Cited by 716Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesMolecular Biology Techniques and Applications

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index; 1 of the 9 sources its claims cite were checked for support.

Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows

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Published version of a preprint

Abstract

Background: Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample dissociation and storage of single cells have been proposed as have single-nuclei profiling methods. What has been lacking is a systematic comparison of their relative biases and benefits. Results: Here, we compare gene expression and cellular composition of single-cell suspensions prepared from adult mouse kidney using two tissue dissociation protocols. For each sample, we also compare fresh cells to cryopreserved and methanol-fixed cells. Lastly, we compare this single-cell data to that generated using three single-nucleus RNA sequencing workflows. Our data confirms prior reports that digestion on ice avoids the stress response observed with 37 °C dissociation. It also reveals cell types more abundant either in the cold or warm dissociations that may represent populations that require gentler or harsher conditions to be released intact. For cell storage, cryopreservation of dissociated cells results in a major loss of epithelial cell types; in contrast, methanol fixation maintains the cellular composition but suffers from ambient RNA leakage. Finally, cell type composition differences are observed between single-cell and single-nucleus RNA sequencing libraries. In particular, we note an underrepresentation of T, B, and NK lymphocytes in the single-nucleus libraries. Conclusions: Systematic comparison of recovered cell types and their transcriptional profiles across the workflows has highlighted protocol-specific biases and thus enables researchers starting single-cell experiments to make an informed choice.

Overview

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TL;DR

This study systematically compares tissue dissociation, cell preservation, and single-cell versus single-nucleus RNA-seq workflows in adult mouse kidney, using 77,656 single-cell, 98,303 single-nucleus, and 15 bulk RNA-seq profiles. It finds protocol-specific biases: warm dissociation induces stress genes and depletes sensitive cell types, cryopreservation loses epithelial cells, methanol fixation preserves composition but causes ambient RNA leakage, and snRNA-seq underrepresents T, B, and NK lymphocytes.

Key findings

  • Warm dissociation induced a stress response: bulk RNA-seq found 71 genes higher in warm-dissociated kidneys versus 5 in cold-dissociated kidneys (logFC > 2, FDR < 0.05), and scRNA-seq found 64 genes higher in warm-dissociated libraries in at least one cell type versus 20 in cold-dissociated libraries. Stress scores were significantly high in 8 of 14 cell types in warm-dissociated samples.
  • Cell composition differed by dissociation protocol: podocytes were 0.03% in warm-dissociated samples versus 2.78% in cold-dissociated samples; aLOH cells were 4.99% versus 2.52%, and PT cells were 71.36% versus 63.34% in warm versus cold, respectively.
  • Cryopreservation severely depleted epithelial cells: PT cells were 63.12% and 70.86% in fresh cold- and warm-dissociated samples but only 0.31% and 0.57% in cryopreserved samples; a repeat experiment showed PT at 55.55% fresh versus 7.65% cryopreserved. Only ~30% of cryopreserved cells were recovered, while methanol fixation better preserved composition but showed ambient RNA leakage.
  • Single-nucleus libraries underdetected immune cells: immune cells averaged 0.73% in snRNA-seq versus 6.03% in scRNA-seq; T, B, and NK cells were not detected in snRNA-seq, and podocytes were 0.7% in snRNA-seq versus 3.28% in scRNA-seq. snRNA-seq detected more genes per nucleus (median 1819) than scRNA-seq per cell (median 981).

Methods

  • Adult mouse kidneys were used: male C57BL/6J mice (19 weeks) for the first dissociation/preservation series, and male Balb/c (18 weeks) or female Balb/c (15 weeks) mice for later scRNA-seq versus snRNA-seq comparisons, with biological triplicates.
  • Workflows compared two dissociation protocols (37 °C Miltenyi Multi Tissue Dissociation Kit 2 versus cold-active *Bacillus licheniformis* protease on ice), two preservation methods (methanol fixation and cryopreservation), and three single-nuclei isolation protocols (SN_FANS_3x500g, SN_FANS_1x2000g, SN_sucrose), plus bulk RNA-seq of intact and dissociated kidney.
  • Libraries were profiled with 10x Genomics Chromium scRNA-seq/snRNA-seq and bulk RNA-seq; analyses included Cell Ranger, EmptyDrops, Seurat, scMatch annotation, edgeR/GeTMM, BSEQ-sc deconvolution, a 17-gene stress score, and Seurat cell-cycle scoring. Data are available at GSE141115.

