Journal: Frontiers in Immunology

Article Title: Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

doi: 10.3389/fimmu.2021.694355

Figure Lengend Snippet: Gene Signature Definition and Generation icSARS Gene Panels. (A) Schematic definition of a gene signature. Differences in gene expression between two groups, such as SARS and mock infected lung cells, are measured by Welch’s two-sample T−test score. Gene signatures are ranked lists of genes from high (red) to low (blue) differential mRNA expression between groups. (B) Generation of icSARS gene panels for use in this study. To identify differentially expressed genes associated with icSARS infection in human airway epithelial cell cultures, query gene sets containing either the 500 most over- or under-expressed genes from positive or negative tails of the gene signature generated from the Gene Expression Omnibus (GEO) accession number GSE47960 mRNA expression dataset. The positive and negative tail query sets were compared individually to the gene signature generated from the GEO GSE47961 dataset, which was used as reference for Gene Set Enrichment Analysis (GSEA). From this GSEA computed two enrichment plots, one for each query set, and their associated normalized enrichment score (NES) and p-value which represent the extent of enrichment between query set and reference signature. GSEA also identified leading-edge genes, which are genes that contribute most to achieving maximum enrichment. Two gene panels were defined from leading-edge genes identified in each query set. These gene panels were used in this study for three purposes: 1) identification of gene expression changes associated with icSARS infection in human airway epithelial cell cultures, 2) verification of identified findings in independent datasets, and 3) comparison to other gene signatures representing changes in gene expression associated with other SARS infections.

Article Snippet: This work used the javaGSEA Desktop Application release 3.0 version of GSEA available from Broad Institute to perform gene T−ranking for signature formation and GSEA for gene identification, verification, and comparison.

Techniques: Gene Expression, Infection, Expressing, Generated, Comparison

Journal: Frontiers in Immunology

Article Title: Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

doi: 10.3389/fimmu.2021.694355

Figure Lengend Snippet: Verification of icSARS Gene Panels in Independent Datasets. (A) Gene Set Enrichment Analysis (GSEA) calculated enrichment, as determined by normalized enrichment score (NES), between the positive icSARS gene panel and the GSE47962-derived icSARSvsmock gene signature. (B) GSEA between the positive icSARS gene panel and GSE37827-derived icSARSvsmock gene signature. (C) GSEA between the positive icSARS gene panel and GSE48142-derived icSARSvsmock gene signature. (D) GSEA between the positive icSARS gene panel and GSE33267-derived icSARSvsmock gene signature. (E) GSEA between the negative icSARS panel and the GSE47962-derived icSARSvsmock signature. (F) GSEA between the negative icSARS panel and the GSE37827-derived icSARSvsmock signature. (G) GSEA between the negative icSARS panel and the GSE48142-derived icSARSvsmock signature. (H) GSEA between the negative icSARS panel and the GSE33267-derived icSARSvsmock signature. (I) Distribution plot of NES from 1000 randomly generated gene panels (individual queries) compared to the GSE47962-derived icSARSvsmock signature. (J) Distribution plot of NES from 1000 randomly generated gene panels compared to the GSE37827-derived icSARSvsmock signature. (K) Distribution plot of NES from 1000 randomly generated gene panels compared to the GSE48142-derived icSARSvsmock signature. (L) Distribution plot of NES from 1000 randomly generated gene panels compared to the GSE33267-derived icSARSvsmock signature.

Article Snippet: This work used the javaGSEA Desktop Application release 3.0 version of GSEA available from Broad Institute to perform gene T−ranking for signature formation and GSEA for gene identification, verification, and comparison.

Techniques: Derivative Assay, Generated

Journal: Frontiers in Immunology

Article Title: Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

doi: 10.3389/fimmu.2021.694355

Figure Lengend Snippet: Positive icSARS Panel Enrichment in icSARS Infected Mouse Model Revealed Genes Associated with icSARS Infection. (A) Gene Set Enrichment Analysis (GSEA) calculated enrichment, as determined by normalized enrichment score (NES), between the positive icSARS gene panel and the GSE50000-derived icSARSvsmock gene signature. (B) GSEA between the negative icSARS panel and the GSE50000-derived icSARSvsmock signature. (C) Distribution plot of NES from 1000 randomly generated gene panels (individual queries) compared to the GSE50000-derived icSARSvsmock signature (reference). (D) Venn diagram of the inclusion and overlap of positive icSARS panel genes in identified leading-edges and dataset platforms across icSARS-CoV human and mouse gene signatures. (E) Heat map of T−scores for the 20 positive icSARS panel leading-edge genes identified in (D) .

