scholarly journals Coverage-dependent bias creates the appearance of binary splicing in single cells

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Carlos F Buen Abad Najar ◽  
Nir Yosef ◽  
Liana F Lareau
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Single Cells ◽  
The Other ◽  
Rna Seq ◽  
Single Cell Rna Sequencing ◽  
Unique Identity ◽  
Underlying Reality ◽  
Human And Mouse ◽  
Insight Into

Single-cell RNA sequencing provides powerful insight into the factors that determine each cell’s unique identity. Previous studies led to the surprising observation that alternative splicing among single cells is highly variable and follows a bimodal pattern: a given cell consistently produces either one or the other isoform for a particular splicing choice, with few cells producing both isoforms. Here, we show that this pattern arises almost entirely from technical limitations. We analyze alternative splicing in human and mouse single-cell RNA-seq datasets, and model them with a probabilistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms. This gives the appearance of binary splicing outcomes, even when the underlying reality is consistent with more than one isoform per cell. We show that accounting for the true amount of information recovered can produce biologically meaningful measurements of splicing in single cells.

scholarly journals Coverage-dependent bias creates the appearance of binary splicing in single cells

2019 ◽  
Author(s):  
Carlos F. Buen Abad Najar ◽  
Nir Yosef ◽  
Liana F. Lareau
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Rna Splicing ◽  
Single Cells ◽  
Cell Types ◽  
Rna Seq ◽  
Unique Identity ◽  
Underlying Reality ◽  
Human And Mouse ◽  
Insight Into

Single cell RNA sequencing provides powerful insight into the factors that determine each cell’s unique identity, including variation in transcription and RNA splicing among diverse cell types. Previous studies led to the surprising observation that alternative splicing outcomes among single cells are highly variable and follow a bimodal pattern: a given cell consistently produces either one or the other isoform for a particular splicing choice, with few cells producing both isoforms. Here we show that this pattern arises almost entirely from technical limitations. We analyzed single cell alternative splicing in human and mouse single cell RNA-seq datasets, and modeled them with a probablistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms in single cells. This gives the appearance of a binary isoform distribution, even when the underlying reality is consistent with more than one isoform per cell. We show that accounting for the true amount of information recovered can produce biologically meaningful measurements of splicing in single cells.

scholarly journals Single-cell transcriptomics allows novel insights into aging and circadian processes

2020 ◽  
Vol 19 (5-6) ◽  
pp. 343-349
Author(s):  
Sara S Fonseca Costa ◽  
Marc Robinson-Rechavi ◽  
Jürgen A Ripperger
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Cellular Level ◽  
Biological Processes ◽  
New Methods ◽  
New Findings ◽  
Single Cell Rna Sequencing ◽  
Aging And Circadian Rhythms ◽  
Insight Into ◽  
Different Time Scales

Abstract Aging and circadian rhythms are two biological processes that affect an organism, although at different time scales. Nevertheless, due to the overlap of their actions, it was speculated that both interfere or interact with each other. However, to address this question, a much deeper insight into these processes is necessary, especially at the cellular level. New methods such as single-cell RNA-sequencing (scRNA-Seq) have the potential to close this gap in our knowledge. In this review, we analyze applications of scRNA-Seq from the aging and circadian rhythm fields and highlight new findings emerging from the analysis of single cells, especially in humans or rodents. Furthermore, we judge the potential of scRNA-Seq to identify common traits of both processes. Overall, this method offers several advantages over more traditional methods analyzing gene expression and will become an important tool to unravel the link between these biological processes.

scholarly journals Myeloid heterogeneity in kidney disease as revealed through single cell RNA sequencing

Kidney360 ◽  
2021 ◽  
pp. 10.34067/KID.0003682021
Author(s):  
Rachel M B Bell ◽  
Laura Denby
Keyword(s):  
Kidney Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Myeloid Cells ◽  
Rna Seq ◽  
Cellular Compartment ◽  
Single Cell Rna Sequencing ◽  
Health And Disease ◽  
Diseased Kidney

