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Bulk RNAseq of Sort-purified IV- Primary (1M) or Quaternary (4M) Tcirc (IV- CD69-/CD103-) or Trm (IV- CD69+/CD103+) Memory P14 cells isolated from Spleen or Mediastinal Lymph Nodes

ABSTRACT: Purpose: The goals of this study are to compare the phenotypic, transcriptomic, trafficking and functional atttibutes of Influenza-experienced circulating or resident memory phenotype cells from the spleen or lung-draining mediastinal lymph nodes. Results: Following read alignment, gene expression profiles were computed using featureCounts. Filtering and visualization of differentially expressed genes with a log2fold change >1.5<-1.5 and a p value of less than 0.05 were identified using Partek GS software and for some figures values from Partek were normalized and displayed using GraphPad Prism. Gene set enrichment and functional assignment were performed in DAVID bioinformatics resources and software from the Broad Institute.

ORGANISM(S): Mus musculus

PROVIDER: GSE172279 | GEO | 2021/06/28

REPOSITORIES: GEO

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Bulk RNAseq of Sort-purified IV- Primary (1M) or Quaternary (4M) Tcirc (IV- CD69-/CD103-) or Trm (IV- CD69+/CD103+) Memory P14 cells isolated from Spleen or Mediastinal Lymph Nodes

Project description:Bulk RNAseq of Sort-purified IV- Primary (1M) or Quaternary (4M) Tcirc (IV- CD69-/CD103-) or Trm (IV- CD69+/CD103+) Memory P14 cells isolated from Spleen or Mediastinal Lymph Nodes

| PRJNA722744 | ENA

Reactive glia promote development of CD103+ CD69+ CD8+ T-cells through programmed cell death-ligand 1 (PD-L1).

Project description:INTRODUCTION:Previous work from our laboratory has demonstrated in vivo persistence of CD103+ CD69+ brain resident memory CD8+ T-cells (bTRM ) following viral infection, and that the PD-1: PD-L1 pathway promotes development of these TRM cells within the brain. Although glial cells express low basal levels of PD-L1, its expression is upregulated upon IFN-?-treatment, and they have been shown to modulate antiviral T-cell effector responses through the PD-1: PD-L1 pathway. METHODS:We performed flow cytometric analysis of cells from co-cultures of mixed glia and CD8+ T-cells obtained from wild type mice to investigate the role of glial cells in the development of bTRM . RESULTS:In this study, we show that interactions between reactive glia and anti-CD3 Ab-stimulated CD8+ T-cells promote development of CD103+ CD69+ CD8+ T-cells through engagement of the PD-1: PD-L1 pathway. These studies used co-cultures of primary murine glial cells obtained from WT animals along with CD8+ T-cells obtained from either WT or PD-1 KO mice. We found that ?CD3 Ab-stimulated CD8+ T-cells from WT animals increased expression of CD103 and CD69 when co-cultured with primary murine glial cells. In contrast, significantly reduced expression of CD103 and CD69 was observed using CD8+ T-cells from PD-1 KO mice. We also observed that reactive glia promoted high levels of CD127, a marker of memory precursor effector cells (MPEC), on CD69+ CD8+ T-cells, which promotes development of TRM cells. Interestingly, results obtained using T-cells from PD-1 KO animals showed significantly reduced expression of CD127 on CD69+ CD8+ cells. Additionally, blocking of glial PD-L1 resulted in decreased expression of CD103, along with reduced CD127 on CD69+ CD8+ T-cells. CONCLUSIONS:Taken together, these results demonstrate a role for activated glia in promoting development of bTRM through the PD-1: PD-L1 pathway.

| S-EPMC5946148 | biostudies-literature

Prolactin-induced protein (PIP) regulates proliferation of luminal A type breast cancer cells in a hormone-independent manner

Project description:RNA was extracted from cells using Aurum Total RNA kit from Bio-Rad Laboratories, Inc., Hercules, CA following the manufacturer’s recommendations. Gene expression profiling was performed using the BeadChip HumanHT-12 v4 Expression kit from Illumina®, which contains 47,231 gene-probes (Illumina® Inc., San Diego, CA). The raw signal intensities were imported and analyzed using the GenomeStudio® data software. After background subtraction and normalization, the signal intensity values were exported to the Partek® genomics expression analysis suite using “Partek's Report Plug-in” option in the GenomeStudio® software. Differentially expressed genes in the dox- versus vehicle-treated samples were identified using the “gene expression” workflow in the Partek® software.

