bulk rna sequencing  (Azenta)

Journal: FASEB BioAdvances

Article Title: A TLR8 Variant Identified From Whole Exome Sequencing as a Sepsis‐Prone Mutation

doi: 10.1096/fba.2026-00049

Figure Lengend Snippet: Single‐cell RNA‐seq analysis of PBMCs in sepsis patients and healthy donors. (a) Schematic of the experimental design for single‐cell RNA sequencing of PBMCs. (b) UMAP visualization of all immune cell types within PBMCs. (c) UMAP plot showing monocyte subclusters across study conditions (severe sepsis, mild sepsis, and healthy donors). (d) Dot plot of canonical marker genes defining the three monocyte subtypes. (e) Dot plot showing TLR8 expression across monocyte subtypes. (f) Dot plot showing TLR8 expression across the three study conditions. (g) Violin plot illustrating type I interferon signaling scores across monocyte subtypes. One‐way ANOVA with Bonferroni post hoc analysis was used. **** p < 0.0001. (h) Table summarizing the clinical demographics of patients with the TLR8 rs3764880 polymorphism.

Article Snippet: TLR8 knockout cells were generated using CRISPR‐Cas9 targeting the sg_1 guide RNA (Figure ), followed by bulk RNA sequencing after ssRNA stimulation with ssRNA40/LyoVec, a known TLR8 agonist [ ], that has been shown to be a weak TLR7 and strong TLR8 agonist when tested using cell lines expressing either human or mouse TLR7 or TLR8 ( https://www.invivogen.com/ssrna40‐lv ).

Techniques: Single Cell, RNA Sequencing, Marker, Expressing

Journal: FASEB BioAdvances

Article Title: A TLR8 Variant Identified From Whole Exome Sequencing as a Sepsis‐Prone Mutation

doi: 10.1096/fba.2026-00049

Figure Lengend Snippet: Bulk RNA‐seq analysis of ssRNA‐stimulated WT and TLR8‐knockout THP‐1 monocytes. (a) Volcano plot of differentially expressed genes (DEGs) in ssRNA‐stimulated THP‐1 monocytes compared with unstimulated controls. (b) Volcano plot of DEGs in ssRNA‐stimulated TLR8‐knockout THP‐1 monocytes relative to stimulated wild‐type controls. (c) Gene Ontology enrichment analysis of upregulated genes in ssRNA‐stimulated THP‐1 monocytes. (d) Gene Ontology enrichment analysis of downregulated genes in ssRNA‐stimulated THP‐1 monocytes. (e) Table of interferon‐stimulated genes (ISGs) in ssRNA‐stimulated TLR8‐knockout THP‐1 monocytes relative to stimulated wild‐type controls.

Article Snippet: TLR8 knockout cells were generated using CRISPR‐Cas9 targeting the sg_1 guide RNA (Figure ), followed by bulk RNA sequencing after ssRNA stimulation with ssRNA40/LyoVec, a known TLR8 agonist [ ], that has been shown to be a weak TLR7 and strong TLR8 agonist when tested using cell lines expressing either human or mouse TLR7 or TLR8 ( https://www.invivogen.com/ssrna40‐lv ).

Techniques: RNA Sequencing, Knock-Out

Journal: Regenerative Therapy

Article Title: Sex as a biological variable in human dental pulp stem cells: An exploratory epigenomic and transcriptomic comparison

doi: 10.1016/j.reth.2026.101117

Figure Lengend Snippet: Bulk RNA-seq of human DPSCs from male and female donors. (A) Principal component analysis of rlog-normalized counts for the top 500 most variable genes with concentration eclipses showing within-group dispersion. Each point represents one donor. (B) Pairwise sample–sample correlation matrix between male (M) and female (F) DPSCs. Colors show Pearson correlation coefficients. (C) Unsupervised hierarchical clustering heatmap of all expressed genes using Euclidean distance and complete linkage. (D) Summary of differentially expressed genes (DEGs) in male DPSCs compared to female DPSCs. Outer circles show totals at adjusted p value < 0.05, and inner circles show the subset with |log 2 FC| > 1. (E) MA plot showing sex-biased gene expression in DPSCs. Statistically significant DEGs (adjusted p < 0.05) are marked in green, blue, and red for autosomal, X-linked, and Y-linked genes, respectively. (F) Volcano plot of RNA-seq data with represented genes labelled.

Article Snippet: Bulk RNA sequencing (RNA-seq) was performed by Novogene Ltd. (Cambridge, UK).