Kidney disease represents a global health burden of increasing prevalence and is an independent risk factor for cardiovascular disease. Myeloid cells are a major cellular compartment of the immune system; they are found in the healthy kidney and in increased numbers in the damaged and/or diseased kidney, where they act as key players in the progression of injury, inflammation and fibrosis. They possess enormous plasticity and heterogeneity, adopting different phenotypic and functional characteristics in response to stimuli in the local milieu. Though this inherent complexity remains to be fully understood in the kidney, advances in single-cell genomics promises to change this. Specifically, single-cell RNA sequencing (scRNA-seq) has had a transformative effect on kidney research, enabling the profiling and analysis of the transcriptomes of single cells at unprecedented resolution and throughput, and subsequent generation of cell atlases. Moving forward, combining scRNA- and single-nuclear RNA-seq with greater resolution spatial transcriptomics will allow spatial mapping of kidney disease of varying aetiology to further reveal the patterning of immune cells and non-immune renal cells. This review summarises the roles of myeloid cells in kidney health and disease, the experimental workflow in currently available scRNA-seq technologies and published findings using scRNA-seq in the context of myeloid cells and the kidney.

scholarly journals Comparison of Principal Component Analysis and t-Stochastic Neighbor Embedding with Distance Metric Modifications for Single-cell RNA-sequencing Data Analysis

2017 ◽  
Author(s):  
Haejoon (Ellen) Kwon ◽  
Jean Fan ◽  
Peter Kharchenko
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Component Analysis ◽  
Alternative Methods ◽  
Rna Seq ◽  
Distance Metric ◽  
Single Cell Rna Sequencing ◽  
Reliable Classification ◽  
Variable Genes

AbstractRecent developments in technological tools such as next generation sequencing along with peaking interest in the study of single cells has enabled single-cell RNA-sequencing, in which whole transcriptomes are analyzed on a single-cell level. Studies, however, have been hindered by the ability to effectively analyze these single cell RNA-seq datasets, due to the high-dimensional nature and intrinsic noise in the data. While many techniques have been introduced to reduce dimensionality of such data for visualization and subpopulation identification, the utility to identify new cellular subtypes in a reliable and robust manner remains unclear. Here, we compare dimensionality reduction visualization methods including principle component analysis and t-stochastic neighbor embedding along with various distance metric modifications to visualize single-cell RNA-seq datasets, and assess their performance in identifying known cellular subtypes. Our results suggest that selecting variable genes prior to analysis on single-cell RNA-seq data is vital to yield reliable classification, and that when variable genes are used, the choice of distance metric modification does not particularly influence the quality of classification. Still, in order to take advantage of all the gene expression information, alternative methods must be used for a reliable classification.

scholarly journals Oocytes, a single cell and a tissue

2020 ◽  
Author(s):  
Di Wu ◽  
Jurrien Dean
Keyword(s):  
Single Cell ◽  
Oocyte Maturation ◽  
Single Cells ◽  
Rna Seq ◽  
Single Cell Sequencing ◽  
Mouse Oocytes ◽  
Endogenous Genes ◽  
Insight Into

AbstractDevelopment of single cell sequencing allows detailing the transcriptome of individual oocytes. Here, we compare different RNA-seq datasets from single and pooled mouse oocytes and show higher reproducibility using single oocyte RNA-seq. We further demonstrate that UMI (unique molecular identifiers) based and other deduplication methods are limited in their ability to improve the precision of these datasets. Finally, for normalization of sample differences in cross-stage comparisons, we propose that external spike-in molecules are comparable to using the endogenous genes stably expressed during oocyte maturation. The ability to normalize data among single cells provides insight into the heterogeneity of mouse oocytes.