Limitations

  • Stated in the paper: bulk RNA-seq deconvolution is sensitive to the input marker gene list, may overlook rare and novel cell types, and cell abundance estimates from bulk data are influenced by both cell number and relative mRNA content; the authors note they lack a definitive “ground truth” for cell composition and did not use in vitro cell mixtures or spiking because these do not represent dissociation from solid tissue.
  • Stated in the paper: flow cytometry still requires dissociation, and ISH/IHC/spatial methods only give proportions for sections examined rather than whole-organ estimates; a classifier able to distinguish mitotic cells from early G1 and late G2 is needed to fully dissect cell-cycle biases in snRNA-seq.
  • Evident from the text: findings are restricted to adult mouse kidney, specific mouse strains/sexes, selected 10x chemistries, and particular dissociation, preservation, and nuclei-isolation protocols, so generalization to other tissues, species, or protocols is not established; some analyses excluded low-abundance cell types such as podocytes and transitional cells, and red blood cell depletion was not applied.

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Integrity signals

Registry

Crossref · 10.1186/s13059-020-02048-6

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

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Figures

Fig. 1 Overview of experiments performed in this study. All experiments were carried out in biological triplicate using three kidneys from three different mice. a 37 °C dissociation used the Multi-tissue dissociation kit 2 from Miltenyi Biotec. b Cold dissociation was carried out on ice using B. Licheniformis protease. In a and b, methanol-fixed samples used 80% MeOH at − 20 °C and then were stored at − 80 °C. Cryopreservation was carried out using 50% FBS, 40% RPMI-1640, 10% and DMSO with gradient cooling to − 80 °C then stored in liquid nitrogen. c–e Whole kidneys were flash frozen using an isopentane bath − 30 °C and then stored at − 80 °C. Three different nuclei preparation methods were tested using either fluorescently activated nuclei sorting (FANS) or a sucrose gradient to enrich for singlet nuclei. f Bulk RNA-seq was carried out using the NEBNext Ultra II RNA Library Kit for Illumina with rRNA depletion or NEBNext Poly(A) mRNA isolation module. See “Methods” for more details
Fig. 1 Overview of experiments performed in this study. All experiments were carried out in biological triplicate using three kidneys from three different mice. a 37 °C dissociation used the Multi-tissue dissociation kit 2 from Miltenyi Biotec. b Cold dissociation was carried out on ice using B. Licheniformis protease. In a and b, methanol-fixed samples used 80% MeOH at − 20 °C and then were stored at − 80 °C. Cryopreservation was carried out using 50% FBS, 40% RPMI-1640, 10% and DMSO with gradient cooling to − 80 °C then stored in liquid nitrogen. c–e Whole kidneys were flash frozen using an isopentane bath − 30 °C and then stored at − 80 °C. Three different nuclei preparation methods were tested using either fluorescently activated nuclei sorting (FANS) or a sucrose gradient to enrich for singlet nuclei. f Bulk RNA-seq was carried out using the NEBNext Ultra II RNA Library Kit for Illumina with rRNA depletion or NEBNext Poly(A) mRNA isolation module. See “Methods” for more detailsCC BY · PubMed Central
Fig. 2 Comparison of cold and warm tissue dissociation protocols. a Bulk RNA-seq profiles of dissociated kidneys. GeTMM-normalized counts [29] were averaged across three biological replicates and log2-transformed after adding a pseudo count of 1. DEGs with FDR < 0.05 and logFC threshold of 2 (edgeR exact test [27]) are shown as red and blue dots; protein-coding genes with logFC > 4 are labelled. b Number of differentially expressed genes (DEGs) between cold- and warm-dissociated scRNA-seq libraries. Calculated for each cell type separately using Wilcoxon test in Seurat [30] with thresholds of logFC = 0.5, minimum detection rate 0.5, FDR < 0.05. Numbers on the right side of the plot indicate cell population size. c Stress score – an expression score for a set of 17 stress-response-related genes (Fosb, Fos, Jun, Junb, Jund, Atf3, Egr1, Hspa1a, Hspa1b, Hsp90ab1, Hspa8, Hspb1, Ier3, Ier2, Btg1, Btg2, Dusp1). Calculated as average gene expression level of these genes subtracted by averaged expression of randomly selected control genes and then averaged for cell types. Significance was calculated in a Monte-Carlo procedure with 1000 randomly selected gene sets of the same size, asterisks denote p value < 0.01. d Expression and detection rates of differentially expressed genes commonly induced in warm-dissociated samples (differentially expressed in at least four cell types). e Cell type composition of freshly profiled scRNA-seq libraries. Three biological replicates are shown per condition. Asterisks denote two-sided chi-square test p value < 0.001. In b–d, podocytes and transitional cells were excluded due to low cell numbers. aLOH: ascending loop of Henle; CD_IC: intercalated cells of collecting duct; CD_PC: principal cells of collecting duct; CNT: connecting tubule; DCT: distal convoluted tubule; PT: proximal tubule
