scholarly journals Detecting differential alternative splicing events in scRNA-seq with or without UMIs

2019 ◽  
Author(s):  
Yu Hu ◽  
Kai Wang ◽  
Mingyao Li
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Analysis ◽  
High Sensitivity ◽  
Sequencing Depth ◽  
Cell Analysis ◽  
Technical Noise ◽  
Qrt Pcr ◽  
Single Cell Rna Sequencing

Analysis of alternative splicing in single-cell RNA sequencing (scRNA-seq) is challenging due to its inherent technical noise and generally low sequencing depth. We present SCATS (Single-Cell Analysis of Transcript Splicing) for differential alternative splicing (DAS) analysis for scRNA-seq data with or without unique molecular identifiers (UMIs). By modeling technical noise and grouping exons that originate from the same isoform(s), SCATS achieves high sensitivity to detect DAS events compared to Census, DEXSeq and MISO, and these events were confirmed by qRT-PCR experiment.

scholarly journals Preparation of single-cell suspension from mouse breast cancer focusing on preservation of original cell state information and cell type composition

2019 ◽  
Author(s):  
Abaffy Pavel ◽  
Lettlova Sandra ◽  
Truksa Jaroslav ◽  
Kubista Mikael ◽  
Sindelka Radek
Keyword(s):  
Gene Expression ◽  
Cell Suspension ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Single Cell Suspension ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Original Cell

SUMMARYSingle-cell analysis of gene expression has become a very popular method during the last decade. Unfortunately, appropriate standardization and workflow optimization remain elusive. The first step of the single cell analysis requires that the solid tissue be disassociated into a suspension of individual cells. However, during this step several technical bias can arise which can later result in the misinterpretation of the data. The goal of this study was to identify and quantify the effect of these technical factors on the quality of the single-cell suspension and the subsequent interpretation of the produced expression data. We tested the effects of various enzymes used for dissociation, several centrifugation forces, dissociation temperatures and the addition of Actinomycin D, a gene expression inhibitor. RT-qPCR was used to assess the effect from each parameter alteration, while a single-cell RNA sequencing experiment was used to confirm the optimized factors. Our concluding results provide a complete protocol for the tissue dissociation of mouse mammary tumour from 4T1 cells that preserves the original cell state and is suitable for any single-cell RNA sequencing analysis. Furthermore, our workflow may serve as a guide for the optimization of the dissociation procedure of any other tissue of interest, which would ultimately improve the reproducibility of the reported data.

scholarly journals Microfluidic platform accelerates tissue processing into single cells for molecular analysis and primary culture models

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jeremy A. Lombardo ◽  
Marzieh Aliaghaei ◽  
Quy H. Nguyen ◽  
Kai Kessenbrock ◽  
Jered B. Haun
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Cell Analysis ◽  
Processing Technologies ◽  
Microfluidic Platform ◽  
Tissue Processing ◽  
Single Cell Rna Sequencing ◽  
Culture Models ◽  
Tissue Digestion

AbstractTissues are complex mixtures of different cell subtypes, and this diversity is increasingly characterized using high-throughput single cell analysis methods. However, these efforts are hindered, as tissues must first be dissociated into single cell suspensions using methods that are often inefficient, labor-intensive, highly variable, and potentially biased towards certain cell subtypes. Here, we present a microfluidic platform consisting of three tissue processing technologies that combine tissue digestion, disaggregation, and filtration. The platform is evaluated using a diverse array of tissues. For kidney and mammary tumor, microfluidic processing produces 2.5-fold more single cells. Single cell RNA sequencing further reveals that endothelial cells, fibroblasts, and basal epithelium are enriched without affecting stress response. For liver and heart, processing time is dramatically reduced. We also demonstrate that recovery of cells from the system at periodic intervals during processing increases hepatocyte and cardiomyocyte numbers, as well as increases reproducibility from batch-to-batch for all tissues.

