Journal: Frontiers in Cellular Neuroscience

Article Title: Cell-type expression and activation by light of neuropsins in the developing and mature Xenopus retina

doi: 10.3389/fncel.2023.1266945

Figure Lengend Snippet: scRNA-seq data from the adult zebrafish . (A) UMAP plot featuring annotated retinal cell types . (B) Quantification of cells which express neuropsin mRNA organized by cell type detected by scRNA-seq.

Article Snippet: Publicly available single cell RNA sequencing (scRNA-seq) whole eye datasets for the adult zebrafish ( Danio rerio ), chicken (P10) ( Gallus gallus ) and mouse (P60) ( Mus musculus ) were downloaded from GitHub at https://github.com/jiewwwang/Single-cell-retinal-regeneration ( ).

Techniques:

Journal: The Journal of Infectious Diseases

Article Title: Measles Virus Infects and Programs MAIT Cells for Apoptosis

doi: 10.1093/infdis/jiaa407

Figure Lengend Snippet: MAIT cells express the highest levels of SLAMF1/CD150 among PBMC subsets. A, Publicly available scRNA-Seq data from 11 769 PBMCs were analyzed. The 9432 cells that passed quality control filters are visualized on a t-SNE projection (left panel) demonstrating clusters corresponding to CD14+ monocytes (n = 2992), CD16+ monocytes (n = 328), cDCs (n = 74), pDCs (n = 68), NK cells (n = 544), B cells (n = 1419), CD4+ T cells (n = 2643), CD8+ T cells (n = 720), MAIT cells (n = 592), and platelets (n = 52). Each dot represents a single cell. The expression of SLAMF1 across indicated clusters, quantified as normalized and scaled count data, is shown in a violin plot (right panel), in which dots represent single cells and widths denote cell densities. B and C, MAIT cells and other peripheral blood T cell subsets were examined for CD150 expression. MAIT and iNKT cells were identified by MR1 tetramer staining (PubMed IDs 24101382 and 24695216) and CD1d tetramer staining (PubMed IDs 10839805 and 10974039), respectively. Open and filled histograms correspond to the staining of PBMCs with anti-CD150 and isotype control, respectively, after gating on CD3+MR1 tetramer+ MAIT cells (B). The frequencies of CD150+ cells and the gMFI of CD150 staining (C) in indicated T cell subsets are summarized using Box-and-Whisker plots, with each symbol representing an individual donor. *, *** and **** denote differences with P < .05, P < .001, and P < .0001, respectively, using matched one-way ANOVA with Dunnett post-hoc analysis. D, PBMCs (n = 4) were left untreated or stimulated with rhIL-12 plus rhIL-18. The frequencies of MAIT cells expressing CD150, CD69, or CD46 were determined 24 hours later by flow cytometry. ** denotes a difference with P < .05 by paired Student t test. Abbreviations: 5-OP-RU, 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil; APC, allophycocyanin; cDC, classic dendritic cell; FITC, fluorescein isothiocyanate; gMFI, geometric mean fluorescence intensity; iNKT, invariant natural killer T cell; MAIT, mucosa-associated invariant T cell; MR1, MHC-related protein 1; NK cell, natural killer cell; NS, not significant; PBMC, peripheral blood mononuclear cell; pDC, plasmacytoid pre-dendritic cell; PE, phycoerythrin; rhIL, recombinant human interleukin; scRNA-Seq, single-cell RNA sequencing; TCM, central memory T cell; TEM, effector memory T cell; TN, naive T cell; t-SNE, t-distributed stochastic neighbor embedding.

Article Snippet: Transcriptomic Analysis of Peripheral Blood Mononuclear Cells The pbmc_10k_v3 dataset, consisting of single-cell RNA sequencing (scRNA-Seq) data from 11 769 peripheral blood mononuclear cells (PBMCs), was created by 10x Genomics ( https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/pbmc_10k_v3 ).

Techniques: Control, Expressing, Staining, Whisker Assay, Flow Cytometry, Fluorescence, Recombinant, RNA Sequencing

Journal: bioRxiv

Article Title: Immune characterization and profiles of SARS-CoV-2 infected patients reveals potential host therapeutic targets and SARS-CoV-2 oncogenesis mechanism

doi: 10.1101/2021.02.17.431721

Figure Lengend Snippet: Publicly available datasets from the NCBI Gene Expression Omnibus (GEO) database included in analysis. Datasets were identified from the queries “single cell COVID19” and “COVID19 SARS CoV 2” in GEO DataSets.

Article Snippet: GSE154567 , GPL24676 , Examined immune response using 10x genomics to measure single-cell RNA sequence (scRNA-seq) of blood buffy coat from COVID-19 patients , Blood buffy coat , 17 , 12 , 6 , (6) Convalescent (5) Moderate (6) Severe.

Techniques: Gene Expression, Infection, Sequencing, Control

Journal: Scientific Reports

Article Title: The RNA-binding protein CPEB1 marks healthy adult β cells in mice but is dispensable for β cell identity and function

doi: 10.1038/s41598-025-32403-1

Figure Lengend Snippet: Cpeb1 transcripts are expressed mainly in healthy β cells of murine pancreas and Cpeb1 expression is reduced during β cell development and diabetes in mice. ( A ) scRNA-seq data of the whole pancreas from Tabula Muris reveals predominant transcript expression of Cpeb1 in β cells, with sparse expression in other endocrine cells. ( B ) Percentage of Cpeb1 expressing cells and mean expression levels of Cpeb1 in the Tabula Muris scRNA-seq data. ( C ) Bulk RNA-seq of sorted β cells published in Nimkulrat et al. unveils a gradual increase of Cpeb1 expression from embryonic (E18.5) to neonate (P1, P7, and P10) and healthy adult β cells. ( D ) Cpeb1 transcript expression from Nimkulrat et al. dataset is reduced in both types of diabetes with a more significant reduction in NOD (type-1 diabetic mouse model) than BTBR ob / ob (type-2 diabetic mouse model). ( E ) Comparison between different Cpeb1 paralogs in Nimkulrat et al. dataset indicates that Cpeb1 is the dominant Cpeb paralog expressed in the β cells. ( F ) Comparison of Cpeb1 expression in male and female β cells in Nimkulrat et al. dataset shows higher expression in female β cells than in male β cells.

