Isolated nuclei from frozen tissue are the superior source for single cell RNA-seq compared with whole cells
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ABSTRACT: The isolation of intact single cells from frozen tissue is a challenge due to the mechanical and physical stress inflicted upon the cell during the freeze-thaw process. Ruptured cells release ambient RNA into the cell suspension, which can become encapsulated into droplets during droplet based single cell RNA-seq library preparation methods. The presence of ambient RNA in droplets has been suggested to impact data quality, however there have been limited reports on single cell RNA-seq data from frozen tissue. Here, we compare the results of single cell RNA-seq derived from disaggregated cells from frozen brain tissue with single nuclei RNA-seq derived from purified nuclei of identical tissue using the 10X Genomics Chromium 3’ gene expression assay. Our results indicated that presence of ambient RNA in the cell suspension resulted in single cell RNA-seq data with a 25-fold lower gene count, a 5-fold lower UMI count per cell and a 2-fold lower fraction of reads per cell compared with single nuclei RNA-seq data. Cell clustering with the single cell RNA-seq data was unable to resolve the heterogeneity of brain cell types. Our conclusion is that nuclei from frozen tissue are the superior substrate for single cell transcriptome analysis.
Project description:Contamination of ambient RNA was found in single-nuclei RNA-Seq data of mouse frontal cortex. CellBender plus subcluster cleaning selectively removed ambient RNA signature from glial cell types.
Project description:Abstract The liver is the largest solid organ and a primary metabolic hub. In recent years, intact cell nuclei were used to perform single-nuclei RNA-seq (snRNA-seq) for tissues difficult to dissociate and for flash-frozen archived tissue samples to discover unknown and rare cell sub-populations. In this study, we performed snRNA-seq of a liver sample to identify sub-populations of cells based on nuclear transcriptomics. In 4,282 single nuclei we detected on average 1,377 active genes and we identified seven major cell types. We integrated data from 94,286 distal interactions (p<0.05) for 7,682 promoters from a targeted chromosome conformation capture technique (HiCap) and mass spectrometry (MS) proteomics for the same liver sample. We observed a reasonable correlation between proteomics and in silico bulk snRNA-seq (r=0.47) using tissue-independent gene-specific protein abundancy estimation factors. We specifically looked at genes of medical importance. The DPYD gene is involved in the pharmacogenetics of fluoropyrimidines toxicity and some of its variants are analyzed for clinical purposes. We identified a new putative polymorphic regulatory element, which may contribute to variation in toxicity. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and we investigated all known risk genes. We identified a complex regulatory landscape for the SLC2A2 gene with 16 candidate enhancers. Three of them harbor somatic motif breaking and other mutations in HCC in the Pan Cancer Analysis of Whole Genomes dataset and are candidates to contribute to malignancy. Our results highlight the potential of a multi-omics approach in the study of human diseases.
Project description:Ambient RNA contamination in single-cell RNA sequencing (RNA-seq) is a significant problem, but its consequences are poorly understood. Here, we show that ambient RNAs in brain single-nuclei RNA-seq can have a nuclear or extra-nuclear origin, and each origin results in a distinct gene set signature. Both ambient RNA signatures are predominantly neuronal and we find that some previously annotated neuronal cell types are distinguished by ambient RNA. Strikingly, we also detect pervasive neuronal ambient RNA contamination in all glial cell types unless glia and neurons are physically separated prior to sequencing. We demonstrate that this contamination can be removed in silico using existing tools. We also show that previous annotations of immature oligodendrocytes are likely glial cells contaminated with ambient RNAs. After ambient RNA removal, we can detect extremely rare committed oligodendrocyte progenitor cells, which were infrequently annotated in previously published adult human brain datasets. Together, these results provide an in-depth analysis of ambient RNA contamination in brain single-cell datasets.
Project description:The widespread application of single-cell genomics technologies has accelerated our understanding of the breadth and depth of heterogeneity of cell states across diverse contexts. As single-cell RNA sequencing (scRNA-seq) has been the most popular modality used for profiling, many populations have been described primarily based on specific marker transcript profiles compared to classical cytometry approaches relying on protein expression. Additionally, many single cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address this limitation, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables single cell and single nuclei RNA-seq profiling from subpopulations of complex cellular mixtures solely defined by the abundance of RNA transcripts. Across vignettes of immune cell populations as well as nuclei from fresh frozen and formalin-fixed paraffin-embedded brain tissue, we demonstrate the enrichment of cell populations via RNA-based cytometry upstream of high-throughput scRNA-seq. Together, our approach provides a rational, programmable method for studying cell identities and transcriptional heterogeneity of rare populations identifiable by as few as one marker transcript, advancing the rational study of cellular diversity across fresh and archived tissue materials.
