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Agilent scanner g2565ba

Manufactured by Agilent Technologies
Sourced in United States

The Agilent Scanner G2565BA is a microarray scanner designed for high-sensitivity, high-resolution scanning of gene expression and genomic DNA microarrays. It features a dual-laser system, autofocus capabilities, and scan resolutions up to 10 microns per pixel. The scanner is capable of reading a wide range of microarray slide formats.

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7 protocols using agilent scanner g2565ba

1

Differential Gene Expression Analysis

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The microarrays used in this work have been already described [5 (link)]. RNA was extracted from the culture samples at exponential (22.5 h, 46.5 h) and stationary (60 h) phase, and analysis were performed for two biological replicates for each condition (two strains and three growth times). Labeling of RNA preparations with Cy3-dCTP, labeling of genomic DNA as the reference sample with Cy5-dCTP (2.5 pmol/50 μl hybridization solution), and the purification procedures were carried out as described previously [43 (link)]. The hybridization conditions, washing, scanning with Agilent Scanner G2565BA, and the quantification of the images were accomplished as previously described [44 (link)].
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2

Microarray Data Analysis Workflow

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Microarray images were acquired by the Agilent scanner G2565BA (Agilent Technologies, Palo Alto, CA, USA) at 5 µm resolution and intensity raw data were extracted by the software Feature Extraction V10.5 (Agilent Technologies, Palo Alto, CA, USA).
Data preprocessing and statistical analysis were performed by LIMMA (LInear Model of Microarray Analysis) package [19] . The quality control of raw data was carried out according to MAQC (MicroArray Quality Control) project guidelines [20] (link). The intensity raw data were background subtracted by normexp method and normalized within-arrays by LOESS and between-arrays by scale methods.
Bayesian moderated t-statistic [21] (link) was used to perform the statistical analysis and only genes with Benjamini and Hochberg [22] adjusted-p-value <0.05 were considered as differentially expressed.
GeneCards (http://www.genecards.org) [23] (link), Onto-Express (http://vortex.cs.wayne.edu/ontoexpress/) [24] (link), [25] (link), and COREMINE (http://www.coremine.com/medical/) bioinformatics tools were adopted to build interaction networks among the differentially expressed genes and to perform an accurate screening of related scientific evidence.
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3

Mouse miRNA Expression Profiling

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Total RNA was isolated using a miRNeasy kit (Qiagen). After dephosphorylation and denaturation, the total RNA was labeled with cyanine 3-pCp and subsequently hybridized to an Agilent mouse microRNA microarray (release version 15) using the microRNA Complete Labeling and Hyb Kit (Agilent Technologies, Inc.). After hybridization for 20 h, the slides were washed using the Gene Expression Wash Buffer (Agilent Technologies, Inc.), scanned using an Agilent Scanner G2565BA, and processed and analyzed using Agilent Feature Extraction Software version 9.5.1. The raw data were analyzed using GeneSpring GX software version 12.5 (Agilent Technologies, Inc.).
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4

Profiling Mouse Kidney microRNA Expression

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Frozen kidney tissues were first placed on the RNAlater®-ICE (Life technologies) for 16 h at −20 °C before the subsequent homogenization process. Total RNA was isolated using the miRNeasy kit (Qiagen) following the manufacturer’s instructions and was quantified with a Nanodrop spectrophotometer (ND-1000, Nano drop Technologies, DE, USA). The input for the Agilent miR labeling system was 100 ng total RNA. Dephosphorylated and denatured total RNA was labeled with cyanine 3-pCp and subsequently hybridized to the Agilent mouse miR microarray release version 15 using the miR Complete Labeling and Hyb Kit (Agilent Technologies, Inc., Santa Clara, CA, USA). Following hybridization for 20 h, the slides were washed with a Gene Expression Wash Buffer Kit (Agilent) and measured using an Agilent Scanner G2565BA. Agilent Feature Extraction Software (version 9.5.1) and GeneSpring GX software (version 12.5, Agilent) were used for data processing, analysis, and monitoring.
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5

Genomic DNA Extraction and Array-CGH Analysis

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Genomic DNA was extracted from formol fixed paraffin embedded (FFPE) tissue using the Generead DNA FFPE kit (Qiagen, Hilden, Germany). Oligonucleotide array-comparative genomic hybridization (CGH) was performed using the standard version of the Agilent Human Genome CGH microarray 180K (Agilent Technologies, Santa Clara, CA, USA).
Microarrays were scanned using the Agilent scanner G2565BA. Images were extracted using Agilent Feature Extraction software and data were analyzed with Agilent Cytogenomics v.2.5.8.11 software.
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6

One-color Microarray Gene Expression Protocol

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After addition of spike-in controls, 200 ng of RNA was amplified and labeled using one-color microarray based gene expression protocol v 6.0; labeled cRNAs were hybridized to Human GE 4×44K v2 Microarray (Agilent Technologies, Santa Clara, CA). Slides were scanned by the Agilent G2565BA scanner and images were processed by Feature Extraction software v.10 (Agilent Technologies). The raw data were imported into GeneSpring 12.1 software (Agilent Technologies) and a quantile normalization was applied.
Microarray data have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus and are accessible via: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=xxsxlqouuaasmzk&acc=GSE44099.
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7

Microarray Analysis of IL-1β Induced Transcriptome

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Three sample RNA pools were run per sub-array with three individual RNA pool sub-arrays per condition. Agilent microarray was performed (Agilent 5190-2305, 5188-5282, 5188-5242, 5188-5327, and RNeasy mini kit, Qiagen 74104) following the labeling protocol (version 6.6, September 2012 Agilent Technologies, G4140-90040) per manufacturer’s instructions and scanned using the Agilent G2565BA scanner.
Data analysis was performed using the Bioconductor package Limma in the programing language “R.” Target files were created containing Agilent G2565BA microarray scanner output files. Background correction, cyclic loess normalization, and averaging of repeats was performed. A linear modeling matrix was built and fitted. Gene lists were filtered discarding those unaltered by IL-1ß in the order of a log2 fold-change of < 1 and for an adjusted P value of < 0.05. A pathway analysis functional output was obtained using Signaling Pathway Impact Analysis (SPIA) in R. All was as described in previous papers from our group.13 (link) A two-dimensional projection of the microarray expression data was generated using the non-parametric dimensionality reduction. This was achieved using the t-distributed stochastic neighbor embedding (t-SNE) algorithm in the R package Rtse. The resulting t-SNE output was plotted with R package ggplot2. The array data will be deposited in NCBI’s Gene Expression Omnibus.
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