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Xu, Yunbo, Hongliang Hu, Jie Zheng, and Biaoru Li. "Feasibility of Whole RNA Sequencing from Single-Cell mRNA Amplification." Genetics Research International 2013 (December 23, 2013): 1–8. http://dx.doi.org/10.1155/2013/724124.
Повний текст джерелаАнотація:
Single-cell sampling with RNA-seq analysis plays an important role in reference laboratory; cytogenomic diagnosis for specimens on glass-slides or rare cells in circulating blood for tumor and genetic diseases; measurement of sensitivity and specificity in tumor-tissue genomic analysis with mixed-cells; mechanism analysis of differentiation and proliferation of cancer stem cell for academic purpose. Our single- cell RNA-seq technique shows that fragments were 250–450 bp after fragmentation, amplification, and adapter addition. There were 11.6 million reads mapped in raw sequencing reads (19.6 million). The numbers of mapped genes, mapped transcripts, and mapped exons were 31,332, 41,210, and 85,786, respectively. All QC results demonstrated that RNA-seq techniques could be used for single-cell genomic performance. Analysis of the mapped genes showed that the number of genes mapped by RNA-seq (6767 genes) was much higher than that of differential display (288 libraries) among similar specimens which we have developed and published. The single-cell RNA-seq can detect gene splicing using different subtype TGF-beta analysis. The results from using Q-rtPCR tests demonstrated that sensitivity is 76% and specificity is 55% from single-cell RNA-seq technique with some gene expression missing (2/8 genes). However, it will be feasible to use RNA-seq techniques to contribute to genomic medicine at single-cell level.
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Dhar, Manjima, Reem Khojah, Andy Tay, and Dino Di Carlo. "Research highlights: microfluidic-enabled single-cell epigenetics." Lab on a Chip 15, no. 21 (2015): 4109–13. http://dx.doi.org/10.1039/c5lc90101d.
Повний текст джерелаАнотація:
Barcoded droplet-based mRNA sequencing from thousands of single cells – Exploring regulatory differences in single cells with fluidics-controlled ATAC-seq – Towards single-cell chromatin immunoprecipitation.
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D’avola, D., C. Villacorta, S. N. Martins-Filho, A. Craig, I. Labgaa, J. V. Felden, A. Kimaada, et al. "Single-cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma." Journal of Hepatology 68 (April 2018): S445—S446. http://dx.doi.org/10.1016/s0168-8278(18)31131-0.
Повний текст джерела
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Nakamoto, Margaret, Mirko Corselli, Ian Taylor, and Suraj Saksena. "Single cell multiomic analysis of chronically stimulated T cells displaying hallmarks of T-cell exhaustion." Journal of Immunology 202, no. 1_Supplement (May 1, 2019): 189.18. http://dx.doi.org/10.4049/jimmunol.202.supp.189.18.
Повний текст джерелаАнотація:
Abstract T-cell exhaustion is a dysfunctional state caused by persistent antigen stimulation mediated by chronic infections or cancer. Current immunotherapy approaches focus on reinvigorating exhausted T cells through immune-receptor-blocking antibodies. A deeper understanding of the exhausted T-cell state is crucial for identification of new therapeutic targets. Single cell RNA-sequencing (scRNA-seq) is a powerful tool for resolving heterogeneity in complex systems like these; however the lack of protein information for the same cells can make it difficult to identify cells of interest or detect cellular responses. To resolve both mRNA and protein information in the same assay, we utilized DNA-conjugated BD™ AbSeq antibodies to profile protein and mRNA expression, using high-throughput sequencing analysis at the single cell level. Sorted T cells that had been transiently and chronically stimulated were multiplexed using the BD™ Single-Cell Multiplexing Kit and pooled before undergoing cell partitioning and cDNA capture on the BD Rhapsody™ system; this minimized batch effects and saved time and reagents. A panel of 400 mRNA targets alongside the 39-plex antibody panel was used for the study. We showed that cell-type resolution increased with higher protein plex, and the addition of mRNA information alongside protein markers revealed candidate protein markers for specific cell states. This study showcased the power of multiomics in analyzing heterogenous cell populations and cell states and answering complex biological questions. Research Use Only. Not for use in diagnostic or therapeutic procedures. BD, the BD Logo, and Rhapsody are trademarks of Becton, Dickinson and Company. © 2019 BD and its subsidiaries. All rights reserved.
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Lee, Jeongwoo, Do Young Hyeon, and Daehee Hwang. "Single-cell multiomics: technologies and data analysis methods." Experimental & Molecular Medicine 52, no. 9 (September 2020): 1428–42. http://dx.doi.org/10.1038/s12276-020-0420-2.
Повний текст джерелаАнотація:
Abstract Advances in single-cell isolation and barcoding technologies offer unprecedented opportunities to profile DNA, mRNA, and proteins at a single-cell resolution. Recently, bulk multiomics analyses, such as multidimensional genomic and proteogenomic analyses, have proven beneficial for obtaining a comprehensive understanding of cellular events. This benefit has facilitated the development of single-cell multiomics analysis, which enables cell type-specific gene regulation to be examined. The cardinal features of single-cell multiomics analysis include (1) technologies for single-cell isolation, barcoding, and sequencing to measure multiple types of molecules from individual cells and (2) the integrative analysis of molecules to characterize cell types and their functions regarding pathophysiological processes based on molecular signatures. Here, we summarize the technologies for single-cell multiomics analyses (mRNA-genome, mRNA-DNA methylation, mRNA-chromatin accessibility, and mRNA-protein) as well as the methods for the integrative analysis of single-cell multiomics data.
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Shi, Xiaoshan, Imteaz Siddique, Margaret Nakamoto, and Stefanie Mortimer. "Simultaneous mRNA, protein, and immune repertoire profiling of antigen-specific T cells by single cell sequencing." Journal of Immunology 204, no. 1_Supplement (May 1, 2020): 246.17. http://dx.doi.org/10.4049/jimmunol.204.supp.246.17.
Повний текст джерелаАнотація:
Abstract High-throughput single cell RNA-seq (scRNA-seq) has transformed our understanding of complex and heterogenous immune populations. New advances in scRNA-seq are expanding the molecules that can be profiled at the single cell level, such as oligo-conjugated antibody technologies that enable protein expression profiling alongside mRNA. Although the ability to sequence the immune repertoire can provide crucial insights into understanding the complexities of the adaptive immune system and advancing discoveries in immuno-oncology, the ability to extract this information from single cells requires new technology to profile regions of the mRNA that are missed by conventional 3′ scRNA-seq. In this study we utilized an ex vivo antigen stimulation system to measure antigen-specific T-cell activation and clonal amplification. Stimulated T cells from two donors were loaded onto the BD Rhapsody™ Single-Cell Analysis System to extract immune repertoire information in addition to gene and protein expression information from the same cells. In a single workflow, we profiled a panel of 400 mRNA targets, 20 BD® AbSeq protein markers associated with different status of T-cell activation, and the hypervariable region of T-cell receptors at the single cell resolution. The study is a proof of concept of combining mRNA, protein and immune repertoire analysis at the single cell level to deconvolute the heterogeneity and different activation of stimulated T cells. For Research Use Only. Not for use in diagnostic or therapeutic procedures. BD, the BD Logo, and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2019 BD. All rights reserved.
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Liu, Wendao, and Noam Shomron. "Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data." Journal of Personalized Medicine 12, no. 10 (October 21, 2022): 1750. http://dx.doi.org/10.3390/jpm12101750.
Повний текст джерелаАнотація:
MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, and thus reduce target gene expression levels and expression variability, also known as ‘noise’. Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells. To evaluate scRNA-seq as a tool for investigating miRNA regulation, we analyzed datasets with both mRNA and miRNA expression in single-cell format. We found that miRNAs slightly reduce the expression noise of target genes; however, this effect is easily masked by strong technical noise from scRNA-seq. We suggest improvements aimed at reducing technical noise, which can be implemented in experimental design and computational analysis prior to running scRNA-seq. Our study provides useful guidelines for experiments that evaluate the effect of miRNAs on mRNA expression from scRNA-seq.
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Schoettle, Louis, Xixi Wei, Marlene Garcia-Neurer, Veronkia Zarnitsyna, Rustom Antia, Hao Yan, and Joseph Blattman. "DNA origami: single cell analysis of T cell receptors without single cell sorting. (LYM7P.719)." Journal of Immunology 192, no. 1_Supplement (May 1, 2014): 193.7. http://dx.doi.org/10.4049/jimmunol.192.supp.193.7.
