Genespring gx 10

Manufactured by Agilent Technologies

Sourced in United States

GeneSpring GX 10 is a software application for the analysis and visualization of gene expression data. It provides tools for data normalization, statistical analysis, and pathway visualization.

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49 protocols using genespring gx 10

Robust Gene Expression Analysis

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Gene expression was analyzed using GeneSpring GX 10.0 software (Agilent Technologies, Palo Alto, CA). Array data was normalized using the Robust Multiarray Analysis (RMA) algorithm (23 (link)). Probesets with an intensity value in the lowest 20th percentile among all the intensity values were excluded. The remaining probesets, with intensity values between the 20th and 100th percentile, were used for downstream statistical analysis. Significance analysis was conducted using one-way analysis of variance (ANOVA) using the multiple correction testing method of Benjamini and Hochberg (24 ) with a p value cut-off of <0.01.

King T., Kocharunchitt C., Gobius K., Bowman J.P, & Ross T. (2016). Physiological Response of Escherichia coli O157:H7 Sakai to Dynamic Changes in Temperature and Water Activity as Experienced during Carcass Chilling. Molecular & Cellular Proteomics : MCP, 15(11), 3331-3347.

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Assessing 5-aza-dC-induced Gene Expression

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To assess restoration of expression, cells from the HuH6 and HepG2 HB lines were treated with 1.0 μM 5‐aza‐dC (Sigma, St. Louis, MO, USA) for 72 h, replacing the drug and medium every 24 h. Total RNA was then extracted using an RNeasy kit (Qiagen), and sample amplification and labeling were done using a Low RNA Input Fluorescent Linear Amplification kit (Agilent Technologies, Santa Clara, CA, USA), both according to the manufacturer's instructions. Samples labeled with Cy3 were hybridized and processed on a 4x44K Whole Human Genome Oligo Microarray. Scanning was done with an Agilent G2565BA microarray scanner using the settings recommended by Agilent Technologies. All raw data were normalized and analyzed using GeneSpring GX 10.0 (Agilent Technologies). We screened for genes whose expression was increased more than twofold by 5‐aza‐dC treatment in HuH6 or HepG2 cells.

Honda S., Minato M., Suzuki H., Fujiyoshi M., Miyagi H., Haruta M., Kaneko Y., Hatanaka K.C., Hiyama E., Kamijo T., Okada T, & Taketomi A. (2016). Clinical prognostic value of DNA methylation in hepatoblastoma: Four novel tumor suppressor candidates. Cancer Science, 107(6), 812-819.

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Differential Gene Expression Analysis

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Gene expression was analyzed using GeneSpring GX 10.0 software (Agilent Technologies, Palo Alto, CA). Array data was normalized using the Robust Multi-Array Analysis (RMA) algorithm [17] (link). Probesets with an intensity value in the lowest 20th percentile among all the intensity values were excluded. The remaining probesets, with intensity values between the 20th and 100th percentile, were used for downstream statistical analysis. Significance analysis was conducted using one way analysis of variance (ANOVA) using the multiple correction testing method of Benjamini and Hochberg [18] with a P-value cut-off of <0.01. Genes were considered to be differentially expressed if the fold change was >2.

Kocharunchitt C., King T., Gobius K., Bowman J.P, & Ross T. (2014). Global Genome Response of Escherichia coli O157∶H7 Sakai during Dynamic Changes in Growth Kinetics Induced by an Abrupt Downshift in Water Activity. PLoS ONE, 9(3), e90422.

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Microarray Gene Expression Analysis Protocol

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GeneSpring GX 10.0 (Agilent Technologies, Santa Clara, California, USA) software was used for gene expression analysis. To standardize the data using the method of Lowess [22 (link)], each chip used the 50% as the base, and each gene was standardized by a median reference. The standardized sample data was entered into the GeneSpring GX software. Firstly, quality controls were performed to select the data and samples of the inserted microarray data. Secondly, all the samples were divided into 3 groups: the normal group (ND), pre-diabetic group (PD), and T2D group (D). Thirdly, matched pairwise analysis was conducted and groups were compared pair-wisely. Finally, less significant genes were filtered out. The selection threshold was set as: False discovery rate (FDR) = 5%, p < 0. 05, |fold change| ≥ 2.

Liu C., Lu L., Kong Q., Li Y., Wu H., Yang W., Xu S., Yang X., Song X., Yang J.Y., Yang M.Q, & Deng Y. (2014). Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2. BMC Bioinformatics, 15(Suppl 17), S5.

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Microarray Design and Analysis of APEC O1:K1:H7

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The sequence used for the array design was the APEC O1:K1:H7 reference strain (NC_008563) (Johnson et al., 2007 (link)). All predicted ORFs were designated for probe design. The web-based Agilent eArray system (Agilent Technologies, https://earray.chem.agilent.com/earray/) was used with the following settings during the microarray probe design: Tm (70°C) matching methodology, 60-mer probe length, 3 probes/target. The protocol, experimental setup, RNA extraction, amplification, labelling, and hybridization are described in detail at http://www.ebi.ac.uk/arrayexpress/. Data analysis was done using GeneSpring GX 10.0 (Agilent).
The ultimate purpose of this analysis was to develop a synthetic medium reproducing these conditions as near as possible. For this reason, a full analysis of gene expression was not carried out by COGs gene classes. They were grouped according to genes likely to affect intracellular survival, response to stress, and virulence gene expression as indicated below.

Zhou X., Richards P., Windhorst D., Imre A., Bukovinski A., Ruggeri J., Elazomi A, & Barrow P. (2022). Generation of an inactivated vaccine for avian pathogenic Escherichia coli using microarrays: A more rational approach to inactivated vaccine design. Open Veterinary Journal, 12(2), 221-230.

