Unknown

Dataset Information

0

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


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.

SUBMITTER: Bakken TE 

PROVIDER: S-EPMC6306246 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

altmetric image

Publications


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  ...[more]

Similar Datasets

2018-12-06 | GSE123454 | GEO
| PRJNA508779 | ENA
| S-EPMC9097260 | biostudies-literature
| S-EPMC9494604 | biostudies-literature
| S-EPMC4784001 | biostudies-literature
| S-EPMC6992778 | biostudies-literature
| S-EPMC6280782 | biostudies-literature
| S-EPMC9794763 | biostudies-literature
| S-EPMC6788728 | biostudies-literature
| S-EPMC5699061 | biostudies-literature