Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis
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Background: A challenge for single-cell genomic studies in kidney and other solid tissues is generating a high-quality single-cell suspension that contains rare or difficult-to-dissociate cell types and is free of both RNA degradation and artifactual transcriptional stress responses. Methods: We compared single-cell RNA sequencing (scRNA-seq) using the DropSeq platform with single-nucleus RNA sequencing (snRNA-seq) using sNuc-DropSeq, DroNc-seq, and 10X Chromium platforms on adult mouse kidney. We validated snRNA-seq on fibrotic kidney from mice 14 days after unilateral ureteral obstruction (UUO) surgery. Results: A total of 11,391 transcriptomes were generated in the comparison phase. We identified ten clusters in the scRNA-seq dataset, but glomerular cell types were absent, and one cluster consisted primarily of artifactual dissociation – induced stress response genes. By contrast, snRNA-seq from all three platforms captured a diversity of kidney cell types that were not represented in the scRNA-seq dataset, including glomerular podocytes, mesangial cells, and endothelial cells. No stress response genes were detected. Our snRNA-seq protocol yielded 20-fold more podocytes compared with published scRNA-seq datasets (2.4% versus 0.12%, respectively). Unexpectedly, single-cell and single-nucleus platforms had equivalent gene detection sensitivity. For validation, analysis of frozen day 14 UUO kidney revealed rare juxtaglomerular cells, novel activated proximal tubule and fibroblast cell states, and previously unidentified tubulointerstitial signaling pathways. Conclusions: snRNA-seq achieves comparable gene detection to scRNA-seq in adult kidney, and it also has substantial advantages, including reduced dissociation bias, compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and successful performance on inflamed fibrotic kidney.
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Differential expression analysis comparing individual cell types profiled by snRNA-seq and scRNA-seq suggested higher expression of long noncoding RNAs in snRNA-seq libraries and higher expression of genes related to mitochondrial and ribosomal functions in scRNA-seq.
“Differential expression analysis comparing individual cell types profiled by snRNA-seq and scRNA-seq suggested higher expression of long noncoding RNAs in snRNA-seq libraries and higher expression of genes related to mitochondrial and ribosomal functions in scRNA-seq, in agreement with previous reports [24, 26]”
From Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows (2020) · cites this paper as [26]
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- Authors
- Wu, H., Kirita, Y., Donnelly, E. L., & Humphreys, B. D.
- Affiliations
- Division of Nephrology, Department of Medicine and
- Washington University in St. Louis (US)
- Corresponding author
- Humphreys, Benjamin D.
- Venue
- Journal of the American Society of Nephrology
- Published
- 2018-12-03
- Volume
- 30
- Issue
- 1
- Pages
- 23-32
- ISSN
- 1046-6673 (ISSN-L)
- 1533-3450
- PMC
- PMC6317600
- OpenAlex
- W2902647266
- Cited by
- 752
- References
- 31
- Citations by year
- 2026: 73 · 2025: 92 · 2024: 139 · 2023: 127 · 2022: 112 · 2021: 107 · 2020: 68 · 2019: 32 · 2012: 1
- FWCI
- 18.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Society of Nephrology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (UH3DK107374, U24DK076169, U24DK115255, R01DK103740, UH2DK107374)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- single-nucleus RNA sequencing, single-cell RNA sequencing, renal fibrosis, unilateral ureteral obstruction, podocytes, mesangial cells, juxtaglomerular cells, transcriptional stress response, mouse kidney
- MeSH terms
- Adult, Animals, Cell Nucleus, Cells, Cultured, Dietary Proteins, Disease Models, Animal, Fibrosis, Gene Expression Regulation, Humans, Kidney Diseases, Mice, Inbred C57BL, RNA, Small Nuclear, Sensitivity and Specificity, Sequence Analysis, RNA, Gene Expression Profiling, Mice, Single-Cell Analysis, Transcriptome, In Vitro Techniques
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