Techniques: RNA Sequencing, Concentration Assay, Dispersion, Gene Expression

Journal: Comprehensive Physiology

Article Title: Exploring the Lung–Liver Axis in Pulmonary Arterial Hypertension

doi: 10.1002/cph4.70171

Figure Lengend Snippet: Differences in gene expression from bulk RNA sequencing of pulmonary artery endothelial cell biopsies from PAH participants in the High‐ versus Low‐MELD clusters were examined using three modeling approaches. (A) The number and proportion of genes generated by three independent models (linear discriminant analysis (LDA) with principal component analysis (PCA), LDA with weighted gene co‐expression analysis (WGCNA), and a random forest (RF) model) and their intersections was reviewed and the intersection of LDA with PCA and WGCNA was used for all subsequent analysis. (B) Pathways analysis demonstrates enrichment for pathways related to apelin signaling, YAP/TAZ, as well as immunity and inflammation.

Article Snippet: PAECs were cultured from RHC balloon tips, expanded to passage 3 or 4 and submitted for library preparation and bulk RNA sequencing (Azenta, Cambridge, MA).

Techniques: Gene Expression, RNA Sequencing, Generated, Expressing

Journal: Comprehensive Physiology

Article Title: Exploring the Lung–Liver Axis in Pulmonary Arterial Hypertension

doi: 10.1002/cph4.70171

Figure Lengend Snippet: Bulk RNA sequencing of MCT (A) and SuHx (B) male rat livers compared to controls demonstrates increased gene expression in pathways related to inflammation and TGB beta signaling and decreased expression in pathways related to cellular metabolism. (C) A regulatory network built from differentially expressed genes in both MCT and SuHx rat livers demonstrates activation of pathways related to activation and recruitment of leukocytes.

Article Snippet: PAECs were cultured from RHC balloon tips, expanded to passage 3 or 4 and submitted for library preparation and bulk RNA sequencing (Azenta, Cambridge, MA).

Techniques: RNA Sequencing, Gene Expression, Expressing, Activation Assay

Journal: Comprehensive Physiology

Article Title: Exploring the Lung–Liver Axis in Pulmonary Arterial Hypertension

doi: 10.1002/cph4.70171

Figure Lengend Snippet: Differential gene expression in SuHx and MCT rat lung endothelial cells from a publicly available single‐cell RNA sequencing dataset was compared to pulmonary artery endothelial cell (PAEC) transcriptomes from High‐MELD participants. (A) Venn diagram demonstrating 775 genes overlapping between human High‐MELD PAECs and rat lung endothelial cells across both models. (B) GO pathway enrichment of the 775 overlapping genes demonstrated significant enrichment for pathways related to cell survival, proliferation, and cancer biology, including EGR1, ECM1 , and MIF . SuHx = Sugen‐Hypoxia. MCT, monocrotaline; MELD, model for end state liver disease.

Article Snippet: PAECs were cultured from RHC balloon tips, expanded to passage 3 or 4 and submitted for library preparation and bulk RNA sequencing (Azenta, Cambridge, MA).

Techniques: Gene Expression, Single Cell, RNA Sequencing

Journal: JID Innovations

Article Title: The human Flower isoform hFWE4 facilitates cornification in cutaneous squamous cell carcinoma

doi: 10.1016/j.xjidi.2026.100468

Figure Lengend Snippet: FWE KO dysregulates cornification and lamellar body–related gene expression in cSCC xenografts. ( a ) Volcano plot representing differential expression analysis of bulk RNA sequencing of hFWE WT (n = 12) and KO (n = 11) SCC-13 xenografts. Genes implicated in lamellar body function or cornification are annotated. ( b ) GO:BP and GO:CC analysis on differentially downregulated genes in hFWE- KO SCC-13 xenografts. ( c ) Representative immunofluorescence for KLK5 in hFWE WT and KO SCC-13 xenografts (bar = 500 μm and 50 μm [inset]). ( d ) Quantification of percentage tumor area KLK5 positive (mean ± SEM) in hFWE WT and KO SCC-13 xenografts (n = 6, 2-tailed unpaired t -test, ∗∗ P < .01). cSCC, cutaneous squamous cell carcinoma; GO:BP, gene ontology biological process; GO:CC; gene ontology cellular component; KO, knockout; WT, wild-type.

Article Snippet: Bulk RNA-sequencing data are available at the National Center for Biotechnology Information Gene Expression Omnibus under the accession number GSE314399 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE314399 ).

Techniques: Gene Expression, Quantitative Proteomics, RNA Sequencing, Immunofluorescence, Knock-Out