Повний текст джерелаАнотація:
Abstract The immune system must be able to recognize virtually any pathogen (diversity) while maintaining enough cells specific for each pathogen in order to mount an effective response (protection). T cells generate diversity by imprecise joining of gene segments to generate alpha/beta heterodimeric receptors. Linking sequence information for TCRα and TCRβ from individual cells has been problematic due to the cost of single cell sorting and inadequate molecular approaches for linking mRNA encoding these proteins. We have developed novel DNA origami nanostructures to capture and protect both TCRα and TCRβ mRNA from individual cells, which can then be physically linked via a unique dual-primed reverse-transcription and ligation reaction to generate single amplicons containing both TCR from individual cells for use in next generation sequencing. We have demonstrated high efficiency transfection and recovery of DNA origami, optimized methods for purification with bound TCR mRNA, and validated this approach with transgenic T cells expressing a known TCR sequence. Surprisingly, we find that <1% of TCR are shared even between genetically identical individuals, challenging the idea of “public” TCR. This approach is directly amenable to single cell analysis of other immune receptors (or other species) by relatively simple modifications of the origami sequences, and could be applied to virtually any heterogeneous cell population for which sequence information on any two genes is required.
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Li, Jiawei, Yi Zhang, Cheng Yang, and Ruiming Rong. "Discrepant mRNA and Protein Expression in Immune Cells." Current Genomics 21, no. 8 (December 21, 2020): 560–63. http://dx.doi.org/10.2174/1389202921999200716103758.
Повний текст джерелаАнотація:
With the development of single-cell mRNA sequencing (scRNA-seq), researchers have attempted to identify new methods for performing in-depth studies of immune cells. However, the discrepancies between the mRNA levels and the levels of surface proteins have confused many researchers. Here, we report a significant and interesting phenomenon in which the mRNA and protein expression levels were mismatched in immune cells. We concluded that scRNA-seq should be combined with other sequencing methods in single-cell studies (e.g., CITE-seq). The simultaneous assessment of both mRNA and protein expression will enhance the precision and credibility of the results.
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Battich, Nico, Joep Beumer, Buys de Barbanson, Lenno Krenning, Chloé S. Baron, Marvin E. Tanenbaum, Hans Clevers, and Alexander van Oudenaarden. "Sequencing metabolically labeled transcripts in single cells reveals mRNA turnover strategies." Science 367, no. 6482 (March 5, 2020): 1151–56. http://dx.doi.org/10.1126/science.aax3072.
Повний текст джерелаАнотація:
The regulation of messenger RNA levels in mammalian cells can be achieved by the modulation of synthesis and degradation rates. Metabolic RNA-labeling experiments in bulk have quantified these rates using relatively homogeneous cell populations. However, to determine these rates during complex dynamical processes, for instance during cellular differentiation, single-cell resolution is required. Therefore, we developed a method that simultaneously quantifies metabolically labeled and preexisting unlabeled transcripts in thousands of individual cells. We determined synthesis and degradation rates during the cell cycle and during differentiation of intestinal stem cells, revealing major regulatory strategies. These strategies have distinct consequences for controlling the dynamic range and precision of gene expression. These findings advance our understanding of how individual cells in heterogeneous populations shape their gene expression dynamics.
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Wineberg, Yishay, Tali Hana Bar-Lev, Anna Futorian, Nissim Ben-Haim, Leah Armon, Debby Ickowicz, Sarit Oriel, et al. "Single-Cell RNA Sequencing Reveals mRNA Splice Isoform Switching during Kidney Development." Journal of the American Society of Nephrology 31, no. 10 (July 10, 2020): 2278–91. http://dx.doi.org/10.1681/asn.2019080770.
Повний текст джерелаАнотація:
BackgroundDuring mammalian kidney development, nephron progenitors undergo a mesenchymal-to-epithelial transition and eventually differentiate into the various tubular segments of the nephron. Recently, Drop-seq single-cell RNA sequencing technology for measuring gene expression from thousands of individual cells identified the different cell types in the developing kidney. However, that analysis did not include the additional layer of heterogeneity that alternative mRNA splicing creates.MethodsFull transcript length single-cell RNA sequencing characterized the transcriptomes of 544 individual cells from mouse embryonic kidneys.ResultsGene expression levels measured with full transcript length single-cell RNA sequencing identified each cell type. Further analysis comprehensively characterized splice isoform switching during the transition between mesenchymal and epithelial cellular states, which is a key transitional process in kidney development. The study also identified several putative splicing regulators, including the genes Esrp1/2 and Rbfox1/2.ConclusionsDiscovery of the sets of genes that are alternatively spliced as the fetal kidney mesenchyme differentiates into tubular epithelium will improve our understanding of the molecular mechanisms that drive kidney development.
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Pan, Lu, Huy Q. Dinh, Yudi Pawitan, and Trung Nghia Vu. "Isoform-level quantification for single-cell RNA sequencing." Bioinformatics 38, no. 5 (December 2, 2021): 1287–94. http://dx.doi.org/10.1093/bioinformatics/btab807.
Повний текст джерелаАнотація:
Abstract Motivation RNA expression at isoform level is biologically more informative than at gene level and can potentially reveal cellular subsets and corresponding biomarkers that are not visible at gene level. However, due to the strong 3ʹ bias sequencing protocol, mRNA quantification for high-throughput single-cell RNA sequencing such as Chromium Single Cell 3ʹ 10× Genomics is currently performed at the gene level. Results We have developed an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. The method, called Scasa, compares well in simulations against competing approaches including Alevin, Cellranger, Kallisto, Salmon, Terminus and STARsolo at both isoform- and gene-level expression. The reanalysis of a CITE-Seq dataset with isoform-based Scasa reveals a subgroup of CD14 monocytes missed by gene-based methods. Availability and implementation Implementation of Scasa including source code, documentation, tutorials and test data supporting this study is available at Github: https://github.com/eudoraleer/scasa and Zenodo: https://doi.org/10.5281/zenodo.5712503. Supplementary information Supplementary data are available at Bioinformatics online.
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Smith, Samantha L., Philippa R. Kennedy, Kevin B. Stacey, Jonathan D. Worboys, Annie Yarwood, Seungmae Seo, Everardo Hegewisch Solloa, et al. "Diversity of peripheral blood human NK cells identified by single-cell RNA sequencing." Blood Advances 4, no. 7 (April 9, 2020): 1388–406. http://dx.doi.org/10.1182/bloodadvances.2019000699.
Повний текст джерелаАнотація:
Abstract Human natural killer (NK) cells in peripheral blood perform many functions, and classification of specific subsets has been a longstanding goal. We report single-cell RNA sequencing of NK cells, comparing gene expression in unstimulated and interleukin (IL)-2–activated cells from healthy cytomegalovirus (CMV)-negative donors. Three NK cell subsets resembled well-described populations; CD56brightCD16−, CD56dimCD16+CD57−, and CD56dimCD16+CD57+. CD56dimCD16+CD57− cells subdivided to include a population with higher chemokine mRNA and increased frequency of killer-cell immunoglobulin-like receptor expression. Three novel human blood NK cell populations were identified: a population of type I interferon–responding NK cells that were CD56neg; a population exhibiting a cytokine-induced memory-like phenotype, including increased granzyme B mRNA in response to IL-2; and finally, a small population, with low ribosomal expression, downregulation of oxidative phosphorylation, and high levels of immediate early response genes indicative of cellular activation. Analysis of CMV+ donors established that CMV altered the proportion of NK cells in each subset, especially an increase in adaptive NK cells, as well as gene regulation within each subset. Together, these data establish an unexpected diversity in blood NK cells and provide a new framework for analyzing NK cell responses in health and disease.
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Kupke, Sascha Young, Lam-Ha Ly, Stefan Thomas Börno, Alexander Ruff, Bernd Timmermann, Martin Vingron, Stefan Haas, and Udo Reichl. "Single-Cell Analysis Uncovers a Vast Diversity in Intracellular Viral Defective Interfering RNA Content Affecting the Large Cell-to-Cell Heterogeneity in Influenza A Virus Replication." Viruses 12, no. 1 (January 7, 2020): 71. http://dx.doi.org/10.3390/v12010071.