Fig. 2 Comparison of cold and warm tissue dissociation protocols. a Bulk RNA-seq profiles of dissociated kidneys. GeTMM-normalized counts [29] were averaged across three biological replicates and log2-transformed after adding a pseudo count of 1. DEGs with FDR < 0.05 and logFC threshold of 2 (edgeR exact test [27]) are shown as red and blue dots; protein-coding genes with logFC > 4 are labelled. b Number of differentially expressed genes (DEGs) between cold- and warm-dissociated scRNA-seq libraries. Calculated for each cell type separately using Wilcoxon test in Seurat [30] with thresholds of logFC = 0.5, minimum detection rate 0.5, FDR < 0.05. Numbers on the right side of the plot indicate cell population size. c Stress score – an expression score for a set of 17 stress-response-related genes (Fosb, Fos, Jun, Junb, Jund, Atf3, Egr1, Hspa1a, Hspa1b, Hsp90ab1, Hspa8, Hspb1, Ier3, Ier2, Btg1, Btg2, Dusp1). Calculated as average gene expression level of these genes subtracted by averaged expression of randomly selected control genes and then averaged for cell types. Significance was calculated in a Monte-Carlo procedure with 1000 randomly selected gene sets of the same size, asterisks denote p value < 0.01. d Expression and detection rates of differentially expressed genes commonly induced in warm-dissociated samples (differentially expressed in at least four cell types). e Cell type composition of freshly profiled scRNA-seq libraries. Three biological replicates are shown per condition. Asterisks denote two-sided chi-square test p value < 0.001. In b–d, podocytes and transitional cells were excluded due to low cell numbers. aLOH: ascending loop of Henle; CD_IC: intercalated cells of collecting duct; CD_PC: principal cells of collecting duct; CNT: connecting tubule; DCT: distal convoluted tubule; PT: proximal tubuleCC BY · PubMed Central
Fig. 3 Cell preservation protocol performance in cold-dissociated samples. a Cell type composition of freshly profiled and preserved cold-dissociated samples. b Number of differentially expressed genes (DEGs) detected between preserved and freshly profiled aliquots. Seurat Wilcoxon test [30] with logFC = 1, min detection rate 0.5, FDR < 0.05 as thresholds. c Expression and detection rates of DEGs with higher expression in cryopreserved samples in at least two cell types. d Expression and detection rates of DEGs with higher expression in methanol-fixed samples in at least nine cell types. aLOH: ascending loop of Henle; CD_IC: intercalated cells of collecting duct; CD_PC: principal cells of collecting duct; CNT: connecting tubule; DCT: distal convoluted tubule; PT: proximal tubule
Fig. 3 Cell preservation protocol performance in cold-dissociated samples. a Cell type composition of freshly profiled and preserved cold-dissociated samples. b Number of differentially expressed genes (DEGs) detected between preserved and freshly profiled aliquots. Seurat Wilcoxon test [30] with logFC = 1, min detection rate 0.5, FDR < 0.05 as thresholds. c Expression and detection rates of DEGs with higher expression in cryopreserved samples in at least two cell types. d Expression and detection rates of DEGs with higher expression in methanol-fixed samples in at least nine cell types. aLOH: ascending loop of Henle; CD_IC: intercalated cells of collecting duct; CD_PC: principal cells of collecting duct; CNT: connecting tubule; DCT: distal convoluted tubule; PT: proximal tubuleCC BY · PubMed Central
Fig. 4 Comparison of single-cell and single-nucleus libraries. a Cell type composition for kidneys from Balb/c female mice. Average percentages for scRNA-seq libraries are shown in blue and for snRNA-seq libraries in gray. BSEQ-sc estimates are shown for bulk RNA-seq of intact and dissociated kidneys. Error bars are standard error of mean. b Abundance of renal epithelial cell types in Clark et al. study [34] in comparison to our data from Balb/c female mice
Fig. 4 Comparison of single-cell and single-nucleus libraries. a Cell type composition for kidneys from Balb/c female mice. Average percentages for scRNA-seq libraries are shown in blue and for snRNA-seq libraries in gray. BSEQ-sc estimates are shown for bulk RNA-seq of intact and dissociated kidneys. Error bars are standard error of mean. b Abundance of renal epithelial cell types in Clark et al. study [34] in comparison to our data from Balb/c female miceCC BY · PubMed Central

