Expression console

Manufactured by Thermo Fisher Scientific

Sourced in United States, Canada

The Expression Console is a software tool designed for managing and analyzing gene expression data. It provides a user-friendly interface for organizing, visualizing, and interpreting data from various gene expression experiments. The software supports multiple file formats and allows users to perform statistical analyses, generate heat maps, and create custom reports.

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347 protocols using expression console

Transcriptional Changes During Limb Regeneration

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The proportional increase in body length (Day 7 body length –
post-amputation body length / post-amputation body length) was compared between
chemically treated and control embryos using Student’s t-test. For the
microarray experiment, several quality control methods were used to examine
expression values across the 65 GeneChips in the experiment. Box plots were
generated in Expression Console (Affymetrix, Santa Clara, CA) to examine the
consistency of expression across arrays, and principal components analysis and
Mahalanobis distances were calculated in JMP to examine array clustering in
multivariate space. One of the GeneChips (12 hr non-treated) was identified as
an outlier and removed from the experiment. All of the retained GeneChips were
normalized using Affymetrix Expression Console software to accomplish robust
multichip averaging (RMA) (Irizarry et al.,
2003). Student’s t-test was performed separately for each
time point to identify probe sets that yielded significantly different average
expression values as a function of treatment. These lists were further filtered
using a false discovery rate of α = 0.05 and by requiring a 1.5
fold difference between treatment means.

Ponomareva L.V., Athippozhy A., Thorson J.S, & Voss S.R. (2015). Using Ambystoma mexicanum (Mexican Axolotl) Embryos, Chemical Genetics, and Microarray Analysis to Identify Signaling Pathways Associated with Tissue Regeneration. Comparative biochemistry and physiology. Toxicology & pharmacology : CBP, 178, 128-135.

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Analyzing lncRNA and mRNA Expression Profiles

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According to the annotation profiles provided by the GPL570 [HG-U133 Plus 2] Affymetrix Human Genome U133 Plus 2.0 Array, expression information of lncRNA-associated probes was analyzed using ExpressionConsole (version 1.1; Affymetrix; Thermo Fisher Scientific, Inc.) to evaluate the gene expression levels. BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi) was used to annotate the probes matched to lncRNAs. Additionally, expression information of mRNA-associated probes was analyzed using ExpressionConsole based on the information provided by GPL96 [HG-U133A] Affymetrix Human Genome U133A Array. Subsequently, DEGs and DELs between Day 0, 8, 15 and 33 were screened using random variance model corrective analysis of variance in R 3.5.1 software (https://cran.r-project.org/). Thresholds of DEGs and DELs were set as follows: P≤0.001, false discovery rate (FDR) ≤0.01, and fold change ≥2. Numbers of screened DEGs and DELs were illustrated using Venn diagrams.

Li S., Bian H., Cao Y., Juan C., Cao Q., Zhou G, & Fang Y. (2018). Identification of novel lncRNAs involved in the pathogenesis of childhood acute lymphoblastic leukemia. Oncology Letters, 17(2), 2081-2090.

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Transcriptome Analysis of Frozen Cells

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RNA extraction (QIAGEN, Hilden, Germany) of snap frozen cells were performed as described^{50 (link)}. For quality control and quantification aliquots (1 µl) were analyzed with the RNA 6000 nano Kit on a Bioanalyzer 2100 (Agilent) and Nanodrop (Thermofisher Scientific). For transcriptome analysis, 150 ng RNA was processed as previously described^{50 (link)} and hybridized on Affymetrix Human Transcriptome Array 2.0 according to the manufacturer’s staining and scanning protocol. Data were analyzed using Expression console (Thermofisher Scientific, Darmstadt, Germany) and Transcriptome Analysis Console (TAC) software version 4.0 (Thermofisher Scientific, Darmstadt, Germany) (1.5-fold, p-value 0.05) as previously described^{51 (link)}. Full datasets are available under GSE136039 on https://www.ncbi.nlm.nih.gov/geo. Further bioinformatic analysis was performed using the knowledge-based Ingenuity Pathway Analysis (IPA) (release summer 2018 (QIAGEN, Hilden, Germany)) QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis ^{52 (link)}.

Barbosa D.M., Fahlbusch P., Herzfeld de Wiza D., Jacob S., Kettel U., Al-Hasani H., Krüger M., Ouwens D.M., Hartwig S., Lehr S., Kotzka J, & Knebel B. (2020). Rhein, a novel Histone Deacetylase (HDAC) inhibitor with antifibrotic potency in human myocardial fibrosis. Scientific Reports, 10, 4888.