Повний текст джерелаАнотація:
Virus replication displays a large cell-to-cell heterogeneity; yet, not all sources of this variability are known. Here, we study the effect of defective interfering (DI) particle (DIP) co-infection on cell-to-cell variability in influenza A virus (IAV) replication. DIPs contain a large internal deletion in one of their eight viral RNAs (vRNA) and are, thus, defective in virus replication. Moreover, they interfere with virus replication. Using single-cell isolation and reverse transcription polymerase chain reaction, we uncovered a large between-cell heterogeneity in the DI vRNA content of infected cells, which was confirmed for DI mRNAs by single-cell RNA sequencing. A high load of intracellular DI vRNAs and DI mRNAs was found in low-productive cells, indicating their contribution to the large cell-to-cell variability in virus release. Furthermore, we show that the magnitude of host cell mRNA expression (some factors may inhibit virus replication), but not the ribosome content, may further affect the strength of single-cell virus replication. Finally, we show that the load of viral mRNAs (facilitating viral protein production) and the DI mRNA content are, independently from one another, connected with single-cell virus production. Together, these insights advance single-cell virology research toward the elucidation of the complex multi-parametric origin of the large cell-to-cell heterogeneity in virus infections.
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Martin, Jody, H. Christina Fan, and Eleen Shum. "Oligo-conjugated antibodies (Ab-seq) and massively parallel single cell sequencing reveal the high parameter correlation of protein and mRNA expression in individual immune cells." Journal of Immunology 200, no. 1_Supplement (May 1, 2018): 120.33. http://dx.doi.org/10.4049/jimmunol.200.supp.120.33.
Повний текст джерелаАнотація:
Abstract Single-Cell mRNA sequencing has enhanced our knowledge of the cell populations found in individual tissues or disease states. However, low correlation between mRNA and protein expression levels hinders our understanding of biology and disease. Traditional single cell protein assays are limited in the number of parameters that can be achieved within one experiment. Here we use oligo-conjugated antibodies (Ab-seq) in combination with massively parallel single cell mRNA sequencing on the BD Rhapsody™ platform to simultaneously measure the protein and mRNA content of individual human blood cells (PBMCs). To accomplish this, a 30+ parameter Ab-seq panel against immune relevant cell surface markers was paired with the BD Rhapsody™ Immune Response panel (a targeted gene expression panel consisting of 399 targets). The Multi-omics data from this single workflow experiment provides a measurement of both gene expression and protein expression. The digital measurements are rendered free of PCR bias through the use of the unique molecular indices (UMIs). Our results show that protein expression detected with Ab-seq is highly sensitive and specific. Protein expression patterns correlate well with results from flow cytometry data on the same samples. Ab-seq allowed the robust detection of expressed genes even when their cognate mRNA transcripts have low abundance. Certain markers cannot be easily distinguished at the mRNA level (i.e. isoforms CD45RA and CD45RO) but are easily distinguished at the protein level. Our study shows successful analysis of protein and mRNA expression data within a single workflow, and should enable the further elucidation single cells within different tissues, developmental time points, and disease states.
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Yang, Yufan, Longlong Xie, Yinghui Peng, Haipeng Yan, Jiaotian Huang, Zhenghui Xiao, and Xiulan Lu. "Single-Cell Transcriptional Profiling Reveals Low-Level Tragus Stimulation Improves Sepsis-Induced Myocardial Dysfunction by Promoting M2 Macrophage Polarization." Oxidative Medicine and Cellular Longevity 2022 (October 15, 2022): 1–16. http://dx.doi.org/10.1155/2022/3327583.
Повний текст джерелаАнотація:
Background. Sepsis can lead to multiple organ damage, of which the heart is one of the most vulnerable organs. Vagal nerve stimulation can reduce myocardial injury in sepsis and improve survival rates. However, the potential impact of low-level tragus stimulation and disparate cell populations on sepsis-induced myocardial dysfunction remains undetermined. Methods. A cardiac single-cell transcriptomic approach was used for characterizing cardiac cell populations that form the heart. Single-cell mRNA sequencing data were used for selecting all cardiac macrophages from CD45+ cells. Then, echocardiography, western blot, flow cytometry, immunofluorescence, and immunohistochemistry were performed to verify the single-cell mRNA sequencing results. Results. Using single-cell mRNA sequencing data, we uncovered the multiple cell populations contributing to myocardial injury in sepsis under low-level tragus stimulation, thereby illustrating a comprehensive map of the cardiac cellular landscape. Pseudotiming analysis in single-cell sequencing showed that low-level vagal nerve stimulation played an anti-inflammatory role by promoting cardiac monocytes into M2 macrophages, which significantly increased α7nAChR expression in heart tissues. Echocardiography assessment indicated that low-level vagal nerve stimulation could also improve cardiac functions in mice with sepsis-induced myocardial dysfunction. In addition, the heart tissues of mice from the sepsis group with low-level tragus stimulation had significantly lower interleukin-1β expression levels than those from the sepsis group. Flow cytometry analysis showed that different acetylcholine concentrations promoted cardiac monocytes into M2 macrophages in in vitro experiments. Conclusion. Low-level tragus stimulation could improve sepsis-induced myocardial dysfunction by promoting cardiac monocytes to M2 macrophages.
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Sountoulidis, Alexandros, Andreas Liontos, Hong Phuong Nguyen, Alexandra B. Firsova, Athanasios Fysikopoulos, Xiaoyan Qian, Werner Seeger, Erik Sundström, Mats Nilsson, and Christos Samakovlis. "SCRINSHOT enables spatial mapping of cell states in tissue sections with single-cell resolution." PLOS Biology 18, no. 11 (November 20, 2020): e3000675. http://dx.doi.org/10.1371/journal.pbio.3000675.
Повний текст джерелаАнотація:
Changes in cell identities and positions underlie tissue development and disease progression. Although single-cell mRNA sequencing (scRNA-Seq) methods rapidly generate extensive lists of cell states, spatially resolved single-cell mapping presents a challenging task. We developed SCRINSHOT (Single-Cell Resolution IN Situ Hybridization On Tissues), a sensitive, multiplex RNA mapping approach. Direct hybridization of padlock probes on mRNA is followed by circularization with SplintR ligase and rolling circle amplification (RCA) of the hybridized padlock probes. Sequential detection of RCA-products using fluorophore-labeled oligonucleotides profiles thousands of cells in tissue sections. We evaluated SCRINSHOT specificity and sensitivity on murine and human organs. SCRINSHOT quantification of marker gene expression shows high correlation with published scRNA-Seq data over a broad range of gene expression levels. We demonstrate the utility of SCRINSHOT by mapping the locations of abundant and rare cell types along the murine airways. The amenability, multiplexity, and quantitative qualities of SCRINSHOT facilitate single-cell mRNA profiling of cell-state alterations in tissues under a variety of native and experimental conditions.
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Song, Hye-Won, Gisele V. Baracho, Nidhanjali Bansal, Ian Taylor, Eleen Shum, Stephanie Widmann, and Stefanie Mortimer. "Simultaneous analysis of mRNA and proteins in immune cells using the BD&[trade] Single-Cell Multiplexing Kit and BD&[trade] AbSeq reagents on the BD Rhapsody&[trade] system for high-resolution interrogation of differential immune regulation." Journal of Immunology 202, no. 1_Supplement (May 1, 2019): 60.19. http://dx.doi.org/10.4049/jimmunol.202.supp.60.19.
Повний текст джерелаАнотація:
Abstract Obesity can weaken the body’s immune system and trigger chronic inflammation. To understand the root cause of this problem, we used single cell sequencing to examine thousands of immune cells isolated from primary and secondary lymphoid organs as well as adipose tissue and compared a diet-induced obesity mouse model with control mice. Cells were stained with 30 DNA-barcoded antibodies from BD™ AbSeq reagents to enable multiomic analysis, i.e. examining protein alongside mRNA expression in tandem. We also utilized DNA-barcoded universal antibodies from the BD™ Single-Cell Multiplexing Kit, which allowed us to combine 8 samples from different mice and tissue types into a single pooled sample, significantly reducing experimental scale and cost while eliminating potential batch effects. The pooled samples were loaded on the BD Rhapsody™ system to perform cell lysis and individual mRNA and cell barcoding, allowing measurement of ~400 immune-related mRNAs and 30 proteins at the single cell level. We were able to de-multiplex the pooled samples with high specificity after sequencing. The targeted mRNA and AbSeq panel provided robust clustering of immune cell types and showed that genes related to critical immune responses, including inflammation and lymphocyte activation, are differentially regulated in specific immune-cell subsets in obese mouse. Using this multiomic analysis of genes differentially regulated in immune cells from different tissues, we propose a model to explain the immuno-phenotype we observed in obese mouse. For Research Use Only. Not for use in diagnostic or therapeutic procedures. BD, the BD Logo, and Rhapsody are trademarks of Becton, Dickinson and Company. © 2019 BD and its subsidiaries. All rights reserved.