IMMU-51. SINGLE-CELL ANALYSIS OF TUMOR-ASSOCIATED MICROGLIA AND MACROPHAGES FROM HUMAN GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi104-vi104
Author(s):  
Atul Anand ◽  
Rikke Sick Andersen ◽  
Mark Burton ◽  
Dylan Scott Lykke Harwood ◽  
Frantz Rom Poulsen ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Primary Brain Tumor ◽  
Tumor Type ◽  
Cell Analysis ◽  
Data Set ◽  
Human Glioblastoma ◽  
Glioblastoma Patient ◽  
Single Cell Rna Sequencing ◽  
Therapeutic Problem

Abstract Patients with glioblastoma, the most frequent and malignant primary brain tumor type, have a poor prognosis with a median survival of 14 months. A major therapeutic problem is chemoresistance. In surgically removed glioblastoma tissue, tumor-associated microglia and macrophages (TAMs) constitute up to 30 % of the total cells. TAMs are capable of secreting cytokines, chemokines and growth factors, thereby influencing the tumor microenvironment. However, the existence of different TAM subtypes and their role in glioblastoma is not fully comprehended and rarely considered therapeutically. This could explain why many glioblastoma clinical trials fail despite of promising preclinical results. This project aims to interrogate the existence and characteristics of different TAM subtypes in human glioblastoma biopsies in order to identify novel subpopulations and therapeutic targets. To study the heterogeneity in TAMs, CD11b+ cells were isolated from glioblastoma patient′s tissue, and single-cell RNA sequencing was performed using the 10X Genomics Chromium platform for single-cell generation and an Illumina NovaSeq6000 system for sequencing. We have sequenced TAMs from three glioblastomas and CD11b+ cells from brain tissue adjacent to two brain metastases samples. In the filtered data set of almost 71,000 CD11b+ cells, we were able to identify recently described TAM populations, such as an interferon-induced, a phagocytic, a hypoxic and a proliferating subset. Interestingly, we also discovered potential novel TAM subsets, such as a pro-angiogenic subset. We have detected a TAM population which is more complex than the established M1 and M2 phenotypes, constituting novel TAM subsets. We are currently investigating these findings to validate specific markers associated with these subpopulations, and for the identification of novel clinically relevant targets.

How to Get Started with Single Cell RNA Sequencing Data Analysis

2021 ◽  
pp. ASN.2020121742 ◽  
Author(s):  
Michael S. Balzer ◽  
Ziyuan Ma ◽  
Jianfu Zhou ◽  
Amin Abedini ◽  
Katalin Susztak
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Epigenetic Changes ◽  
Sequencing Data ◽  
Single Experiment ◽  
Gene And Protein Expression ◽  
Single Cell Rna Sequencing ◽  
Analytical Tools ◽  
Sequencing Data Analysis

Over the last 5 years, single cell methods have enabled the monitoring of gene and protein expression, genetic, and epigenetic changes in thousands of individual cells in a single experiment. With the improved measurement and the decreasing cost of the reactions and sequencing, the size of these datasets is increasing rapidly. The critical bottleneck remains the analysis of the wealth of information generated by single cell experiments. In this review, we give a simplified overview of the analysis pipelines, as they are typically used in the field today. We aim to enable researchers starting out in single cell analysis to gain an overview of challenges and the most commonly used analytical tools. In addition, we hope to empower others to gain an understanding of how typical readouts from single cell datasets are presented in the published literature.

scholarly journals Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽  
2020 ◽  
Vol 371 (6531) ◽  
pp. eaba5257 ◽  
Author(s):  
Anna Kuchina ◽  
Leandra M. Brettner ◽  
Luana Paleologu ◽  
Charles M. Roco ◽  
Alexander B. Rosenberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cell Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Growth Stages ◽  
High Throughput Analysis ◽  
Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

High-throughput single-cell analysis of low copy number β-galactosidase by a laboratory-built high-sensitivity flow cytometer

2013 ◽  
Vol 48 ◽  
pp. 49-55 ◽  
Author(s):  
Lingling Yang ◽  
Tianxun Huang ◽  
Shaobin Zhu ◽  
Yingxing Zhou ◽  
Yunbin Jiang ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Copy Number ◽  
Single Cell Analysis ◽  
High Sensitivity ◽  
Flow Cytometer ◽  
Cell Analysis ◽  
Low Copy Number

scholarly journals Single-cell RNAseq reveals seven classes of colonic sensory neuron

