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Bakken, Trygve E; Hodge, Rebecca D; Miller, Jeremy A; Yao, Zizhen; Nguyen, Thuc Nghi; Aevermann, Brian; Barkan, Eliza; Bertagnolli, Darren; Casper, Tamara; Dee, Nick; Garren, Emma; Goldy, Jeff; Graybuck, Lucas T; Kroll, Matthew; Lasken, Roger S; Lathia, Kanan; Parry, Sheana; Rimorin, Christine; Scheuermann, Richard H; Schork, Nicholas J; Shehata, Soraya I; Tieu, Michael; Phillips, John W; Bernard, Amy; Smith, Kimberly A; Zeng, Hongkui; Lein, Ed S; Tasic, Bosiljka
PloS one, 12/2018, Letnik: 13, Številka: 12Journal Article
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 (~11,000 genes) than nuclei (~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.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Vir: Osebne bibliografije
in: SICRIS
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