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Zhao, Kangqi, Ming Hao, Qian Xu, Hongxue Li, Chengye Xu, Ziyu Meng, and Hongyu Kuang. "Current Advances in Single-Cell RNA Sequencing in Diabetic Retinopathy." Journal of Biomedical Nanotechnology 20, no. 2 (February 1, 2024): 197–206. http://dx.doi.org/10.1166/jbn.2024.3770.
Повний текст джерелаАнотація:
With the development of high-throughput sequencing technology, humans have been able to conduct large-scale analysis of DNA sequence, chromatin structure, RNA transcripts, proteins, metabolites and other genomes and their products. Traditional high-throughput transcriptome sequencing techniques based on tissue samples (RNA Seq) are used to centrally sequence thousands of cells, each of which varies in size, protein levels, and mRNA expression transcription. Measuring the average of multiple cells grouped together can mask significant differences in gene expression between cells. Single-cell RNA sequencing is a technique for high-throughput sequencing of the genome, transcriptome, and epigenome at the single-cell level. Based on the single cell RNA transcription map, the intraocular cells can be distinguished from other subtypes, and the different subtypes are found to have significant differences in morphology, physiology and specific expression genes. In recent years, the application of single-cell RNA sequencing technology in the field of ophthalmology has increased, mainly including cell type and cell subtype identification, retinal development process, and eye disease research. This paper systematically summarized the latest application of single-cell sequencing technology in the field of diabetic retinopathy, and summarized marker genes and potential therapeutic targets. It has guiding significance for the clinical treatment of diabetic retinopathy.
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Hazzard, Brittany, Juliana M. Sá, Angela C. Ellis, Tales V. Pascini, Shuchi Amin, Thomas E. Wellems, and David Serre. "Long read single cell RNA sequencing reveals the isoform diversity of Plasmodium vivax transcripts." PLOS Neglected Tropical Diseases 16, no. 12 (December 16, 2022): e0010991. http://dx.doi.org/10.1371/journal.pntd.0010991.
Повний текст джерелаАнотація:
Plasmodium vivax infections often consist of heterogenous populations of parasites at different developmental stages and with distinct transcriptional profiles, which complicates gene expression analyses. The advent of single cell RNA sequencing (scRNA-seq) enabled disentangling this complexity and has provided robust and stage-specific characterization of Plasmodium gene expression. However, scRNA-seq information is typically derived from the end of each mRNA molecule (usually the 3’-end) and therefore fails to capture the diversity in transcript isoforms documented in bulk RNA-seq data. Here, we describe the sequencing of scRNA-seq libraries using Pacific Biosciences (PacBio) chemistry to characterize full-length Plasmodium vivax transcripts from single cell parasites. Our results show that many P. vivax genes are transcribed into multiple isoforms, primarily through variations in untranslated region (UTR) length or splicing, and that the expression of many isoforms is developmentally regulated. Our findings demonstrate that long read sequencing can be used to characterize mRNA molecules at the single cell level and provides an additional resource to better understand the regulation of gene expression throughout the Plasmodium life cycle.
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Borcherding, Nicholas, Sydney Crotts, Luana Ortolan, Nicholas Bormann, and Ali Jabbari. "Single-Cell mRNA Sequencing of Murine and Human Alopecia Areata Identifies Immune Cell Profiles Predictive of Human Disease State." American Journal of Clinical Pathology 154, Supplement_1 (October 2020): S5. http://dx.doi.org/10.1093/ajcp/aqaa137.008.
Повний текст джерелаАнотація:
Abstract Alopecia areata (AA) is one of the most common autoimmune conditions, presenting initially with loss of hair without overt skin changes. The unremarkable appearance of the skin surface contrasts with the complex immune activity occurring at the hair follicle. AA pathogenesis is due to the loss of immune privilege of the hair follicle leading to autoimmune attack. Although the literature has focused on CD8+ T cells, vital roles for CD4+ T cells and antigen-presenting cells have been suggested. Here, we use single-cell mRNA sequencing to reveal distinct expression profiles of immune cells in AA. We found clonal expansions of both CD4+ and CD8+ T cells, with shared clonotypes across varied transcriptional states. Demonstrating distinct gene and clonotypic variations, AA murine data were used to generate highly predictive models of human AA disease. In order to corroborate the results, single-cell sequencing of T cells in human AA recapitulated the clonotypic findings and the gene expression of the predictive models. Taken together, this work demonstrates the unique transcriptomic environment of AA skin, not just limited to CD8+ T cells. This work also represents the first single-cell sequencing for the autoimmune condition AA.
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Shi, Samuel X., Cynthia Sakofsky, Zhiqi Zhang, Samatha Vadrevu, Xiaoshan Shi, Hye-Won Song, and Aruna Ayer. "Abstract 335: BD®OMICS-Guard Sample Preservation Buffer preserves mRNA and cell surface epitopes for single-cell sequencing applications." Cancer Research 84, no. 6_Supplement (March 22, 2024): 335. http://dx.doi.org/10.1158/1538-7445.am2024-335.
Повний текст джерелаАнотація:
Abstract Multiomics has emerged as a powerful tool to derive insights on the transcriptomic and proteomic data of human cancer samples and preclinical models of blood and tumor malignancies. Due to the sensitivity of sequencing techniques, sample quality and stability can potentially interfere with results. BD® OMICS-Guard Sample Preservation Buffer (SPB), a novel preservation solution, allows cells and bulk tissues to be stored for up to 72h at 4 °C, while reliably capturing the true biology of cells. This reagent gently preserves mRNA and protein integrity without the traditional cross-linking and harsh fixatives, increasing flexibility and expanding options for study designs. Here, we showcase the preservation properties ofthis reagent for multiomic readouts in human cells and mouse tissue across three different timepoints.BD® OMICS-Guard SPB’s preservation of mRNA from human PBMC and bulk mouse spleen tissues wasevidenced by WTA for differentially expressed genes in samples preserved for 24, 48 and 72h comparedto fresh/unpreserved controls. Protein epitope preservation was demonstrated via CITE-Seq assay withthe BD® AbSeq Human Immune Discovery Panel (human PBMC) or a 30-plex panel of anti-mouse BD®AbSeq Antibody-Conjugated Oligonucleotides (mouse splenocytes) and confirmed with multicolor flowcytometry. For both sample types, high correlation R2 values (>0.87) were calculated for the preservation time points versus fresh controls. Concomitant flow cytometry analysis of major cell types and surface protein expression was consistent with sequencing data for all samples. Specificity and sensitivity of major cell type markers and cell surface proteins across cell types and time is visualized in the BD®AbSeq Antibody-generated heatmap for each sample. Additionally, BD® OMICS-Guard SPB maintains mRNA integrity in targeted gene assays and VDJ full-length assays, suggesting robust preservation of select transcripts readily interrogated in single-cell profiling. Batch effect across time and technical replicates for both sample types was limited with the BD Rhapsody™ HT Xpress System and delineated by donor/sample specific tSNEs across time. We demonstrate that the BD® OMICS-Guard Sample Preservation Buffer effectively preserves both mRNA and surface proteins for single-cell experiments. BD® OMICS-Guard SPB allows the convenient preservation of samples such as tumor biopsies to be collected and stored for up to 72h at 4 °C while maintaining mRNA and protein integrity, allowing the flexibility for precious samples to be potentially shipped to a central sequencing site to ensure standardized sequencing workflows. For Research Use Only. Not for use in diagnostic or therapeutic procedures.BD and BD Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2023 BD. All rights reserved. Citation Format: Samuel X. Shi, Cynthia Sakofsky, Zhiqi Zhang, Samatha Vadrevu, Xiaoshan Shi, Hye-Won Song, Aruna Ayer. BD®OMICS-Guard Sample Preservation Buffer preserves mRNA and cell surface epitopes for single-cell sequencing applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 335.
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Foster, Stephany, Nathalie Oulhen, and Gary Wessel. "A single cell RNA sequencing resource for early sea urchin development." Development 147, no. 17 (August 18, 2020): dev191528. http://dx.doi.org/10.1242/dev.191528.