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Microarray Analysis of Mouse RNA

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Aliquots (250 ng) of total RNA obtained from 4 animals per group at 16.5 wks were individually converted to cDNA and labeled with Clariom™ S Assay, mouse (Thermo Fisher Scientific, Inc., cat.# 902930) and GeneChip™WT PLUS Reagent Kit (Thermo Fisher Scientific, Inc., cat.# 902281) according to the manufacturer’s instructions. Hybridization, washing, and staining were performed using the Hybridization, Wash, and Stain Kit (Thermo Fisher Scientific, Inc., cat.# 900720), GeneChip™ Hybridization Oven 645 (Thermo Fisher Scientific, Inc.), and GeneChip™ Fluidics Station 450 (Thermo Fisher Scientific, Inc.), according to the manufacturer’s protocols. After washing, Array Strips were analyzed using GeneChip™ Scanner 3000 7G (Thermo Fisher Scientific, Inc.). Data were validated using Expression Console™ and Transcriptome Analysis Console™ Software (Thermo Fisher Scientific, Inc.). A cut-off point of ≤-1.3 or ≥1.3 of the linear fold change and P-values was used. We submitted our microarray data, which was approved under the accession number GSE18830 to the GEO repository.

Suzuki M., Kohmura-Kobayashi Y., Ueda M., Furuta-Isomura N., Matsumoto M., Oda T., Kawai K., Itoh T., Matsuya M., Narumi M., Tamura N., Uchida T., Mochizuki K, & Itoh H. (2022). Comparative Analysis of Gene Expression Profiles in the Adipose Tissue of Obese Adult Mice With Rapid Infantile Growth After Undernourishment In Utero. Frontiers in Endocrinology, 13, 818064.

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Transcriptome Analysis of Affymetrix Clariom D

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The data for the transcriptome analysis using an Affymetrix Clariom D Human array (Thermo Fisher Scientific) have been deposited in NCBI's Gene Expression Omnibus (Achuta et al., 2018 ) and are accessible through accession number GEO: GSE103965). For the gene-level analysis, the raw expression data were normalized using the Expression Console program (v.1.3) (https://www.thermofisher.com/). The signal space transformation robust multi-array average method was used to normalize the data (Li and Wong, 2001 (link)). To identify differentially expressed genes, an empirical Bayes moderated t test was applied using the “limma” package (v.3.34.9) (Smyth, 2005 ). To address the problem of multiple testing, the p values were adjusted (Benjamini and Hochberg, 1995 ). A gene was considered differentially expressed if the adjusted p value was less than 0.05.
Alternative splicing analysis was performed using the transcriptome analysis console (TAC) (v.4.0) (https://www.thermofisher.com/). TAC was used with the default setting and only exon-level false discovery rate p values <0.05 were considered differentially expressed. The EventPointer (Romero et al., 2016 (link)) algorithm was used to detect splicing events and to test for significant differential splicing events.

Danesi C., Achuta V.S., Corcoran P., Peteri U.K., Turconi G., Matsui N., Albayrak I., Rezov V., Isaksson A, & Castrén M.L. (2018). Increased Calcium Influx through L-type Calcium Channels in Human and Mouse Neural Progenitors Lacking Fragile X Mental Retardation Protein. Stem Cell Reports, 11(6), 1449-1461.

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Macrophage Transcriptome Analysis in SNI

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Macrophages (F4/80⁺ CD11b⁺ 2–5000 cells) were sorted from a pool of ipsilateral L4/L5 DRG of SNI WT and miR-21 cKO using a FACS Aria II sorter (BD Bioscience). Total RNA was prepared from the cell lysate. Each condition was represented by independently collected biological triplicates. Labeled cell extracts were processed for microarray analysis using the WT Pico Amplification kit (Thermofisher) and hybridized to Affymetrix Mouse 430V2 Arrays. MAS5 pre-processed data were generated in Expression Console (Thermofisher) and analyzed for differential gene expression using Transcript Analysis Console (Thermofisher) with a P value cutoff < 0.05 and two-fold change filter applied. Statistically significant differentially expressed gene list associated with each condition were further annotated and interrogated using MetaCore software (Reuters).

Simeoli R., Montague K., Jones H.R., Castaldi L., Chambers D., Kelleher J.H., Vacca V., Pitcher T., Grist J., Al-Ahdal H., Wong L.F., Perretti M., Lai J., Mouritzen P., Heppenstall P, & Malcangio M. (2017). Exosomal cargo including microRNA regulates sensory neuron to macrophage communication after nerve trauma. Nature Communications, 8, 1778.

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Microarray Data Analysis Pipeline

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Expression console (v.1.4.1.46, Thermo Fisher Scientific Inc.) was used for quality control and to obtain annotated normalized RMA gene-level data (standard settings including median polish and sketch-quantile normalisation). Statistical analyses were performed by utilizing the statistical programming environment R (R Development Core Team [59 ]). Genewise testing for differential expression was done employing the (limma) t-test (p < 0.05) and cut-offs for ratio (>1.3-fold) and expression levels (average > 16 in at least one experimental group per comparison) were applied. PCA was done in R and the upstream regulator analysis was generated through the use of QIAGEN's Ingenuity Pathway Analysis (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity).

