Microarray analysis was performed with the Illumina MouseWGE6 BeadChip (Illumina, London, UK). All RNA samples were analyzed on the same day under identical conditions. RNA samples were prepared for array analysis using the Illumina TotalPrep-96 RNA Amplification Kit, following the manufacturer’s instructions (Ambion/Applied Biosystems, Warrington, UK). First and second strand cDNA was synthesized from 0.1 to 0.5 μg of total RNA and labeled with biotin. The biotin-labeled cRNA was applied to the arrays using the whole-genome gene expression direct hybridization assay system from Illumina. Finally, the BeadChips was scanned using the Illumina BeadArray Reader. The data was extracted using BeadStudio 3.2 (Illumina, London, UK).
Beadstudio 3
Manufactured by Illumina
Sourced in United States
BeadStudio 3.2 is a software suite that enables the analysis of data generated from Illumina's DNA microarray platforms. It provides tools for data visualization, normalization, and quality control.
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Lab products found in correlation
Streptavidin cy3, by GE Healthcare (4 mentions)
Beadarray reader, by Illumina (3 mentions)
Iscan reader, by Illumina (3 mentions)
Rneasy mini kit, by Qiagen (2 mentions)
Trizol reagent, by Thermo Fisher Scientific (2 mentions)
Totalprep rna amplification kit, by Illumina (2 mentions)
Genomestudio v2009, by Illumina (2 mentions)
Goldengate assay, by Illumina (2 mentions)
High capacity cdna transcription kit, by Thermo Fisher Scientific (2 mentions)
Totalprep kit, by Illumina (2 mentions)
Taqman fast universal master mix, by Thermo Fisher Scientific (2 mentions)
Rneasy plus mini kit, by Qiagen (2 mentions)
Beadstation, by Illumina (2 mentions)
Totalprep 96 rna amplification kit, by Illumina (1 mentions)
Whole genome gene expression direct hybridization assay system, by Illumina (1 mentions)
Genespring gx11, by Agilent Technologies (1 mentions)
Humanht 12 v4 expression beadchip, by Illumina (1 mentions)
Microarray platform, by Illumina (1 mentions)
Rnase free dnase set, by Qiagen (1 mentions)
Beadstation array reader, by Illumina (1 mentions)
32 protocols using beadstudio 3
1
Microarray Analysis of Mouse Transcriptome
2
Gene Expression Profiling of SH-SY5Y Cells
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Briefly, SH-SY5Y and SH-SY5Y-APP cells were harvested, processed and read on an Illumina microarray platform. Total RNA was extracted from three biological replicates. Cells were washed twice, scraped in ice-cold PBS and centrifuged for 5 min at 500 g, 4 °C. The cell pellet obtained was resuspended in TRIzol Reagent (Invitrogen) for RNA extraction, followed by purification using the RNeasy Mini kit (Qiagen) according to the instructions of the manufacturer. DNA contamination was removed by DNase treatment using the RNase-Free DNase Set (Qiagen) during the RNA purification step. RNA quantification was carried out using a Nanodrop spectrophotometer. Biotinylated complementary RNA was then generated from 400 ng of the harvested RNA using the Illumina TotalPrep RNA Amplification Kit, and hybridized to the HumanHT-12 v4 Expression BeadChips (Illumina), which contains 47 231 probes against known genes. Data collection was carried out by scanning in an Illumina BeadStation array reader. The data were processed and controlled for quality using BeadStudio 3.2 (Illumina), and subsequently imported into GeneSpring GX 11.5 (Agilent) for analysis. Differential gene lists were generated based on a fold change of >1.5. Statistical significance was established at p-value < 0.05 according to the unpaired Student’s t-test with the Benjamini–Hochberg multiple testing correction.
3
Mouse RNA Expression Profiling by Microarray
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Total RNA (300 ng) was used as input for labeling. T7-linked double-stranded cDNA was synthesized, and in vitro transcription incorporating biotin-labeled nucleotides was performed using the Premier RNA Amplification Kit (Thermo Fisher Scientific). Purified and labeled cRNA was then hybridized onto MouseRef-8 v2 Expression BeadChips (Illumina). After washing, the chips were stained with streptavidin-Cy3 (GE Healthcare) and scanned using the iScan reader (Illumina) and its software. Bead intensities were mapped using BeadStudio 3.2 (Illumina). Background correction was performed using the Affymetrix Robust Multiarray Analysis background correction model. Variance stabilization was performed using the log2 scaling, and gene expression normalization was calculated with the method implemented with the lumi package of R-Bioconductor. Data postprocessing and graphics were performed with in-house–developed functions. Hierarchical clustering was performed with one minus correlation metric and the unweighted average distance (also known as group average) linkage method. The data were deposited in the National Center for Biotechnology Information’s (NCBI’s) Gene Expression Omnibus with accession number GSE95608.