Comprehensive Bulk and Single Cell Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2906-2906 ◽  
Author(s):  
Jean Fan ◽  
Lili Wang ◽  
Angela N Brooks ◽  
Youzhong Wan ◽  
Donna S Neuberg ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Single Cells ◽  
Lymphocytic Leukemia ◽  
Rna Seq ◽  
Wild Type ◽  
Mutation Status ◽  
Total Rna ◽  
Gene Sets

Abstract Large-scale sequencing efforts have identified SF3B1 as arecurrently mutated gene in chronic lymphocytic leukemia (CLL). While SF3B1 mutations have been associated with adverse clinical outcome in CLL, mechanistic understanding of its role in the oncogenic phenotype remains lacking. We therefore undertook a comprehensive transcriptomic characterization of CLL in relation to SF3B1 mutation status at both bulk and single cell levels. We first profiled bulk mature poly-A selected RNA by sequencing (RNA-seq) from 37 CLLs (13 SF3B1 wild-type, 24 mutated). After identifying and classifying splice alterations using the tool JuncBASE, we found SF3B1 mutation to be associated with increased alternative splicing, with the most pervasive changes in 3' splice site selection. 304 alternatively spliced events were significantly associated with SF3B1 mutation, 4 of which we validated by qRT-PCR in 20 independent CLL samples with known SF3B1 mutation status. We further identified 1963 differentially expressed genes (q < 0.2) associated with SF3B1 mutation. By gene set enrichment analysis, SF3B1 mutation appeared to impact a variety of cancer and CLL-associated gene pathways, including DNA damage response, apoptosis regulation, chromatin remodeling, RNA processing, and Notch activation (q < 0.01). ~20% of these gene sets were also found to be significantly enriched for genes exhibiting alternative splicing in association with SF3B1 mutation. As SF3B1 acts at the level of pre-mRNA, we also performed bulk RNA-seq with total RNA libraries generated from 5 CLLs (2 SF3B1 wild-type, 3 with the common K700E mutation). We again observed an enrichment of 3' splice site changes, along with ~30% overlap of differentially expressed genes, and ~16% overlap of enriched gene sets with the aforementioned poly-A data analysis. One differentially over-expressed gene associated with SF3B1 mutation unique to this total RNA data analysis and validated by total RNA qPCR of independent CLL samples was TERC, an essential RNA component of telomerase that serves as a replication template during telomeric elongation. TERC is a non-polyadenylated transcript and thus was undetected by our previous poly-A selected RNA-seq and by targeted qRT-PCR of oligo dT-generated cDNA. Recent reports have highlighted the involvement of the spliceosome in telomerase RNA processing, and shorter telomere length of CLLs with SF3B1 mutation. Thus, although further investigation will be needed, our analyses suggest a potential mechanism by which SF3B1 mutation contributes to aberrant regulation of telomerase activity. Since SF3B1 is commonly found as a subclonal mutation in CLL, and because signals obtained from bulk analyses reflect only the average characteristics of the population, we assessed the transcriptomic effects of SF3B1 mutation in single cells within a subset of CLL cases. We developed a novel and sensitive microfluidic approach that performs multiplexed targeted amplification of RNA to simultaneously detect somatic mutation status, gene expression (96 targets), and alternative splicing (45 targets) within the same individual cell for 96 to 288 cells from 5 patients with different SF3B1 mutations. From the same patient sample, single cells with SF3B1 mutation generally exhibited increased alternative splicing for events identified from the bulk analysis, thus confirming the association of SF3B1 mutation with altered splicing at the single cell level. Different SF3B1 hotspot mutations within the HEAT repeat domains exhibited similar patterns of alternative splicing while a mutation outside of the repeat domain did not. Furthermore, we confirmed significant changes in gene expression between SF3B1 wild-type and mutant cells of target genes involved in the Notch pathway (NCOR2), cell cycle (CDKN2A, CCND1) and apoptosis (TXNIP). Consistent with these analyses, functional studies with overexpression of full-length mutated SF3B1 in a hematopoietic cell lines confirmed the modulation of these pathways by this putative CLL driver. Our high-resolution single cell analysis further uncovered 2 transcription factors strongly associated with SF3B1 mutation but not previously appreciated (KLF3 and KLF8). Our comprehensive transcriptomic analysis thus highlights SF3B1 mutation as an efficient mechanism by which a complex of changes relevant to CLL biology are generated that can contribute to disease progression. Disclosures Kipps: Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Li:Fluidigm: Employment. Livak:Fluidigm: Employment.