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Transcriptomic Profiling of hMSC Clones

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Total RNA was extracted from hMSC clones (RECs, moderately expanding clones [MECs], and slowly expanding clones [SECs]). After purification, 300 ng of total RNA was labeled with Cy3 and hybridized to an Agilent human whole‐genome chip (4 × 44 K, AMADID = 14 850; Agilent Technologies, Santa Clara, California), which was scanned using a microarray scanner system (Agilent Technologies). Gene expression analysis was performed using GeneSpring GX10 (Agilent Technologies). The results were uploaded to the Gene Expression Omnibus (number: GSE86369). The quantitative PCR was performed with fast SYBR Green master mix or Power SYBR Green PCR master mix (Life Technologies) and an HT7900 fast real‐time PCR system or a ViiA7 real‐time PCR system (Applied Biosystems) (Table S1). Microarray and quantitative PCR analyses are described in the Supplemental Experimental Procedures.

Harada S., Mabuchi Y., Kohyama J., Shimojo D., Suzuki S., Kawamura Y., Araki D., Suyama T., Kajikawa M., Akazawa C., Okano H, & Matsuzaki Y. (2020). FZD5 regulates cellular senescence in human mesenchymal stem/stromal cells. Stem Cells (Dayton, Ohio), 39(3), 318-330.

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MicroRNA Profiling of GIST Samples

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Human microRNA microarrays (HmiOA7.0, PhalanxBio Inc.) were used in GIST samples. The microarray contains probes for 2003 human microRNAs from Sanger miRBase release 19.0. Total RNA (100 ng) derived from GIST samples was labelled with Cy5 or Cy3. Microarray slides were scanned by DNA Microarray Scanner G2565B (Agilent Technology). Labeling and hybridization were performed in accordance with the protocols in the PhalanxBio miRNA microarray system. The microarray image information was converted into spot intensity values using Feature Extraction Software. The signal after background subtraction was exported directly into the GeneSpring GX10 software (Agilent Technologies, Santa Clara, CA).

Ding J., Xia Y., Yu Z., Wen J., Zhang Z., Zhang Z., Liu Z., Jiang Z., Liu H, & Liao G. (2019). Identification of upstream miRNAs of SNAI2 and their influence on the metastasis of gastrointestinal stromal tumors. Cancer Cell International, 19, 289.

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Prostate Cancer Transcriptome Analysis

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The RNA samples were extracted from four PCa biopsy samplesand four BPH biopsy controls for microarray profiling and performed in Affymetrix Human U133 Plus 2 arrays for gene expression profiling analysis. Microarray data were analyzed using GeneSpring GX 10 (Agilent). The complete microarray datasets have been available on the NCBI Gene Expression Omnibus (GEO Accession Number: GSE104749). Statistical analysis of gene expression microarray data was carried out using the GeneSpring GX software program. Raw data from gene expression files were imported into the program. Post hoc Bonferroni multiple comparison testing was performed to identify statistically significant differences in the expression of genes between PCa samples and BPH RNA samples, with P values less than 0.05 considered significant.

Shan M., Xia Q., Yan D., Zhu Y., Zhang X., Zhang G., Guo J., Hou J., Chen W., Zhu T., Zhang X., Xu J., Wang J., Ding T, & Zheng J. (2017). Molecular analyses of prostate tumors for diagnosis of malignancy on fine-needle aspiration biopsies. Oncotarget, 8(62), 104761-104771.

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Agilent Microarray Gene Expression Analysis

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Total RNA was isolated by Trizol, and RNA quality was checked using denaturing agarose gels. For microarray, the cRNA was purified and then hybridized to the 4×44K oligo microarray manufactured by Agilent Technologies. Microarray data were analyzed using an Agilent G2565BA Microarray Scanner. Comparative analysis was done using GeneSpring GX 10 (Agilent Technologies) [2 (link), 25 (link)–26 (link)]. The experimental data were compared to baseline data. Genes were considered differentially expressed if expression changed by at least two-fold.

Wang Q., Li J., Wu W., Shen R., Jiang H., Qian Y., Tang Y., Bai T., Wu S., Wei L., Zang Y., Zhang J, & Wang L. (2016). Smad4-dependent suppressor pituitary homeobox 2 promotes PPP2R2A-mediated inhibition of Akt pathway in pancreatic cancer. Oncotarget, 7(10), 11208-11222.

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Genome-wide expression profiling of cell lines

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Genome-wide expression arrays (Illumina, San Diego, CA, USA) were used for the analysis of SAS (human WG6, version 3, 48 803 genes) and HepG2 (human WG6, version 1, 47 296 genes). Data were analyzed by TransGenic (Kumamoto, Japan). For MM102, a 3D-Gene mouse Oligo chip 24k (23 522 genes; Toray Industries, Tokyo, Japan) was used and the data were analyzed by Toray Industries using GeneSpring GX10 (Agilent Technologies, Santa Clara, CA, USA). HepG2 versus HepG2 cancer stem cell (CSC) analysis was carried out by MOGERA-Array self (Tohoku Chemical, Iwate, Japan).

Fukumoto M., Amanuma T., Kuwahara Y., Shimura T., Suzuki M., Mori S., Kumamoto H., Saito Y., Ohkubo Y., Duan Z., Sano K., Oguchi T., Kainuma K., Usami S., Kinoshita K., Lee I, & Fukumoto M. (2014). Guanine nucleotide-binding protein 1 is one of the key molecules contributing to cancer cell radioresistance. Cancer Science, 105(10), 1351-1359.

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