Gut ◽  
2018 ◽  
Vol 68 (4) ◽  
pp. 633-644 ◽  
Author(s):  
James R F Hockley ◽  
Toni S Taylor ◽  
Gerard Callejo ◽  
Anna L Wilbrey ◽  
Alex Gutteridge ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sensory Neurons ◽  
Unsupervised Clustering ◽  
Sensory Innervation ◽  
Marker Genes ◽  
Specific Marker ◽  
Transcriptomic Profiling ◽  
Qrt Pcr ◽  
Single Cell Rna Sequencing

ObjectiveIntegration of nutritional, microbial and inflammatory events along the gut-brain axis can alter bowel physiology and organism behaviour. Colonic sensory neurons activate reflex pathways and give rise to conscious sensation, but the diversity and division of function within these neurons is poorly understood. The identification of signalling pathways contributing to visceral sensation is constrained by a paucity of molecular markers. Here we address this by comprehensive transcriptomic profiling and unsupervised clustering of individual mouse colonic sensory neurons.DesignUnbiased single-cell RNA-sequencing was performed on retrogradely traced mouse colonic sensory neurons isolated from both thoracolumbar (TL) and lumbosacral (LS) dorsal root ganglia associated with lumbar splanchnic and pelvic spinal pathways, respectively. Identified neuronal subtypes were validated by single-cell qRT-PCR, immunohistochemistry (IHC) and Ca2+-imaging.ResultsTranscriptomic profiling and unsupervised clustering of 314 colonic sensory neurons revealed seven neuronal subtypes. Of these, five neuronal subtypes accounted for 99% of TL neurons, with LS neurons almost exclusively populating the remaining two subtypes. We identify and classify neurons based on novel subtype-specific marker genes using single-cell qRT-PCR and IHC to validate subtypes derived from RNA-sequencing. Lastly, functional Ca2+-imaging was conducted on colonic sensory neurons to demonstrate subtype-selective differential agonist activation.ConclusionsWe identify seven subtypes of colonic sensory neurons using unbiased single-cell RNA-sequencing and confirm translation of patterning to protein expression, describing sensory diversity encompassing all modalities of colonic neuronal sensitivity. These results provide a pathway to molecular interrogation of colonic sensory innervation in health and disease, together with identifying novel targets for drug development.

scholarly journals SAVER: Gene expression recovery for UMI-based single cell RNA sequencing

2017 ◽  
Author(s):  
Mo Huang ◽  
Jingshu Wang ◽  
Eduardo Torre ◽  
Hannah Dueck ◽  
Sydney Shaffer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Analysis ◽  
Specific Gene ◽  
Recovery Method ◽  
Single Cell Rna Sequencing ◽  
Cell Gene Expression ◽  
Single Cell Profiling ◽  
Downstream Analysis

AbstractRapid advances in massively parallel single cell RNA sequencing (scRNA-seq) is paving the way for high-resolution single cell profiling of biological samples. In most scRNA-seq studies, only a small fraction of the transcripts present in each cell are sequenced. The efficiency, that is, the proportion of transcripts in the cell that are sequenced, can be especially low in highly parallelized experiments where the number of reads allocated for each cell is small. This leads to unreliable quantification of lowly and moderately expressed genes, resulting in extremely sparse data and hindering downstream analysis. To address this challenge, we introduce SAVER (Single-cell Analysis Via Expression Recovery), an expression recovery method for scRNA-seq that borrows information across genes and cells to impute the zeros as well as to improve the expression estimates for all genes. We show, by comparison to RNA fluorescence in situ hybridization (FISH) and by data down-sampling experiments, that SAVER reliably recovers cell-specific gene expression concentrations, cross-cell gene expression distributions, and gene-to-gene and cell-to-cell correlations. This improves the power and accuracy of any downstream analysis involving genes with low to moderate expression.

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