Повний текст джерелаАнотація:
ABSTRACTIdentifying cell states during development from their mRNA profiles provides insight into their gene regulatory network. Here, we leverage the sea urchin embryo for its well-established gene regulatory network to interrogate the embryo using single cell RNA sequencing. We tested eight developmental stages in Strongylocentrotus purpuratus, from the eight-cell stage to late in gastrulation. We used these datasets to parse out 22 major cell states of the embryo, focusing on key transition stages for cell type specification of each germ layer. Subclustering of these major embryonic domains revealed over 50 cell states with distinct transcript profiles. Furthermore, we identified the transcript profile of two cell states expressing germ cell factors, one we conclude represents the primordial germ cells and the other state is transiently present during gastrulation. We hypothesize that these cells of the Veg2 tier of the early embryo represent a lineage that converts to the germ line when the primordial germ cells are deleted. This broad resource will hopefully enable the community to identify other cell states and genes of interest to expose the underpinning of developmental mechanisms.
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Loi, Danson S. C., Lei Yu, and Angela R. Wu. "Effective ribosomal RNA depletion for single-cell total RNA-seq by scDASH." PeerJ 9 (January 15, 2021): e10717. http://dx.doi.org/10.7717/peerj.10717.
Повний текст джерелаАнотація:
A decade since its invention, single-cell RNA sequencing (scRNA-seq) has become a mainstay technology for profiling transcriptional heterogeneity in individual cells. Yet, most existing scRNA-seq methods capture only polyadenylated mRNA to avoid the cost of sequencing non-messenger transcripts, such as ribosomal RNA (rRNA), that are usually not of-interest. Hence, there are not very many protocols that enable single-cell analysis of total RNA. We adapted a method called DASH (Depletion of Abundant Sequences by Hybridisation) to make it suitable for depleting rRNA sequences from single-cell total RNA-seq libraries. Our analyses show that our single-cell DASH (scDASH) method can effectively deplete rRNAs from sequencing libraries with minimal off-target non-specificity. Importantly, as a result of depleting the rRNA, the rest of the transcriptome is significantly enriched for detection.
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Song, Ye Na, and Man Ryul Lee. "Single-cell transcriptomics of lung organoids." Organoid 1 (October 19, 2021): e9. http://dx.doi.org/10.51335/organoid.2021.1.e9.
Повний текст джерелаАнотація:
The in vitro application of human pluripotent stem cell- or adult stem cell-derived lung organoids has the potential to revolutionize lung disease research, but there are several limitations in the consistent implementation of lung organoids resulting from the structural diversity of the lung tissues and the variety of cell types (more than 40 resident cell types) populating these tissues. However, the evaluation of these complexities using a combination of lung organoids and single-cell transcriptomics has made it possible to identify several key cell types and sub-populations critical to the development of robust in vitro organoid models. Recent studies have started to use stem cells to produce these organoids, making it possible to mimic complex 3-dimensional tissues. Furthermore, single-cell mRNA sequencing allows critical comparisons of the transcriptome, which may help focus future research in the field of lung disease.
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Stancill, Jennifer S., Moujtaba Y. Kasmani, Achia Khatun, Weiguo Cui, and John A. Corbett. "Single-cell RNA sequencing of mouse islets exposed to proinflammatory cytokines." Life Science Alliance 4, no. 6 (April 21, 2021): e202000949. http://dx.doi.org/10.26508/lsa.202000949.
Повний текст джерелаАнотація:
Exposure to proinflammatory cytokines is believed to contribute to pancreatic β-cell damage during diabetes development. Although some cytokine-mediated changes in islet gene expression are known, the heterogeneity of the response is not well-understood. After 6-h treatment with IL-1β and IFN-γ alone or together, mouse islets were subjected to single-cell RNA sequencing. Treatment with both cytokines together led to expression of inducible nitric oxide synthase mRNA (Nos2) and antiviral and immune-associated genes in a subset of β-cells. Interestingly, IL-1β alone activated antiviral genes. Subsets of δ- and α-cells expressed Nos2 and exhibited similar gene expression changes as β-cells, including increased expression of antiviral genes and repression of identity genes. Finally, cytokine responsiveness was inversely correlated with expression of genes encoding heat shock proteins. Our findings show that all islet endocrine cell types respond to cytokines, IL-1β induces the expression of protective genes, and cellular stress gene expression is associated with inhibition of cytokine signaling.
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Luo, Jian-Hua, Silvia Liu, Bao-Guo Ren, and Yan-Ping Yu. "Abstract LB253: Long-read single-cell sequencing of liver cancer." Cancer Research 83, no. 8_Supplement (April 14, 2023): LB253. http://dx.doi.org/10.1158/1538-7445.am2023-lb253.
Повний текст джерелаАнотація:
Abstract The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Protein mutation is essential in species evolution and cancer development. Accurate Long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPseq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection (UMAP) analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen (HLA) molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPseq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome. Citation Format: Jian-Hua Luo, Silvia Liu, Bao-Guo Ren, Yan-Ping Yu. Long-read single-cell sequencing of liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB253.
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Conde, Daniel, Paolo M. Triozzi, Kelly M. Balmant, Andria L. Doty, Mariza Miranda, Anthony Boullosa, Henry W. Schmidt, Wendell J. Pereira, Christopher Dervinis, and Matias Kirst. "A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus." PLOS ONE 16, no. 5 (May 11, 2021): e0251149. http://dx.doi.org/10.1371/journal.pone.0251149.
Повний текст джерелаАнотація:
Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover key regulatory elements that determine cell fate during developmental programs. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell wall structure, Populus shoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.
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Pagani, Andrea, Dominik Duscher, Sally Kempa, Mojtaba Ghods, and Lukas Prantl. "Preliminary Single-Cell RNA-Sequencing Analysis Uncovers Adipocyte Heterogeneity in Lipedema." Cells 13, no. 12 (June 13, 2024): 1028. http://dx.doi.org/10.3390/cells13121028.
Повний текст джерелаАнотація:
Background: Despite its increasing incidence and prevalence throughout Western countries, lipedema continues to be a very enigmatic disease, often misunderstood or misdiagnosed by the medical community and with an intrinsic pathology that is difficult to trace. The nature of lipedemic tissue is one of hypertrophic adipocytes and poor tissue turnover. So far, there are no identified pathways responsible, and little is known about the cell populations of lipedemic fat. Methods: Adipose tissue samples were collected from affected areas of both lipedema and healthy participants. For single-cell RNA sequencing analysis, the samples were dissociated into single-cell suspensions using enzymatic digestion and then encapsulated into nanoliter-sized droplets containing barcoded beads. Within each droplet, cellular mRNA was converted into complementary DNA. Complementary DNA molecules were then amplified for downstream analysis. Results: The single-cell RNA-sequencing analysis revealed three distinct adipocyte populations at play in lipedema. These populations have unique gene signatures which can be characterized as a lipid generating adipocyte, a disease catalyst adipocyte, and a lipedemic adipocyte. Conclusions: The single-cell RNA sequencing of lipedemic tissue samples highlights a triad of distinct adipocyte subpopulations, each characterized by unique gene signatures and functional roles. The interplay between these adipocyte subtypes offers promising insights into the complex pathophysiology of lipedema.
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Asada, Ken, Ken Takasawa, Hidenori Machino, Satoshi Takahashi, Norio Shinkai, Amina Bolatkan, Kazuma Kobayashi, et al. "Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research." Biomedicines 9, no. 11 (October 21, 2021): 1513. http://dx.doi.org/10.3390/biomedicines9111513.
Повний текст джерелаАнотація:
In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; technologies that are centered on single-cell RNA sequencing (scRNA-seq) have been reported to analyze cancer constituent cells, identify cell groups responsible for therapeutic resistance, and analyze gene signatures of resistant cell groups. However, although single-cell analysis is a powerful tool, various issues have been reported, including batch effects and transcriptional noise due to gene expression variation and mRNA degradation. To overcome these issues, machine learning techniques are currently being introduced for single-cell analysis, and promising results are being reported. In addition, machine learning has also been used in various ways for single-cell analysis, such as single-cell assay of transposase accessible chromatin sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq) analysis, and multi-omics analysis; thus, it contributes to a deeper understanding of the characteristics of human diseases, especially cancer, and supports clinical applications. In this review, we present a comprehensive introduction to the implementation of machine learning techniques in medical research for single-cell analysis, and discuss their usefulness and future potential.