2012-10-29 | GSE41894 | GEO

Expression profile of Normal Breast Tissue in Brazilian women

Project description:Control samples used to performed gene expression comparison with breast cancer tissues. mRNA samples from normal breast tissue were amplified, labeled, and hybridized to the Affymetrix GeneChip Human Exon 1.0 ST array. After normalization and analysis of the microarray data using Partek® software (http://www.partek.com).

2021-11-03 | GSE180835 | GEO

Expression data from the human whole blood samples

Project description:Microarray expression profiling approach was used to identify age-related mRNA markers. In this dataset, we include the expression data obtained from whole venous blood samples collected from ERF (Erasmus Rucphen Family study) donors of different age. Two age groups - young (~25 y.o.) and old (~ 60 y.o.) were analyzed using Partek GS software.

2015-12-22 | GSE27458 | GEO

Expression profile of brazilian gastric adenocarcinoma cell lines

Project description:The ACP02 cell line was stablished from a primary diffuse adenocarcinoma (T3N2M0) and AGP01 cell was established from ascitic fluid cells from intestinal gastric adenocarcinoma (T3N2M1). mRNA samples from cell lines were amplified, labeled, and hybridized to the Affymetrix GeneChip Human Exon 1.0 ST array. The chip array data analysis was performed with Partek® software (http://www.partek.com).

2020-11-18 | GSE161689 | GEO

microRNA expression profile of human bone marrow-derived mesenchymal stem cells

Project description:MicroRNA expression profiling was performed in human BMSCs at 0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 7 days. RNA quantity and quality was assessed spectrophotometrically with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) with Agilent RNA 6000 Nano Kit for total RNA. The latest version of Affymetrix platform for miRNA expression analysis (Genechip miRNA 2.0 array) based on mirBase version 12 (http://www.mirbase.org/) was used to obtain miRNA profiles. Normalization and statistical analysis were performed with Partek Genomic Suite 6.6 software by means of ANOVA test. Fold-change (FC) and p-values were applied to generate miRNA differentially expressed lists.

2015-09-30 | E-MTAB-2977 | biostudies-arrayexpress

Expression profile of Breast Cancer tumors in Brazilian women

Project description:On the basis of prognostic information provided by the PAM50 predictor, we evaluated how samples grouped relative to the other breast tumor subtypes. mRNA samples from 24 patients were amplified, labeled, and hybridized to the Affymetrix GeneChip Human Exon 1.0 ST array. After normalization and analysis of the microarray data using Partek® software (http://www.partek.com), we clustered all samples using the PAM50 predictor.

2014-05-30 | GSE58102 | GEO

Expression data from mouse skin scar after wounding

Project description:Using a TCF reporter mouse which contain a LacZ gene downstream of a c-fos minimal promoter and three consensus TCF-binding motifs, we wounded skin and harvested the scar tissue one week post wounding. Healing tissue sorted to group of cells : β-Gal+ cells (R) expression data with β-Gal- cells (L) , an analysis of gene expression was performed using Partek Genotyping Suite and Ingenuity Systems Software.

2011-07-26 | GSE30913 | GEO

Bovine blood gamma/delta T cell stimulation study

Project description:Blood gamma/delta T cells were purfiied from holstein calves less than six months old. Blood from 4 individual calves were pooled and gamma/delta T cells were purified by immunomagnetic separation, rested in RPMI medium for 12h, and underwent ConA & hIL-2 stimulation. Total RNAs were extracted by using Trizol reagents. 15 ug of total RNA was used for cDNA synthesis and microarray hybridization. Table 1: regulated genes These genes were identified, in GeneSpring software, via filtering of genes with relative expression ratio of 1.5 and over or 0.667 or below, equivalent to up- and down-regulation by fold change 1.5 or more, in both experiments. Table 2: down-regulated genes These genes were identified, in GeneSpring software, via filtering of genes with relative expression ratio of 0.667 or below, equivalent to down-regulation by fold change 1.5 or more, in both experiments. The avergae fold change was then converted to negative value. Gene annotation was performed by using GeneSpring's "Build Simplified Ontology" constructor. Table 3: up-regulated genes These genes were identified, in GeneSpring software, via filtering of genes with relative expression ratio of 1.5 or over, equivalent to up-regulation by fold change 1.5 or more, in both samples. Gene annotation was performed by using GeneSpring's "Build Simplified Ontology" constructor. Keywords: other

2004-10-28 | GSE1870 | GEO

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