학술논문
Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.
Document Type
Article
Author
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.
Source
Subject
*NUCLEOTIDE sequence
*BRAIN physiology
*NUCLEIC acids
*VISUAL cortex physiology
*GENETIC transcription
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Language
ISSN
1932-6203
Abstract
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. [ABSTRACT FROM AUTHOR]