Article Snippet: This work used the javaGSEA Desktop Application release 3.0 version of GSEA available from Broad Institute to perform gene T−ranking for signature formation and GSEA for gene identification, verification, and comparison.

Techniques: Infection, Derivative Assay, Generated

Journal: Frontiers in Immunology

Article Title: Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

doi: 10.3389/fimmu.2021.694355

Figure Lengend Snippet: icSARS Panel Enrichment Detected Differential Gene Expression Similarities Across SARS Strains with Varying Virulen. (A) Heat map of Gene Set Enrichment Analysis (GSEA) calculated normalized enrichment scores (NES) of the positive and negative icSARS panels across SARS-CoV strains with varying levels of virulence in both human lung cultures and mouse lung samples. (B) Box and whisker plots of NES from 1000 randomly generated gene panels containing 233 genes (individual queries) compared to gene signatures (individual references) used in (A) . (C) Box and whisker plots of NES from 1000 randomly generated gene panels containing 114 genes (individual queries) compared to gene signatures (individual references) used in (A) .

Article Snippet: This work used the javaGSEA Desktop Application release 3.0 version of GSEA available from Broad Institute to perform gene T−ranking for signature formation and GSEA for gene identification, verification, and comparison.

Techniques: Gene Expression, Whisker Assay, Generated

Journal: Frontiers in Immunology

Article Title: Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

doi: 10.3389/fimmu.2021.694355

Figure Lengend Snippet: Five Over-Expressed Genes Identified in SARS-CoV Meta-analysis Found in Meta-analysis of MERS-CoV and SARS-CoV2 Signatures. (A) Heat map of Gene Set Enrichment Analysis calculated normalized enrichment scores for positive and negative icSARS panels across gene signatures derived from MERS-CoV and SARS-CoV2 infections in human or mouse lung cultures. (B) Box and whisker plots of normalized enrichment scores from 1000 randomly generated gene panels containing 233 genes (individual queries) compared to MERS-CoV and SARS-CoV2 gene signatures (individual references). (C) Box and whisker plots of normalized enrichment scores from 1000 randomly generated gene panels containing 114 genes (individual queries) compared to MERS-CoV and SARS-CoV2 gene signatures (individual references). (D) Venn diagram of the inclusion and overlap of positive icSARS panel genes in identified leading-edges and dataset platforms across MERS-CoV human and mouse gene signatures. (E) Venn diagram of the inclusion and overlap of shared positive icSARS panel genes in identified in SARS-CoV ( Figure 6 ), MERS-CoV (from D), and SARS-CoV2 gene signatures. (F) Heat map of T−scores for the five positive icSARS panel leading-edge genes identified in (E) .

Article Snippet: This work used the javaGSEA Desktop Application release 3.0 version of GSEA available from Broad Institute to perform gene T−ranking for signature formation and GSEA for gene identification, verification, and comparison.

Techniques: Derivative Assay, Whisker Assay, Generated

Journal: bioRxiv

Article Title: SARS-CoV-2 Airway Infection Results in Time-dependent Sensory Abnormalities in a Hamster Model

doi: 10.1101/2022.08.19.504551

Figure Lengend Snippet: A) Mechanical thresholds of mock, IAV, and SARS-CoV-2 animals at 28dpi (n=6 per group; **p<0.01, ****p<0.0001 for one-way ANOVA Tukey’s m.c.). B) Volcano plot for 31dpi SARS-CoV-2 tDRG RNA-seq (n=3 per group). Red=p-adj.<0.1, log2FC>0. Blue=p-adj.<0.1, log2FC>0. Green=p-nom.<0.05. C) IPA top 10 canonical pathways (−log10(p-value)>1.3) associated with 31dpi SARS-CoV-2 tDRG DEGs (p-nom.<0.05). D) enrichr DisGENET gateway top 10 diseases associated with 31 dpi SARS-CoV-2 tDRG DEGs (p-nom.<0.05). E) Log 2 (FC) of select neuronal and inflammatory genes from 31dpi RNA-seq (p-adj.<0.1). F) Positively and negatively enriched cell subtypes associated with 31dpi SARS-CoV-2 tDRG DEGs (GSEA NES>|1.5|; DEG p-adj.<0.1). G) IPA top 15 upstream regulators between 31dpi SARS-CoV-2 tDRG, Striatum, and Thalamus (DEG p-nom.<0.05).

Article Snippet: Gene set enrichment analyses were conducted using the GSEA Java application for Mac (v 4.1.0) (MSigDB; Broad Institute, UC San Diego).

Techniques: RNA Sequencing