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Shi, Xiaobo, You Li, Yuchen Sun, Xu Zhao, Xuanzi Sun, Tuotuo Gong, Zhinan Liang, Yuan Ma, and Xiaozhi Zhang. "Genome-wide analysis of lncRNAs, miRNAs, and mRNAs forming a prognostic scoring system in esophageal squamous cell carcinoma." PeerJ 8 (February 10, 2020): e8368. http://dx.doi.org/10.7717/peerj.8368.
Повний текст джерелаАнотація:
Background Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal carcinoma. Protein coding genes and non-coding RNAs can be powerful prognostic factors in multiple cancers, including ESCC. However, there is currently no model that integrates multiple types of RNA expression signatures to predict clinical outcomes. Methods The sequencing data (RNA-sequencing and miRNA-sequencing) and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database, and Differential gene expression analysis, Cox regression analysis and Spearman correlation analysis were used to construct prognosis-related lncRNA-mRNA co-expression network and scoring system with multiple types of RNA. The potential molecular mechanisms of prognostic mRNAs were explored by functional enrichment analysis. Results A total of 62 prognostic lncRNAs, eight prognostic miRNAs and 66 prognostic mRNAs were identified in ESCC (P-value < 0.05) and a prognosis-related lncRNA-mRNA co-expression network was created. Five prognosis-related hub RNAs (CDCA2, MTBP, CENPE, PBK, AL033384.1) were identified. Biological process analysis revealed that mRNAs in prognosis-related co-expression RNA network were mainly enriched in cell cycle, mitotic cell cycle and nuclear division. Additionally, we constructed a prognostic scoring system for ESCC using ten signature RNAs (MLIP, TNFSF10, SIK2, LINC01068, LINC00601, TTTY14, AC084262.1, LINC01415, miR-5699-3p, miR-552-5p). Using this system, patients in the low-risk group had better long-term survival than those in the high-risk group (log-rank, P-value < 0.0001). The area under the ROC curve (AUCs) revealed that the accuracy of the prediction model was higher than the accuracy of single type of RNA prediction model. Conclusion In brief, we constructed a prognostic scoring system based on multiple types of RNA for ESCC that showed high predicting prognosis performance, and deeply understood the regulatory mechanism of prognosis-related lncRNA-mRNA co-expression network.
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Song, Hye-Won, Samatha Vadrevu, Punya Narayan, Gisele Baracho, Aaron Tyznik, Jody Martin, Katherine lazaruk, Margaret Nakamoto, and Stefanie Mortimer. "Immune phenotypic analysis using predesigned and lyophilized BD® AbSeq Immune Discovery Panel." Journal of Immunology 206, no. 1_Supplement (May 1, 2021): 27.08. http://dx.doi.org/10.4049/jimmunol.206.supp.27.08.
Повний текст джерелаАнотація:
Abstract High-throughput single cell RNA sequencing (scRNA-seq) has recently emerged as a powerful tool for profiling complex cell populations. While traditional scRNA-seq captures information at the transcript level, recent technology using DNA-barcoded antibodies enable multiomic analysis, examining protein alongside mRNA. Although this approach allows analyzing a large number of protein markers, the sequencing cost can escalate quickly for large panels, particularly ones with high antigen-density markers, and workflows can be long. Therefore, panels should be optimized to gain meaningful results efficiently and cost-effectively. Here, we introduce the BD® AbSeq Immune Discovery Panel (IDP), a lyophilized panel consisting of 30 antibodies against major human immune cell-types and immune response markers for analyzing multiple immune cell subsets. The BD® AbSeq IDP can be used to uncover phenotypic changes in cell subsets such as unique cell input differences or changes in the immune cell status. To test this capability, we used the IDP alongside a mRNA analysis using targeted mRNA panel and whole transcriptome assay to compare the immune phenotypes of cells from disease and in vitro stimulated samples at the single-cell level using the BD Rhapsody™ System. We propose that the BD® AbSeq IDP can be used to identify the cell types and molecular pathways impacted by the disease at the single cell level. For Research Use Only. Not for use in diagnostic or therapeutic procedures. BD, the BD Logo, and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2019 BD. All rights reserved.
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Ulrich, Peaches Rebecca, Louie Schoettle, Courtney Dubois, Kylee Jones, Neelam Chaudhary, Karen S. Anderson, and Joseph Blattman. "Intracellular pairing of multiple mRNA species at the single-cell level using DNA Origami." Journal of Immunology 202, no. 1_Supplement (May 1, 2019): 131.21. http://dx.doi.org/10.4049/jimmunol.202.supp.131.21.
Повний текст джерелаАнотація:
Abstract Current research has demonstrated the importance of identification of antigen-specific T cells for use in adoptive cell therapy to treat cancer. By identifying rare T cells, we may be able to determine highly effective reagents for tumor regression. A major problem in identifying TCR for clinical applications has been development of high-throughput methods for obtaining CDR3 sequence information from TCRαβ pairs from individual cells. To this end, we have developed novel DNA origami nanostructures with “bowtie”-barcoded capture probes to simultaneously capture human TCRαβ mRNA from single cells. Origami nanostructures are delivered into T cells via electroporation, and TCRα and β mRNA are co-captured onto integral nanostructure probes. Individual TCRαβ sequences are then reverse transcribed and appended to unique origami-specific bowtie oligonucleotide barcodes that can be matched in downstream next-generation sequencing. We have validated this approach using a Jurkat T cell line, expressing known TCRαβ sequences. Upon the synthesis of DNA origami with TCRα and β capture probes, Jurkat T cells were transfected with the origami scaffold, resulting in the capture and amplification of TCRαβ sequences. Validation using Sanger sequencing confirmed the capture of barcoded TCRα and TCRβ CDR3 sequences. Using a custom “bowtie” dual-barcoding system, we have developed an approach for single cell analysis of multiple mRNA species. Although our current focus is on the TCR repertoire, the “bowtie”-barcoded probes may be modified to capture sequence information from virtually any two genes of interest.
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Xie, Wenhui, Yilang Ke, Qinyi You, Jing Li, Lu Chen, Dang Li, Jun Fang, et al. "Single-Cell RNA Sequencing and Assay for Transposase-Accessible Chromatin Using Sequencing Reveals Cellular and Molecular Dynamics of Aortic Aging in Mice." Arteriosclerosis, Thrombosis, and Vascular Biology 42, no. 2 (February 2022): 156–71. http://dx.doi.org/10.1161/atvbaha.121.316883.
Повний текст джерелаАнотація:
Objective: The impact of vascular aging on cardiovascular diseases has been extensively studied; however, little is known regarding the cellular and molecular mechanisms underlying age-related vascular aging in aortic cellular subpopulations. Approach and Results: Transcriptomes and transposase-accessible chromatin profiles from the aortas of 4-, 26-, and 86-week-old C57/BL6J mice were analyzed using single-cell RNA sequencing and assay for transposase-accessible chromatin sequencing. By integrating the heterogeneous transcriptome and chromatin accessibility data, we identified cell-specific TF (transcription factor) regulatory networks and open chromatin states. We also determined that aortic aging affects cell interactions, inflammation, cell type composition, dysregulation of transcriptional control, and chromatin accessibility. Endothelial cells 1 have higher gene set activity related to cellular senescence and aging than do endothelial cells 2. Moreover, construction of senescence trajectories shows that endothelial cell 1 and fibroblast senescence is associated with distinct TF open chromatin states and an mRNA expression model. Conclusions: Our data provide a system-wide model for transcriptional and epigenetic regulation during aortic aging at single-cell resolution.
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Kerkelä, Erja, Jenni Lahtela, Antti Larjo, Ulla Impola, Laura Mäenpää, and Pirkko Mattila. "Exploring Transcriptomic Landscapes in Red Blood Cells, in Their Extracellular Vesicles and on A Single-Cell Level." International Journal of Molecular Sciences 23, no. 21 (October 25, 2022): 12897. http://dx.doi.org/10.3390/ijms232112897.
