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

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.

Keywords: 10x Genomics; RNA-seq; Single-cell transcriptomics; scRNA-seq; snRNA-seq.

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. 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. 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. 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