4
Transcriptome Analysis of Mouse Embryos
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Embryos from SCNT and fertilization with/without Aph treatment in 3 replicates, MII oocytes and cumulus cells were lysed and processed for transcriptome analysis by microarray using the Illumina BeadStation 500 (Illumina, San Diego, CA, USA) platform as previously described by Schwarzer and colleagues [40] (link). Briefly, total RNA was extracted using the ZR RNA MicroPrep kit (Zymo Research, R1061). Biotin-labeled cRNA was generated using the TargetAmp 2-Round Biotin-aRNA Amplification Kit 3.0 (Epicentre, TAB2R71024), of which 150 ng/µl was used for each hybridization reaction of 17 hours onto Mouse WG6 v2 expression BeadChips (Illumina). Chips were stained with streptavidin-Cy3 (GE Healthcare) and scanned using an iScan reader (Illumina). Thereafter, the bead intensities were mapped to gene information via BeadStudio 3.2 (Illumina). Microarray data of the embryos from SCNT and fertilization in vitro with/without Aph treatment, and from oocytes, were deposited at the NCBI Gene Expression Omnibus [41] (link) and are accessible through GEO Series accession number GSE53497 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=gxihoikadlijfed&acc=GSE53497 ).
5
ADNI Genotype Data Processing
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Data used in the preparation of this article were obtained from the ADNI database (http://www.loni.ucla.edu/ADNI ). The Illumina SNP genotyping data, demographic information, APOE genotype and baseline diagnosis information from 754 ADNI-1 participants, including 213 cognitive normal individual controls, 175 AD patients, and 366 patients with mild cognitive impairment (MCI) were downloaded from ADNI database. All participants provided written informed consent and study protocols were approved by participating sites’ Institutional Review Board.
SNP genotyping of 620,901 markers on ADNI-1 participants were generated using Illumina BeadStudio 3.2 software from bead intensity data. All SNP genotypes are publicly available for download at the ADNI website. For genotype imputation analysis, only SNPs fulfilling the following criteria were included (1) per-SNP call rate ≥ 0.98; (2) minor allele frequency (MAF) ≥ 0.01; (3) P-value for Hardy-Weinberg equilibrium (HWE) ≥ 10–6 in our sample set. Imputation was performed using the software MACH-ADMIX42 (link) using the 1000 Genomes Project Phase 3 V.5 (http://www.internationalgenome.org ) as a reference panel. We excluded SNPs with R2 < 0.3, MAF < 0.01 and all INDELs from the imputed genotype data to obtain genotypes for 7,512,167 SNPs for subsequent association analyses.
SNP genotyping of 620,901 markers on ADNI-1 participants were generated using Illumina BeadStudio 3.2 software from bead intensity data. All SNP genotypes are publicly available for download at the ADNI website. For genotype imputation analysis, only SNPs fulfilling the following criteria were included (1) per-SNP call rate ≥ 0.98; (2) minor allele frequency (MAF) ≥ 0.01; (3) P-value for Hardy-Weinberg equilibrium (HWE) ≥ 10–6 in our sample set. Imputation was performed using the software MACH-ADMIX42 (link) using the 1000 Genomes Project Phase 3 V.5 (
6
Genome-wide Genotyping Analysis Protocol
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The genome-wide genotyping analysis was conducted using Illumina HumanOmni ZhongHua-8 BeadChips containing more than 890,000 variations. Genotypes of SNPs were called by Illumina BeadStudio 3.2 software (Illumina, San Diego, CA, USA). SNPs were excluded if they had a call rate lower than 90%, minor allele frequency (MAF) of <1%, and/or significant deviation from Hardy-Weinberg equilibrium in the controls (P < 1 × 10−7). After data cleaning and quality control, 829,060 SNPs remained for the MethQTL analysis.
7
Optimizing Genome-Wide Linkage Analysis
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Genotype data were generated using Illumina BeadStudio 3.2 software. PLINK package [17 (link)]was used to remove non-autosomal SNPs and to further eliminate typing errors and uninformative markers. The exclusion criteria were minor allele frequency < 0.01, SNP call rate < 90%, and deviation from Hardy-Weinberg Equilibrium (p < 0.001). MERLIN program [18 (link)] was used to identify mistyped SNPs that are inconsistent with Mendelian inheritance. Moreover, to avoid bias in linkage calculation due to linkage disequilibrium (LD), one of each pair of SNPs was removed if the value of r2 is greater than 0.3. A total of 117 158 SNPs were included in linkage analysis ultimately.