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Claims the paper makes

35 Own result · 20 Own interpretation · 6 Not checked yet · 4 Own method · 4 No basis given · 1 Supported

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  • It may state two separate claims as one. 19
  • Probably not a substantial claim. 8
  • The quote only partly states this claim. 1
26 of 26
  • The paper relies on this without support.

    The biases observed in adult mouse kidney workflows generalize to other tissues and to human disease biology.

    “From our experiments, we have confirmed several observations by others in the field that have direct relevance to designing single-cell experiments studying human disease biology.”
    “Specifically, the depletion of epithelial cell types in cryopreserved samples is concerning given the majority of human cancers are epithelial in origin.”
  • The paper relies on this without support.

    BSEQ-sc deconvolution of bulk RNA-seq accurately estimates cell type proportions in intact kidney.

    “Using the bulk RNA-seq from intact kidneys (Fig. 1f) and BSEQ-sc [35] to predict the proportions of each cell type present, we estimated that approximately 1.51% should correspond to immune cells in Balb/c female mice and 4.84% in Balb/c male mice.”
  • The paper relies on this without support.

    The reference expression profiles from previous mouse kidney studies accurately represent the cell types in the studied samples.

    “Cells were classified into 15 cell types using scMatch [31] by comparing their expression to reference expression profiles from three previous mouse kidney studies [26, 32, 33], followed by gene signature-based refinement”
  • The paper relies on this without support.

    3x SSC inhibits reverse transcription.

    “Due to the reverse transcription inhibition of 3x SSC, the sample had to be loaded at a concentration of 0.125x SSC”
4 of 4

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Citations

Cites

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Research works printed but not linked: 2

  1. Mus musculus ribosomal DNA, complete repeating unit. https://www.ncbi.nlm.nih.gov/nuccore/BK000964. Accessed 24 Jan 2019.
  2. Denisenko E, Guo B, Jones M, Hou R, de Kock L, Lassmann T, et al. Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows. Datasets. Gene Expression Omnibus. 2020. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE141115. Accessed 11 May 2020.

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Metadata

Authors
Denisenko, E., Guo, B. B., Jones, M., Hou, R., de Kock, L., Lassmann, T., Poppe, D., Clément, O., Simmons, R. K., Lister, R., & Forrest, A. R. R.
Affiliations
  • The University of Western Australia (AU)
  • The Kids Research Institute Australia (AU)
Corresponding author
Forrest, Alistair R. R.
Venue
Genome Biology
Published
2020-06-02
Volume
21
Issue
1
Pages
130-130
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
OpenAlex
W3030739213
Cited by
686
References
54
Citations by year
2026: 138 · 2025: 96 · 2024: 118 · 2023: 118 · 2022: 100 · 2021: 83 · 2020: 33
FWCI
27.50
Type
journal article
Language
en
Open access
Locations
  • Genome biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Health and Medical Research Council (APP1154524)
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 › Molecular Biology Techniques and Applications
Keywords
tissue dissociation, single-cell RNA sequencing, single-nucleus RNA sequencing, cryopreservation, methanol fixation, kidney, cell type composition
MeSH terms
Animals, Cell Separation, Kidney, Male, Mice, Inbred C57BL, Stress, Physiological, Cryopreservation, Sequence Analysis, RNA, Single-Cell Analysis

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