scRNA-seq数据集来比较细胞类型检测。虽然在单个全细胞中检测到更多的转录物（类似于11，000个基因）而不是细胞核（类似于7，000个基因），但我们证明，如果在snRNA-seq分析中包括内含子序列，则可以用两种方法类似地区分密切相关的神经元细胞类型。我们估计，总细胞mRNA的核比例从20%到50%以上的大，小锥体神经元，分别。总之，这些结果说明了核RNA的高信息含量的脑组织中的细胞多样性的表征。
Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (similar to 11,000 genes) than nuclei (similar to 7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.