Повний текст джерелаАнотація:
Being enucleated, RBCs lack typical transcriptomes, but are known to contain small amounts of diverse long transcripts and microRNAs. However, the exact role and importance of these RNAs are lacking. Shedding of extracellular vesicles (EVs) from the plasma membrane constitutes an integral mechanism of RBC homeostasis, by which RBCs remove unnecessary cytoplasmic content and cell membrane. To study this further, we explored the transcriptomes of RBCs and extracellular vesicles (EVs) of RBCs using next-generation sequencing. Furthermore, we performed single-cell RNA sequencing on RBCs, which revealed that approximately 10% of the cells contained detectable levels of mRNA and cells formed three subpopulations based on their transcriptomes. A decrease in the mRNA quantity was observed across the populations. Qualitative changes included the differences in the globin transcripts and changes in the expression of ribosomal genes. A specific splice form of a long non-coding RNA, Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1), was the most enriched marker in one subpopulation of RBCs, co-expressing with ribosomal structural transcripts. MALAT1 expression was confirmed by qPCR in CD71-enriched reticulocytes, which were also characterized with imaging flow cytometry at the single cell level. Analysis of the RBC transcriptome shows enrichment of pathways and functional categories required for the maturation of reticulocytes and erythrocyte functions. The RBC transcriptome was detected in their EVs, making these transcripts available for intercellular communication in blood.
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Gorin, Gennady, and Lior Pachter. "Analysis of Length Biases in Single-Cell RNA Sequencing of Unspliced mRNA by Markov Modeling." Biophysical Journal 120, no. 3 (February 2021): 81a. http://dx.doi.org/10.1016/j.bpj.2020.11.706.
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Andersen, Anna Halling Folkmar, Mariane Høgsbjerg Schleimann, Miriam Rosas-Umbert, Rikke Olesen, Jesper Damsgaard Gunst, Michelle Krogsgaard, and Martin Tolstrup. "Single-cell TCR and mRNA sequencing of antigen-specific T cells reveal spatial trajectories from single time points with HLA and VDJ bias." Journal of Immunology 208, no. 1_Supplement (May 1, 2022): 169.01. http://dx.doi.org/10.4049/jimmunol.208.supp.169.01.
Повний текст джерелаАнотація:
Abstract Yellow fever (YF) vaccination induces massive CD8 expansion, comprising up to 10% of all circulating CD8 T cells. We hypothesize that HLA type and VDJ gene usage implicate the highly biased response towards certain immunodominant epitopes. PBMCs were collected from healthy human donors 3 weeks after vaccination with the yellow fever vaccine, Stamaril, and enriched for YF-CD8 T cells using HLA class I tetramers. We focused on the immunodominant epitopes NS4B and NS2A, and the less dominant epitope NS3. Cells were analyzed by single-cell T cell receptor (TCR) and mRNA sequencing, yielding detailed gene phenotypes for around 2000–3000 quality cells from each donor. Data was analyzed using SeqGeq, VDJ explorer, Seurat and Monocle2. From three donors, we performed in depth analyses on both TCR gene use bias across epitope specificity, and established pseudotime cell trajectories from a single sampling time point. We found that within the CD8 population from the same donor, VDJ usage was highly biased for the target antigen. Based on mRNA expression of a panel of 259 T-cell relevant genes, we performed unsupervised clustering, that shows cells with different epitope targets cluster interchangeably, indicating similar functional patterns. However, cells specific for the immunodominant epitopes had lower TCR clonal divergence between naïve-like and activated clusters, indicating a higher degree of clonal expansion compared to less immunodominant clones. Taken together, we show antigen-driven T cell responses are biased based on donor HLA-types, which could implicate development and success of T-cell driven immunotherapies. Supported by grants from Independent Research Fund Denmark (1029-00004B)
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Sugimoto, K., H. Toyoshima, R. Sakai, K. Miyagawa, K. Hagiwara, F. Ishikawa, F. Takaku, Y. Yazaki, and H. Hirai. "Frequent mutations in the p53 gene in human myeloid leukemia cell lines." Blood 79, no. 9 (May 1, 1992): 2378–83. http://dx.doi.org/10.1182/blood.v79.9.2378.2378.
Повний текст джерелаАнотація:
Abstract The p53 gene is currently considered to function as a tumor-suppressor gene in various human malignancies. In hematologic malignancies, alterations in the p53 gene have been shown in some human leukemias and lymphomas. Although mutations in the p53 gene are infrequent in acute myelogenous leukemia (AML) patients, we show in this report that alterations in the p53 gene are frequent in myeloid leukemia cell lines. We studied alterations of the p53 gene in nine human myeloid leukemia cell lines by reverse transcriptase-polymerase chain reaction (RT-PCR), single-strand conformation polymorphism (SSCP) analysis, and direct sequencing. Expression of the p53 gene was not detected at all by RT-PCR in two of the nine cell lines. In these two cell lines, Southern blot analysis showed gross rearrangements and deletions in both of the p53 alleles. Six of the nine cell lines were found to express only mutant p53 mRNA by RT-PCR/SSCP analysis and direct sequencing, and wild-type p53 mRNA was not detected. Two of the mutant p53 mRNAs were shown to be products of abnormal splicing events induced by intronic point mutations. Taken together, eight of nine human myeloid leukemia cell lines expressed no or an undetectable amount of wild-type p53 mRNA. Three of the eight cell lines were growth factor- dependent. Our results suggest that inactivation of the p53 gene may be a common feature in myeloid leukemia cell lines and may play an important role in the establishment of these cell lines.
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Sugimoto, K., H. Toyoshima, R. Sakai, K. Miyagawa, K. Hagiwara, F. Ishikawa, F. Takaku, Y. Yazaki, and H. Hirai. "Frequent mutations in the p53 gene in human myeloid leukemia cell lines." Blood 79, no. 9 (May 1, 1992): 2378–83. http://dx.doi.org/10.1182/blood.v79.9.2378.bloodjournal7992378.
Повний текст джерелаАнотація:
The p53 gene is currently considered to function as a tumor-suppressor gene in various human malignancies. In hematologic malignancies, alterations in the p53 gene have been shown in some human leukemias and lymphomas. Although mutations in the p53 gene are infrequent in acute myelogenous leukemia (AML) patients, we show in this report that alterations in the p53 gene are frequent in myeloid leukemia cell lines. We studied alterations of the p53 gene in nine human myeloid leukemia cell lines by reverse transcriptase-polymerase chain reaction (RT-PCR), single-strand conformation polymorphism (SSCP) analysis, and direct sequencing. Expression of the p53 gene was not detected at all by RT-PCR in two of the nine cell lines. In these two cell lines, Southern blot analysis showed gross rearrangements and deletions in both of the p53 alleles. Six of the nine cell lines were found to express only mutant p53 mRNA by RT-PCR/SSCP analysis and direct sequencing, and wild-type p53 mRNA was not detected. Two of the mutant p53 mRNAs were shown to be products of abnormal splicing events induced by intronic point mutations. Taken together, eight of nine human myeloid leukemia cell lines expressed no or an undetectable amount of wild-type p53 mRNA. Three of the eight cell lines were growth factor- dependent. Our results suggest that inactivation of the p53 gene may be a common feature in myeloid leukemia cell lines and may play an important role in the establishment of these cell lines.
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Feng, Wei, Andrew Przysinda, and Guang Li. "Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells." Journal of Visualized Experiments, no. 155 (January 7, 2020). http://dx.doi.org/10.3791/60647.
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Perez, Julio D., Susanne tom Dieck, Beatriz Alvarez-Castelao, Georgi Tushev, Ivy CW Chan, and Erin M. Schuman. "Subcellular sequencing of single neurons reveals the dendritic transcriptome of GABAergic interneurons." eLife 10 (January 6, 2021). http://dx.doi.org/10.7554/elife.63092.
Повний текст джерелаАнотація:
Although mRNAs are localized in the processes of excitatory neurons, it is still unclear whether interneurons also localize a large population of mRNAs. In addition, the variability in the localized mRNA population within and between cell-types is unknown. Here we describe the unbiased transcriptomic characterization of the subcellular compartments of hundreds of single neurons. We separately profiled the dendritic and somatic transcriptomes of individual rat hippocampal neurons and investigated mRNA abundances in the soma and dendrites of single glutamatergic and GABAergic neurons. We found that, like their excitatory counterparts, interneurons contain a rich repertoire of ~4000 mRNAs. We observed more cell type-specific features among somatic transcriptomes than their associated dendritic transcriptomes. Finally, using cell-type specific metabolic labelling of isolated neurites, we demonstrated that the processes of Glutamatergic and, notably, GABAergic neurons were capable of local translation, suggesting mRNA localization and local translation is a general property of neurons.
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Zhang, Junpeng, Lin Liu, Taosheng Xu, Wu Zhang, Chunwen Zhao, Sijing Li, Jiuyong Li, Nini Rao, and Thuc Duy Le. "Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data." BMC Bioinformatics 22, no. 1 (December 2021). http://dx.doi.org/10.1186/s12859-021-04498-6.