Project description:Single nucleus RNA-Seq (snRNA-Seq) is used as an alternative to single cell RNA-Seq, as it allows transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-Seq is able to detect cellular state in human tissue. Indeed, snRNA-Seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer’s Disease. Our comparison of microglia from single cells and single nuclei of four human subjects revealed that, while the majority of genes showed similar relative abundances in cells and nuclei, a small population of genes (~1%) was depleted in nuclei compared to whole cells. This population was enriched for genes previously implicated in microglial activation, including APOE, CST3, SPP1, and CD74, comprising 18% of previously-identified microglial disease-associated genes. Given the low sensitivity of snRNA-Seq to detect many activation genes, we conclude that snRNA-Seq is not suited to detecting cellular activation in microglia in human disease.
Project description:Single cell genomics is essential to chart tumor ecosystems. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 212,498 cells and nuclei from 39 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate, and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.
Project description:Single-nuclei RNA-Seq is widely employed to investigate cell types, especially of human brain and frozen samples. In contrast to single-cell approaches, many single-nuclei reads are purely intronic. Here, using microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing, we developed single-nuclei isoform RNA-sequencing (‘SnISOr-Seq’), and applied it to human adult frontal cortex. SnISOr-Seq dramatically increased the fraction of informative reads. We found that exons associated with autism exhibit coordinated and highly cell-type specific inclusion. We discovered two distinct combination patterns: first, those distinguishing neural cell types, enriched in TSS-exon, exon-polyA-site, and non-adjacent exon pairs. Second, those with multiple configurations within one cell type, enriched in adjacent exon pairs. Furthermore, adjacent exons are predominantly mutually-associated, while distant exons are frequently mutually-exclusive. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons. SnISOr-Seq enables single-nuclei long-read isoform analysis in human brain, and in any frozen or hard-to-dissociate sample.
Project description:Microglia are the tissue macrophages of the central nervous system (CNS) and the first to respond to CNS dysfunction and disease. Gene expression profiling of microglia during development, under homeostatic conditions and in the diseased CNS provided insight in microglia functions and changes thereof. Single cell sequencing studies further contributed to our understanding of microglia heterogeneity in relation to age, sex and CNS disease. Recently, single nucleus gene expression profiling was performed on (frozen) CNS tissue. Transcriptomic profiling of CNS tissues by (single) nucleus RNA-sequencing has the advantage that it can be applied to archived and well stratified frozen specimens. Here, we give an overview of the significant advances recently made in microglia transcriptional profiling. In addition, we present matched cellular and nuclear microglia RNA-seq datasets we generated from mouse and human CNS tissue to compare cellular versus nuclear transcriptomes from fresh and frozen samples. We demonstrate that microglia can be similarly profiled with cell and nucleus profiling, and importantly also with nuclei isolated from frozen tissue. Nuclear microglia transcriptomes are a reliable proxy for cellular transcriptomes. Interestingly, lipopolysaccharide- (LPS)-induced changes in gene expression were even more pronounced in the nuclear transcriptome. In addition, heterogeneity in microglia observed in fresh samples is similarly detected in frozen nuclei of the same donor. Together, these results show that microglia nuclear RNAs obtained from frozen CNS tissue are a reliable proxy for microglia gene expression and cellular heterogeneity and may prove an effective strategy to study of the role of microglia in neuropathology.
Project description:We present DEFND-seq (DNA and Expression From Nucleosome Depletion), a scalable method for co-sequencing RNA and DNA from single nuclei. In DEFND-seq we treat nuclei with lithium diiodosalicylate to disrupt chromatin and expose genoimc DNA. The nuclei are then tagmented with Tn5 transposase, which fragments and tags gDNA. Tagmented nuclei are loaded into a microfluidic droplet generator which combines nuclei, beads containing transcriptomic and genomic barcodes, and reverse transcription reagents into single droplets. Ultimately two libraries are created, one for nuclear mRNA and one for genomic DNA, with each library containing barcodes linking it to its nuclei of origin, thus allowing simultaneous analysis of single nuclei transcriptomes and genomes. Once nuclei have been depleted of nucleosomes, all steps can be performed using a 10x Chromium Controller and 10x Multiome Kit without further experimental modification.