scholarly journals Single-Cell RNA Sequencing of Batch Chlamydomonas Cultures Reveals Heterogeneity in their Diurnal Cycle Phase

2021 ◽  
Author(s):  
Feiyang Ma ◽  
Patrice A Salomé ◽  
Sabeeha S Merchant ◽  
Matteo Pellegrini
Keyword(s):  
Cell Wall ◽  
Single Cell ◽  
Rna Sequencing ◽  
Environmental Changes ◽  
Single Cells ◽  
Nitrogen Deficiency ◽  
Cycle Phase ◽  
Rna Seq ◽  
Single Cell Rna Sequencing ◽  
A Cell

Abstract The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of its ease of culture in the laboratory. Genomic and systems biology approaches have previously described transcriptome responses to environmental changes using bulk data, thus representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing by the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample natural algal communities. Second, scRNA-seq successfully separated single cells into non-overlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest photosynthesis and cell division to economize resources. Notably, these groups of cells recapitulated known patterns observed with bulk RNA-seq, but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We document experimentally that bulk RNA-seq data represent an average of typically hidden heterogeneity in the population.

scholarly journals Single-Cell RNA Sequencing of Batch Chlamydomonas Cultures Reveals Heterogeneity in their Diurnal Cycle Phase

2020 ◽  
Author(s):  
Feiyang Ma ◽  
Patrice A. Salomé ◽  
Sabeeha S. Merchant ◽  
Matteo Pellegrini
Keyword(s):  
Cell Wall ◽  
Single Cell ◽  
Rna Sequencing ◽  
Diurnal Cycle ◽  
Single Cells ◽  
Nitrogen Deficiency ◽  
Cycle Phase ◽  
Rna Seq ◽  
Single Cell Rna Sequencing ◽  
A Cell

ABSTRACTThe photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of the facility with which it can be cultured in the laboratory. Genomic and systems biology approaches have previously been used to describe how the transcriptome responds to environmental changes, but this analysis has been limited to bulk data, representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing in the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample algae communities in the wild. Second, scRNA-seq successfully separated single cells into non-overlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest cell division to economize resources. Notably, these groups of cells recapitulated known patterns observed with bulk RNA-seq, but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We propose that bulk RNA-seq data represent an average of varied cell states that hides underappreciated heterogeneity.One-sentence summaryWe show that single-cell RNA-seq (scRNA-seq) can be applied to Chlamydomonas cultures to reveal the that heterogenity in bulk cultures is largely driven by diurnal cycle phasesThe author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantcell.org) is: Matteo Pellegrini ([email protected])

scholarly journals SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  
Keyword(s):  
Single Cell ◽  
Posttranslational Modification ◽  
Cellular Differentiation ◽  
Single Cells ◽  
Simultaneous Detection ◽  
Surface Protein ◽  
Rna Seq ◽  
Cell Level ◽  
Simultaneous Integration ◽  
Unique Surface

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.

scholarly journals Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sunny Z. Wu ◽  
Daniel L. Roden ◽  
Ghamdan Al-Eryani ◽  
Nenad Bartonicek ◽  
Kate Harvey ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Tumour Heterogeneity ◽  
Fresh Tissue ◽  
Human Cancers ◽  
Cryopreserved Cell ◽  
Single Cell Rna Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

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