Article Snippet: To begin interrogating the role of CPEB1 in β cells, we first examined its expression in the islets of Langerhans using the Tabula Muris single cell RNA sequencing (scRNA-seq) database .

Techniques: Expressing, RNA Sequencing, Comparison

Journal: Bioinformatics

Article Title: CeLLTra: aligning cell names with gene expression via a pathway-informed transformer

doi: 10.1093/bioinformatics/btaf655

Figure Lengend Snippet: The framework of CeLLTra during pretraining and inference stages. (a) The pretraining stage of the proposed contrastive cell-name-gene-expression learning framework for aligning cell name with gene expression patterns. (b) Inference stage of CeLLTra to predict cell type for a given single-cell gene expression profile. OOD detection is consequently performed on the predicted probability of seen types.

Article Snippet: Single-cell RNA sequencing (scRNA-Seq) technology enables the exploration of gene expression patterns at the individual cell level ( Tabula Muris Consortium et al. 2018 , Tabula Sapiens Consortium et al. 2022 , Yao et al. 2023 , Gabitto et al. 2024 ).

Techniques: Gene Expression, Single Cell

Journal: EMBO Reports

Article Title: TMPRSS11B promotes an acidified microenvironment and immune suppression in squamous lung cancer

doi: 10.1038/s44319-025-00631-1

Figure Lengend Snippet: ( A ) RNA sequencing analysis of tumors from various mouse models of lung cancer. The y-axis represents the normalized counts for Tmprss11b . One-way ANOVA with Dunnett’s multiple comparisons test was used for the statistical analysis (RPR2 mice n = 5; RPM mice n = 15; SNL mice n = 4; LP mice n = 6; SL mice n = 9; KP mice n = 8, biological replicates), **** P < 0.0001 (RPR2, RPM, KP), * P = 0.0133 (LP). Plot represents mean ± SD. ( B ) Schematic representation of Ad-Cre mediated tumor induction in SNL mice. Figure created in BioRender. ( C ) Representative MRI images of the mice in ( B ), 3- & 4-months post infection. Red outlines denote tumors (Biological replicates n > 3). ( D ) Representative H&E images of SNL mouse lung, 7 months post infection with Ad-Cre showing distinct regions of LUSC and mucinous LUAD (Biological replicates n > 3). Scale bar, 100 μm. ( E ) H&E image of SNL mouse lung (11 months post infection with Ad-Cre) and RNAscope of Tmprss11b on a serial section. Left, red outline denotes squamous tumors based on H&E staining. Right, yellow outline denotes regions with Tmprss11b expression (red) corresponding to the regions of squamous tumors. The staining was repeated three times with serial sections (technical replicates) and with lung sections from different mice ( n = 4, biological replicates). Scale bar, 2 mm. ( F ) Zoom-in of ( E ) showing Tmprss11b expression by RNAScope in squamous tumors (top panel) and normal lung (bottom panel). Scale bar, 200 μm. ( G ) Representative H&E image with annotations and RNAscope analysis of Tmprss11b (red) and Sox2 (green) in SNL lung sections. Scale bar, 400 μm. .

Article Snippet: We obtained reference single-cell RNA sequencing (scRNA-seq) data from The Tabla Muris Consortium ( Nature 2018) (Schaum et al, ) and spatial transcriptomics (ST) data from relevant datasets.

Techniques: RNA Sequencing, Infection, RNAscope, Staining, Expressing

Journal: EMBO Reports

Article Title: TMPRSS11B promotes an acidified microenvironment and immune suppression in squamous lung cancer

doi: 10.1038/s44319-025-00631-1

Figure Lengend Snippet: ( A ) Top downregulated Keratin genes from differential gene expression analysis of control shRNA versus Tmprss11b shRNA bulk RNA sequencing from the KLN205 syngeneic experiment in Fig. . The log2FC change depicts the reduction in expression of the indicated genes in the Tmprss11b knockdown tumors compared to the control. ( B ) Top Keratin genes from the differential gene expression (DEG) analysis of the Tmprss11b -high versus low in LUSC spatial data from SNL lung tumors. ( C ) Top keratin genes from the differential gene expression (DEG) analysis of the Tmprss11b -high LUSC versus LUAD spatial data from SNL lung tumors. ( D ) Top Keratin genes from the differential gene expression (DEG) analysis of TMPRSS11B -high versus low LUSC human tumors from TCGA. ( E ) Venn diagram depicting overlapping Keratin genes from the gene lists in ( A – D ).

Article Snippet: We obtained reference single-cell RNA sequencing (scRNA-seq) data from The Tabla Muris Consortium ( Nature 2018) (Schaum et al, ) and spatial transcriptomics (ST) data from relevant datasets.

Techniques: Gene Expression, Control, shRNA, RNA Sequencing, Expressing, Knockdown