scholarly journals Scalable full-transcript coverage single cell RNA sequencing with Smart-seq3xpress

2021 ◽  
Author(s):  
Michael Hagemann-Jensen ◽  
Christoph Ziegenhain ◽  
Rickard Sandberg
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Mononuclear Cells ◽  
Human Peripheral Blood ◽  
Cell Types ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells ◽  
Additional Protein

Plate-based single-cell RNA-sequencing methods with full-transcript coverage typically excel at sensitivity but are more resource and time-consuming. Here, we miniaturized and streamlined the Smart-seq3 protocol for drastically reduced cost and increased throughput. Applying Smart-seq3xpress to 16,349 human peripheral blood mononuclear cells revealed a highly granular atlas complete with both common and rare cell types whose identification previously relied on additional protein measurements or the integration with a reference atlas.

scholarly journals No detectable alloreactive transcriptional responses during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

2020 ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
Mars Stone ◽  
Zev J. Gartner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Transcriptional Responses ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

ABSTRACTSingle-cell RNA sequencing (scRNA-seq) provides high-dimensional measurement of transcript counts in individual cells. However, high assay costs limit the study of large numbers of samples. Sample multiplexing technologies such as antibody hashing and MULTI-seq use sample-specific sequence tags to enable individual samples (e.g., different patients) to be sequenced in a pooled format before downstream computational demultiplexing. Critically, no study to date has evaluated whether the mixing of samples from different donors in this manner results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self immune antigens). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures,. Here, we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from a single donor with and without pooling with PBMCs isolated from other donors with different blood types. We find that there was no evidence of alloreactivity in the multiplexed samples following three distinct multiplexing workflows (antibody hashing, MULTI-seq, and in silico genotyping using souporcell). Moreover, we identified biases amongst antibody hashing sample classification results in this particular experimental system, as well as gene expression signatures linked to PBMC preparation method (e.g., Ficoll-Paque density gradient centrifugation with or without apheresis using Trima filtration).

scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as multiple silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also running time and robustness of a dozen methods. Results: We found that Seurat outperformed other methods, although performance seems to be dependent on many factors, including the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single-cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as three silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also robustness of a dozen methods. Results: We found that some methods, including Seurat and Cell Ranger, outperform other methods, although performance seems to be dependent on the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this, we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

scholarly journals Single-cell RNA sequencing of peripheral blood mononuclear cells from acute Kawasaki disease patients

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhen Wang ◽  
Lijian Xie ◽  
Guohui Ding ◽  
Sirui Song ◽  
Liqin Chen ◽  
...  
Keyword(s):  
T Cells ◽  
Kawasaki Disease ◽  
Immune Responses ◽  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Healthy Controls ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

AbstractKawasaki disease (KD) is the most common cause of acquired heart disease in children in developed countries. Although functional and phenotypic changes of immune cells have been reported, a global understanding of immune responses underlying acute KD is unclear. Here, using single-cell RNA sequencing, we profile peripheral blood mononuclear cells from seven patients with acute KD before and after intravenous immunoglobulin therapy and from three age-matched healthy controls. The most differentially expressed genes are identified in monocytes, with high expression of pro-inflammatory mediators, immunoglobulin receptors and low expression of MHC class II genes in acute KD. Single-cell RNA sequencing and flow cytometry analyses, of cells from an additional 16 KD patients, show that although the percentage of total B cells is substantially decreased after therapy, the percentage of plasma cells among the B cells is significantly increased. The percentage of CD8+ T cells is decreased in acute KD, notably effector memory CD8+ T cells compared with healthy controls. Oligoclonal expansions of both B cell receptors and T cell receptors are observed after therapy. We identify biological processes potentially underlying the changes of each cell type. The single-cell landscape of both innate and adaptive immune responses provides insights into pathogenesis and therapy of KD.

scholarly journals The Characteristics of Peripheral Blood Mononuclear Cells in Takayasu Arteritis by Single Cell RNA Sequencing

2021 ◽  
Author(s):  
Qing Gao ◽  
Jinge Yu ◽  
Zuoguan Chen ◽  
Yongpeng Diao ◽  
Yuqing Miao ◽  
...  
Keyword(s):  
B Cells ◽  
Nk Cells ◽  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Takayasu Arteritis ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Objectives Takayasu Arteritis (TA) is a rare non-specific vascular inflammation and has deleterious effects on patients’ health. Recent studies have advanced in TA diagnosis and treatment, but the research on the immune cell atlas of peripheral blood is still less. For this purpose, we performed single-cell RNA sequencing (scRNA-seq) to analyze the inflammatory cell types and cell markers in TA patients’ Peripheral blood mononuclear cells (PBMCs). Methods 4 TA patients and 4 health controls were enrolled in our study from 2019.10 to 2020.5. Their PBMCs samples were collected and performed scRNA-seq. We used Seurat package (v.3.2.2) in R studio (v.3.5.3) for data analysis, and 2 tests were applied for comparing the composition ratio of each cell type by SPSS 20.0. Results CD14+ monocytes, GZMB+ NKT cells, CD56dim CD16+ NK cells, and naive B cells were significantly increased in TA patients as compared to healthy controls and the expression of THBS1, CD163, AREG, IFITM1, TXNIP, and IGHGs was elevated in the peripheral blood of TA patients. Conclusion Except CD4+ T cells, monocytes, NK cells, NKT cells, B cells also play an important role in TA pathogenesis. The elevated markers have different functions in different types of PBMCs, and they can be used as potential diagnostic markers for TA diagnosis.

scholarly journals Single-cell RNA sequencing unveils the shared and the distinct cytotoxic hallmarks of human TCRVδ1 and TCRVδ2 γδ T lymphocytes

2019 ◽  
pp. 201818488 ◽  
Author(s):  
Gabriele Pizzolato ◽  
Hannah Kaminski ◽  
Marie Tosolini ◽  
Don-Marc Franchini ◽  
Fréderic Pont ◽  
...  
Keyword(s):  
T Lymphocytes ◽  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Human Peripheral Blood ◽  
Effector Memory ◽  
In Vitro Proliferation ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing

γδ T lymphocytes represent ∼1% of human peripheral blood mononuclear cells and even more cells in most tissues of vertebrates. Although they have important anticancer functions, most current single-cell RNA sequencing (scRNA-seq) studies do not identify γδ T lymphocytes because their transcriptomes at the single-cell level are unknown. Here we show that high-resolution clustering of large scRNA-seq datasets and a combination of gene signatures allow the specific detection of human γδ T lymphocytes and identification of their T cell receptor (TCR)Vδ1 and TCRVδ2 subsets in large datasets from complex cell mixtures. In t-distributed stochastic neighbor embedding plots from blood and tumor samples, the few γδ T lymphocytes appear collectively embedded between cytotoxic CD8 T and NK cells. Their TCRVδ1 and TCRVδ2 subsets form close yet distinct subclusters, respectively neighboring NK and CD8 T cells because of expression of shared and distinct cytotoxic maturation genes. Similar pseudotime maturation trajectories of TCRVδ1 and TCRVδ2 γδ T lymphocytes were discovered, unveiling in both subsets an unattended pool of terminally differentiated effector memory cells with preserved proliferative capacity, a finding confirmed by in vitro proliferation assays. Overall, the single-cell transcriptomes of thousands of individual γδ T lymphocytes from different CMV+ and CMV− donors reflect cytotoxic maturation stages driven by the immunological history of donors. This landmark study establishes the rationale for identification, subtyping, and deep characterization of human γδ T lymphocytes in further scRNA-seq studies of complex tissues in physiological and disease conditions.

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