scholarly journals Single-cell transcriptomics reveals diverse and complex gene expression alterations in human trisomy 18

2019 ◽  
Author(s):  
Jing Wang ◽  
Zixi Chen ◽  
Fei He ◽  
Trevor Lee ◽  
Wenjie Cai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Extra Chromosome ◽  
Trisomy 18 ◽  
Autosomal Trisomy ◽  
Single Cell Rna Sequencing ◽  
Cell Groups ◽  
Significant Gene ◽  
Critical Regions ◽  
Gene Expression Alterations

Trisomy 18, commonly known as Edward’s syndrome, is the second most common autosomal trisomy among live born neonates. Multiple tissues including cardiac, abdominal, and nervous systems are affected by an extra chromosome 18. To delineate the complexity of anomalies of trisomy 18, we analyzed amniotic fluid cells from two normal and three trisomy 18 samples using single-cell transcriptomics. We identified six cell groups, which function in major tissue development such as kidney, vasculature, and smooth muscle, and display significant alterations in gene expression detected by single-cell RNA-sequencing. Moreover, we demonstrated significant gene expression changes in previously proposed trisomy 18 critical regions, and identified three new regions such as 18p11.32, 18q11, 18q21.32, which are likely associated with trisomy 18 phenotypes. Our results indicate complexity of trisomy 18 at the gene expression level and reveal genetic reasoning of diverse phenotypes in trisomy 18 patients.

scholarly journals The order and logic of CD4 versus CD8 lineage choice and differentiation in mouse thymus

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mohammad M. Karimi ◽  
Ya Guo ◽  
Xiaokai Cui ◽  
Husayn A. Pallikonda ◽  
Veronika Horková ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Single Cell ◽  
Signal Strength ◽  
Gene Activity ◽  
Cytotoxic T Cell ◽  
Individual Selection ◽  
Cell Lineages ◽  
Single Cell Rna Sequencing ◽  
Tcr Signals

AbstractCD4 and CD8 mark helper and cytotoxic T cell lineages, respectively, and serve as coreceptors for MHC-restricted TCR recognition. How coreceptor expression is matched with TCR specificity is central to understanding CD4/CD8 lineage choice, but visualising coreceptor gene activity in individual selection intermediates has been technically challenging. It therefore remains unclear whether the sequence of coreceptor gene expression in selection intermediates follows a stereotypic pattern, or is responsive to signaling. Here we use single cell RNA sequencing (scRNA-seq) to classify mouse thymocyte selection intermediates by coreceptor gene expression. In the unperturbed thymus, Cd4+Cd8a- selection intermediates appear before Cd4-Cd8a+ selection intermediates, but the timing of these subsets is flexible according to the strength of TCR signals. Our data show that selection intermediates discriminate MHC class prior to the loss of coreceptor expression and suggest a model where signal strength informs the timing of coreceptor gene activity and ultimately CD4/CD8 lineage choice.

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

scholarly journals Single-cell RNA sequencing of the mammalian pineal gland identifies two pinealocyte subtypes and cell type-specific daily patterns of gene expression

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205883 ◽  
Author(s):  
Joseph C. Mays ◽  
Michael C. Kelly ◽  
Steven L. Coon ◽  
Lynne Holtzclaw ◽  
Martin F. Rath ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pineal Gland ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Cell Type Specific ◽  
Mammalian Pineal Gland ◽  
Daily Patterns

scholarly journals Single-Cell RNA-Sequencing Identifies Activation of TP53 and STAT1 Pathways in Human T Lymphocyte Subpopulations in Response to Ex Vivo Radiation Exposure

2019 ◽  
Vol 20 (9) ◽  
pp. 2316 ◽  
Author(s):  
Maria Moreno-Villanueva ◽  
Ye Zhang ◽  
Alan Feiveson ◽  
Brandon Mistretta ◽  
Yinghong Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cluster Analysis ◽  
Dna Damage ◽  
Radiation Exposure ◽  
Single Cell ◽  
T Lymphocyte ◽  
Ex Vivo ◽  
Lymphocyte Subpopulations ◽  
Single Cell Rna Sequencing ◽  
Sequencing Technique

Detrimental health consequences from exposure to space radiation are a major concern for long-duration human exploration missions to the Moon or Mars. Cellular responses to radiation are expected to be heterogeneous for space radiation exposure, where only high-energy protons and other particles traverse a fraction of the cells. Therefore, assessing DNA damage and DNA damage response in individual cells is crucial in understanding the mechanisms by which cells respond to different particle types and energies in space. In this project, we identified a cell-specific signature for radiation response by using single-cell transcriptomics of human lymphocyte subpopulations. We investigated gene expression in individual human T lymphocytes 3 h after ex vivo exposure to 2-Gy gamma rays while using the single-cell sequencing technique (10X Genomics). In the process, RNA was isolated from ~700 irradiated and ~700 non-irradiated control cells, and then sequenced with ~50 k reads/cell. RNA in each of the cells was distinctively barcoded prior to extraction to allow for quantification for individual cells. Principal component and clustering analysis of the unique molecular identifier (UMI) counts classified the cells into three groups or sub-types, which correspond to CD4+, naïve, and CD8+/NK cells. Gene expression changes after radiation exposure were evaluated using negative binomial regression. On average, BBC3, PCNA, and other TP53 related genes that are known to respond to radiation in human T cells showed increased activation. While most of the TP53 responsive genes were upregulated in all groups of cells, the expressions of IRF1, STAT1, and BATF were only upregulated in the CD4+ and naïve groups, but were unchanged in the CD8+/NK group, which suggests that the interferon-gamma pathway does not respond to radiation in CD8+/NK cells. Thus, single-cell RNA sequencing technique was useful for simultaneously identifying the expression of a set of genes in individual cells and T lymphocyte subpopulation after gamma radiation exposure. The degree of dependence of UMI counts between pairs of upregulated genes was also evaluated to construct a similarity matrix for cluster analysis. The cluster analysis identified a group of TP53-responsive genes and a group of genes that are involved in the interferon gamma pathway, which demonstrate the potential of this method for identifying previously unknown groups of genes with similar expression patterns.

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

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

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

scholarly journals Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue

Circulation ◽  
2020 ◽  
Vol 142 (14) ◽  
pp. 1374-1388
Author(s):  
Yanming Li ◽  
Pingping Ren ◽  
Ashley Dawson ◽  
Hernan G. Vasquez ◽  
Waleed Ageedi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Aortic Wall ◽  
Genome Wide Association ◽  
Aortic Tissue ◽  
Sequencing Data ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Differential Gene

Background: Ascending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues. Methods: We performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies. Results: We identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene( ERG ) exerts an important role in maintaining normal aortic wall function. Conclusions: Our study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression.

Abstract A10: Using single-cell RNA sequencing to assess the impact of pancreatic oncogenic Kras on macrophage gene expression in vitro

2019 ◽  
Author(s):  
Katelyn Donahue ◽  
Yaqing Zhang ◽  
Veerin Sirihorachai ◽  
Stephanie The ◽  
Arvind Rao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Rna Sequencing ◽  
The Impact
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