Ballester-López C., Conlon T.M., Ertüz Z., Greiffo F.R., Irmler M., Verleden S.E., Beckers J., Fernandez I.E., Eickelberg O, & Yildirim A.Ö. (2019). The Notch ligand DNER regulates macrophage IFNγ release in chronic obstructive pulmonary disease. EBioMedicine, 43, 562-575.

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Transcriptomic Analysis of Denatonium Effects in AML

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TAS2R expression was analyzed in 61 AML, 49 from a published dataset (32 (link)) and 12 new cases. As validation set, we used also 183 AML samples downloaded from The Cancer Genome Atlas (TCGA) (https://gdc.cancer.gov/about-data/publications/laml_2012) (33 (link)). GEP after DEN treatment was performed in 5 newly diagnosed AML samples and THP-1 and OCI-AML3 cell lines. Three independent replicates of each condition were hybridized to Human Clariom S Arrays (Thermo Fisher Scientific) according to the manufacturer's recommendations. Data quality control, normalization (signal space transformation robust multiple-array average), and supervised analysis were carried out by Expression Console and Transcriptome Analysis Console software, respectively (Thermo Fisher Scientific). For AML cells, data were normalized on vehicle-treated cells before comparison. Genes with a 1.5 fold difference and p ≤ 0.05 were considered for enrichment analyses. Downstream analyses were performed as reported in (32 (link), 34 (link)), and with Thomson Reuter's MetaCore software suite (Clarivate Analytics, Philadelphia, PA, USA). Gene expression data of denatonium-treated cells will be publicly available on the GEO database under the accession number GSE149548.

Salvestrini V., Ciciarello M., Pensato V., Simonetti G., Laginestra M.A., Bruno S., Pazzaglia M., De Marchi E., Forte D., Orecchioni S., Martinelli G., Bertolini F., Méndez-Ferrer S., Adinolfi E., Di Virgilio F., Cavo M, & Curti A. (2020). Denatonium as a Bitter Taste Receptor Agonist Modifies Transcriptomic Profile and Functions of Acute Myeloid Leukemia Cells. Frontiers in Oncology, 10, 1225.

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Gene Expression Profiling of Lung Cancer Subtypes

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Isolated RNA from the cells and patient tissue was further processed with the GeneChip™ 3' IVT PLUS Reagent kit (Thermo Fisher Scientific) and the GeneChip™ Human Genome U133 Plus 2.0 Array (Thermo Fisher Scientific) according to the manufacturer's instructions. For gene expression profiling of the patient tissues, we selected samples with the highest or lowest PAEP expression (40 ADCs and 30 SQCCs), which was determined by qPCR analyses in our previous study (20 (link)). The raw data were normalized using the software Expression Console™ (Thermo Fisher Scientific) [Algorithm: robust multi-array average (RMA)] and analysed by Transcriptome Analysis Console™ 3.0 (Thermo Fisher Scientific). For further evaluation with the software Ingenuity pathway analysis (IPA; IPA-42012434; Qiagen) (upstream regulator analysis), only genes with an expression fold-change <−1.5 or >1.5 were considered. A detailed description of the IPA analysis is available on the manufacturer's homepage (https://www.qiagenbioinformatics.com/products/features/). The microarray data, which were part of this study, are available as described below.

Weber R., Meister M., Muley T., Thomas M., Sültmann H., Warth A., Winter H., Herth F.J, & Schneider M.A. (2018). Pathways regulating the expression of the immunomodulatory protein glycodelin in non-small cell lung cancer. International Journal of Oncology, 54(2), 515-526.

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Microarray Data Normalization Protocol

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Gene expression levels in the form of fluorescence intensity values stored in CEL files were background corrected and normalized on Affymetrix’s Expression Console software (build 1.4.1.46, Thermo Fisher Scientific, Waltham, Massachusetts, USA) using the SST-RMA algorithm. Probe sets with expression levels twofold above the mean expression levels of the antigenomic control probes, which are designed to be incompatible with any human genome sequence, were considered as expressed.

Schulze K.V., Swaminathan S., Howell S., Jajoo A., Lie N.C., Brown O., Sadat R., Hall N., Zhao L., Marshall K., May T., Reid M.E., Taylor-Bryan C., Wang X., Belmont J.W., Guan Y., Manary M.J., Trehan I., McKenzie C.A, & Hanchard N.A. (2019). Edematous severe acute malnutrition is characterized by hypomethylation of DNA. Nature Communications, 10, 5791.

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