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

TLDR

Single‑nucleus RNA‑sequencing (snRNA‑seq) offers less biased cellular coverage, avoids cell‑isolation transcriptional artifacts, and can be applied to archived frozen tissues, making it a valuable alternative to single‑cell RNA‑sequencing (scRNA‑seq). The authors compared matched snRNA‑seq and scRNA‑seq datasets from mouse visual cortex to assess cell‑type detection. Despite detecting fewer transcripts per nucleus (~7,000 vs.

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.