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Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.

Authors :
Bakken TE
Hodge RD
Miller JA
Yao Z
Nguyen TN
Aevermann B
Barkan E
Bertagnolli D
Casper T
Dee N
Garren E
Goldy J
Graybuck LT
Kroll M
Lasken RS
Lathia K
Parry S
Rimorin C
Scheuermann RH
Schork NJ
Shehata SI
Tieu M
Phillips JW
Bernard A
Smith KA
Zeng H
Lein ES
Tasic B
Source :
PloS one [PLoS One] 2018 Dec 26; Vol. 13 (12), pp. e0209648. Date of Electronic Publication: 2018 Dec 26 (Print Publication: 2018).
Publication Year :
2018

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.<br />Competing Interests: The authors have declared that no competing interests exist.

Details

Language :
English
ISSN :
1932-6203
Volume :
13
Issue :
12
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
30586455
Full Text :
https://doi.org/10.1371/journal.pone.0209648