Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: a molecular atlas of kidney development
- PMID: 28851704
- PMCID: PMC5665481
- DOI: 10.1242/dev.151142
Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: a molecular atlas of kidney development
Abstract
Single-cell RNA-seq is a powerful technique. Nevertheless, there are important limitations, including the technical challenges of breaking down an organ or tissue into a single-cell suspension. Invariably, this has required enzymatic incubation at 37°C, which can be expected to result in artifactual changes in gene expression patterns. Here, we describe a dissociation method that uses a protease with high activity in the cold, purified from a psychrophilic microorganism. The entire procedure is carried out at 6°C or colder, at which temperature mammalian transcriptional machinery is largely inactive, thereby effectively 'freezing in' the in vivo gene expression patterns. To test this method, we carried out RNA-seq on 20,424 single cells from postnatal day 1 mouse kidneys, comparing the results of the psychrophilic protease method with procedures using 37°C incubation. We show that the cold protease method provides a great reduction in gene expression artifacts. In addition, the results produce a single-cell resolution gene expression atlas of the newborn mouse kidney, an interesting time in development when mature nephrons are present yet nephrogenesis remains extremely active.
Keywords: Artifacts; Cell dissociation; Kidney development; RNA-seq; Single cell.
© 2017. Published by The Company of Biologists Ltd.
Conflict of interest statement
Competing interestsThe authors declare no competing or financial interests.
Figures







Similar articles
-
Dissociation of Tissues for Single-Cell Analysis.Methods Mol Biol. 2019;1926:55-62. doi: 10.1007/978-1-4939-9021-4_5. Methods Mol Biol. 2019. PMID: 30742262
-
Quality Control of Single-Cell RNA-seq.Methods Mol Biol. 2019;1935:1-9. doi: 10.1007/978-1-4939-9057-3_1. Methods Mol Biol. 2019. PMID: 30758816
-
Dissociation of microdissected mouse brain tissue for artifact free single-cell RNA sequencing.STAR Protoc. 2021 Jun 10;2(2):100590. doi: 10.1016/j.xpro.2021.100590. eCollection 2021 Jun 18. STAR Protoc. 2021. PMID: 34159323 Free PMC article.
-
Current Methodological Challenges of Single-Cell and Single-Nucleus RNA-Sequencing in Glomerular Diseases.J Am Soc Nephrol. 2021 Aug;32(8):1838-1852. doi: 10.1681/ASN.2021020157. Epub 2021 Jun 17. J Am Soc Nephrol. 2021. PMID: 34140401 Free PMC article. Review.
-
[Recent progress in single-cell RNA-Seq analysis].Yi Chuan. 2014 Nov;36(11):1069-76. doi: 10.3724/SP.J.1005.2014.1069. Yi Chuan. 2014. PMID: 25567865 Review. Chinese.
Cited by
-
scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.Bioinformatics. 2023 Feb 14;39(2):btad075. doi: 10.1093/bioinformatics/btad075. Bioinformatics. 2023. PMID: 36734596 Free PMC article.
-
Gut mucosa dissociation protocols influence cell type proportions and single-cell gene expression levels.Sci Rep. 2022 Jun 14;12(1):9897. doi: 10.1038/s41598-022-13812-y. Sci Rep. 2022. PMID: 35701452 Free PMC article.
-
Tissue-resident memory CD8+ T cells possess unique transcriptional, epigenetic and functional adaptations to different tissue environments.Nat Immunol. 2022 Jul;23(7):1121-1131. doi: 10.1038/s41590-022-01229-8. Epub 2022 Jun 27. Nat Immunol. 2022. PMID: 35761084 Free PMC article.
-
scAce: an adaptive embedding and clustering method for single-cell gene expression data.Bioinformatics. 2023 Sep 2;39(9):btad546. doi: 10.1093/bioinformatics/btad546. Bioinformatics. 2023. PMID: 37672035 Free PMC article.
-
Microfluidic Device Technologies for Digestion, Disaggregation, and Filtration of Tissue Samples for Single Cell Applications.Methods Mol Biol. 2022;2394:81-92. doi: 10.1007/978-1-0716-1811-0_6. Methods Mol Biol. 2022. PMID: 35094323
References
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Molecular Biology Databases