Повний текст джерелаАнотація:
Abstract Background Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation. Results In this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to combine single-cell miRNA-mRNA co-sequencing data and putative miRNA-mRNA binding information to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks for understanding miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. The comparison results indicate that CSmiR is effective in predicting cell-specific miRNA targets. Finally, through exploring cell–cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells and helps to understand cell–cell crosstalk. Conclusions To the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation.
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Kojima, Masato, Takanori Harada, Takahiro Fukazawa, Sho Kurihara, Isamu Saeki, Shinya Takahashi, and Eiso Hiyama. "Single-cell DNA and RNA sequencing of circulating tumor cells." Scientific Reports 11, no. 1 (November 24, 2021). http://dx.doi.org/10.1038/s41598-021-02165-7.
Повний текст джерелаАнотація:
AbstractSingle-cell sequencing of circulating tumor cells can precisely represent tumor heterogeneity and provide useful information for cancer treatment and research. After spiking TGW neuroblastoma cells into blood derived from healthy volunteer, the cells were isolated by fluorescence-activated cell sorting. DNA and mRNA were amplified by four different whole-genome amplifications (WGA) and three whole-transcriptome amplifications (WTA) methods, followed by single-cell DNA and RNA sequencing. Multiple displacement amplification (MDA)-based WGA methods showed higher amplification efficiency than other methods with a comparable depth of coverage as the bulk sample. The uniformity of coverage greatly differed among samples (12.5–89.2%), with some samples evaluated by the MDA-based WGA method using phi29 DNA polymerase and random primers showing a high (> 80%) uniformity of coverage. The MDA-based WTA method less effectively amplified mRNA and showed non-specific gene expression patterns. The PCR-based WTA using template switching with locked nucleic acid technology accurately amplified mRNA from a single cell. Taken together, our results present a more reliable and adaptable approach for CTC profiling at the single-cell level. Such molecular information on CTCs derived from clinical patients will promote cancer treatment and research.
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Probst, Victoria, Arman Simonyan, Felix Pacheco, Yuliu Guo, Finn Cilius Nielsen, and Frederik Otzen Bagger. "Benchmarking full-length transcript single cell mRNA sequencing protocols." BMC Genomics 23, no. 1 (December 29, 2022). http://dx.doi.org/10.1186/s12864-022-09014-5.
Повний текст джерелаАнотація:
Abstract Background Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. Results Here, we present a performance evaluation of four different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications taxing high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocols Genome & Transcriptome sequencing (G&T) and SMART-seq3 (SS3). G&T delivered the highest detection of genes per single cell. SS3 presented the highest gene detection per single cell at the lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between samples, but at the absolute highest price. NEB® delivered a lower detection of genes but remains an alternative to more expensive commercial kits. Conclusion For the tested kits we found that ease-of-use came at higher prices. Takara can be selected for its ease-of-use to analyse a few samples, but we recommend the cheaper G&T-seq or SS3 for laboratories where a substantial sample flow can be expected.
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Gorin, Gennady, and Lior Pachter. "Length Biases in Single-Cell RNA Sequencing of pre-mRNA." Biophysical Reports, December 2022, 100097. http://dx.doi.org/10.1016/j.bpr.2022.100097.
Повний текст джерела
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Sullivan, Delaney K., Kristján Eldjárn Hjörleifsson, Nikhila P. Swarna, Conrad Oakes, Guillaume Holley, Páll Melsted, and Lior Pachter. "Accurate quantification of nascent and mature RNAs from single-cell and single-nucleus RNA-seq." Nucleic Acids Research, December 6, 2024. https://doi.org/10.1093/nar/gkae1137.
Повний текст джерелаАнотація:
Abstract In single-cell and single-nucleus RNA sequencing (RNA-seq), the coexistence of nascent (unprocessed) and mature (processed) messenger RNA (mRNA) poses challenges in accurate read mapping and the interpretation of count matrices. The traditional transcriptome reference, defining the “region of interest” in bulk RNA-seq, restricts its focus to mature mRNA transcripts. This restriction leads to two problems: reads originating outside of the “region of interest” are prone to mismapping within this region, and additionally, such external reads cannot be matched to specific transcript targets. Expanding the “region of interest” to encompass both nascent and mature mRNA transcript targets provides a more comprehensive framework for RNA-seq analysis. Here, we introduce the concept of distinguishing flanking k-mers (DFKs) to improve mapping of sequencing reads. We have developed an algorithm to identify DFKs, which serve as a sophisticated “background filter”, enhancing the accuracy of mRNA quantification. This dual strategy of an expanded region of interest coupled with the use of DFKs enhances the precision in quantifying both mature and nascent mRNA molecules, as well as in delineating reads of ambiguous status.
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Trinh, Mi K., Clarissa N. Pacyna, Gerda Kildisiute, Christine Thevanesan, Alice Piapi, Kirsty Ambridge, Nathaniel D. Anderson, et al. "Precise identification of cancer cells from allelic imbalances in single cell transcriptomes." Communications Biology 5, no. 1 (September 7, 2022). http://dx.doi.org/10.1038/s42003-022-03808-9.
Повний текст джерелаАнотація:
AbstractA fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data.
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Russell, Alistair B., Cole Trapnell, and Jesse D. Bloom. "Extreme heterogeneity of influenza virus infection in single cells." eLife 7 (February 16, 2018). http://dx.doi.org/10.7554/elife.32303.
Повний текст джерелаАнотація:
Viral infection can dramatically alter a cell’s transcriptome. However, these changes have mostly been studied by bulk measurements on many cells. Here we use single-cell mRNA sequencing to examine the transcriptional consequences of influenza virus infection. We find extremely wide cell-to-cell variation in the productivity of viral transcription – viral transcripts comprise less than a percent of total mRNA in many infected cells, but a few cells derive over half their mRNA from virus. Some infected cells fail to express at least one viral gene, but this gene absence only partially explains variation in viral transcriptional load. Despite variation in viral load, the relative abundances of viral mRNAs are fairly consistent across infected cells. Activation of innate immune pathways is rare, but some cellular genes co-vary in abundance with the amount of viral mRNA. Overall, our results highlight the complexity of viral infection at the level of single cells.
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Kim, Heon Seok, Susan M. Grimes, Anna C. Hooker, Billy T. Lau, and Hanlee P. Ji. "Single-cell characterization of CRISPR-modified transcript isoforms with nanopore sequencing." Genome Biology 22, no. 1 (December 2021). http://dx.doi.org/10.1186/s13059-021-02554-1.
Повний текст джерелаАнотація:
AbstractWe developed a single-cell approach to detect CRISPR-modified mRNA transcript structures. This method assesses how genetic variants at splicing sites and splicing factors contribute to alternative mRNA isoforms. We determine how alternative splicing is regulated by editing target exon-intron segments or splicing factors by CRISPR-Cas9 and their consequences on transcriptome profile. Our method combines long-read sequencing to characterize the transcript structure and short-read sequencing to match the single-cell gene expression profiles and gRNA sequence and therefore provides targeted genomic edits and transcript isoform structure detection at single-cell resolution.
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Chamberlin, John T., Younghee Lee, Gabor Marth, and Aaron R. Quinlan. "Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments." Genome Research, February 14, 2024, gr.278253.123. http://dx.doi.org/10.1101/gr.278253.123.
Повний текст джерелаАнотація:
A mechanistic understanding of the biological and technical factors that impact transcript measurements is essential to designing and analyzing single-cell and single-nucleus RNA sequencing experiments. Nuclei contain the same pre-mRNA population as cells, but they contain a small subset of the mRNAs. Nonetheless, early studies argued that single-nucleus analysis yielded results comparable to cellular samples if pre-mRNA measurements were included. However, typical workflows do not distinguish between pre-mRNA and mRNA when estimating gene expression, and variation in their relative abundances across cell types has received limited attention. These gaps are especially important given that incorporating pre-mRNA has become commonplace for both assays, despite known gene length bias in pre-mRNA capture. Here, we reanalyze public datasets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell types, which mediates the degree of gene length bias and limits the generalizability of a recently-published normalization method intended to correct for this bias. As an alternative, we repurpose an existing post hoc gene length-based correction method from conventional RNA-seq gene set enrichment analysis. Finally, we show that inclusion of pre-mRNA in bioinformatic processing can impart a larger effect than assay choice itself, which is pivotal to the effective reuse of existing data. These analyses advance our understanding of the sources of variation in single-cell and single-nucleus RNA-seq experiments and provide useful guidance for future studies.