8
Microarray Data Processing and Analysis
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Bead intensities were mapped to gene information using BeadStudio 3.2 (Illumina). Background correction was performed using the Affymetrix Robust Multi-array Analysis (RMA) background correction model [49] . Variance stabilization was performed using log2 scaling, and gene expression normalization was calculated with the quantile method implemented in the lumi package of R-Bioconductor. Data post-processing and graphics were performed with in-house developed functions in Matlab. Hierarchical clustering of genes and samples was performed with a correlation metric and the Unweighted Pair-Group Method using Average (UPGMA) linkage method.
All the raw and processed microarray data discussed in this publication have been deposited into NCBI's Gene Expression Omnibus [50] (link) and are accessible through GEO Series accession number GSE57506. (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi$acc=GSE57506 ).
All the raw and processed microarray data discussed in this publication have been deposited into NCBI's Gene Expression Omnibus [50] (link) and are accessible through GEO Series accession number GSE57506. (
9
Microarray RNA Expression Analysis
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DNA-free RNA samples to be analyzed by microarrays were prepared using Qiagen RNeasy columns with on-column DNA digestion. Three hundred nanograms of total RNA per sample were used as input for the linear amplification protocol (Ambion, Austin, TX, http://www.ambion.com ), which involved synthesis of T7-linked double-stranded cDNA and 12 h of in vitro transcription, incorporating biotin-labeled nucleotides. Purified and labeled cRNA was then hybridized for 18 h onto MouseRef-8 v2 gene expression BeadChips (Illumina, Inc., San Diego, http://www.illumina.com ) following the manufacturer's instructions. After washing, the chips were stained with streptavidin-Cy3 (GE Healthcare, Chalfont St. Giles, UK, http://www.gehealthcare.com ) and scanned using the iScan reader (Illumina, Inc., San Diego, USA) and accompanying software. Samples were exclusively hybridized as biological replicates.
The intensities for each bead were mapped to gene information using BeadStudio 3.2 (Illumina). Background correction was performed using the Affymetrix Robust Multi-array Analysis (RMA) background correction model, variance stabilization was performed using the log2 scaling, and gene expression normalization was calculated with the quantile method implemented in the lumi package of R-Bioconductor. Data post-processing and graphics were performed with in-house developed functions in Matlab.
The intensities for each bead were mapped to gene information using BeadStudio 3.2 (Illumina). Background correction was performed using the Affymetrix Robust Multi-array Analysis (RMA) background correction model, variance stabilization was performed using the log2 scaling, and gene expression normalization was calculated with the quantile method implemented in the lumi package of R-Bioconductor. Data post-processing and graphics were performed with in-house developed functions in Matlab.
10
Microarray Data Analysis Pipeline
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The bead intensities were mapped to gene information using BeadStudio 3.2 (Illumina). Background correction was performed using the Affymetrix Robust Multi-array Analysis (RMA) background correction model (Irizarry et al, 2003 ). Variance stabilization was performed using the log2 scaling, and gene expression normalization was calculated with the method implemented in the lumi package of R-Bioconductor. Data post-processing and graphics were performed with in-house developed functions in Matlab (MathWorks™). Hierarchical clustering of genes and samples was performed with one minus correlation metric and the unweighted average distance (UPGMA) (also known as group average) linkage method.
The GO terms were taken from the AMIGO gene ontology database (Ashburner et al, 2000 (link)). The significance of the GO terms of the DEGs was addressed calculating the P-values using an enrichment approach based on the hypergeometric distribution. All the sets of GO terms were back-propagated from the final term appearing in the gene annotation to the root term of each GO. The multi-test effect influence was corrected by controlling the false discovery rate using the Benjamini–Hochberg correction at a significance level α = 0.05.
The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE53498.
The GO terms were taken from the AMIGO gene ontology database (Ashburner et al, 2000 (link)). The significance of the GO terms of the DEGs was addressed calculating the P-values using an enrichment approach based on the hypergeometric distribution. All the sets of GO terms were back-propagated from the final term appearing in the gene annotation to the root term of each GO. The multi-test effect influence was corrected by controlling the false discovery rate using the Benjamini–Hochberg correction at a significance level α = 0.05.
The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE53498.
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