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Microarray platform

Manufactured by Illumina
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The Microarray platform is a laboratory equipment used for the analysis of gene expression, genotyping, and other genomic applications. It enables the simultaneous measurement of thousands of genetic markers or transcripts in a single experiment. The platform utilizes an array of microscopic DNA spots, each representing a specific gene or genetic sequence, to which complementary DNA or RNA samples are hybridized, allowing for the quantification and comparison of gene expression levels or the detection of genetic variations.

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8 protocols using microarray platform

1

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.
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2

Genotyping of DRD3 and BDNF polymorphisms in mental health disorders

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For the SCZ, TB, GBP, and BN samples, genomic DNA was purified from whole blood samples using non-enzymatic method previously described (Lahiri and Nurnberger 1991 (link)). Genotyping was done after the subjects had completed the follow-up, and all laboratory staff members were blind to suicide attempt status. In all, we genotyped 34 DRD3 and 14 BDNF polymorphisms in the discovery TS sample, of which 15 DRD3 and 4 BDNF polymorphisms were tagged using Haploview using minimum minor allele frequency of 0.2 and an r2 threshold of 0.8. The tag polymorphisms were genotyped using either TaqMan SNP genotyping assays (Life Technologies Inc.) at CAMH or a microarray platform (Illumina) (Hodgkinson et al. 2008 (link)) at the The Centre for Applied Genomics as described previously (Zai et al. 2010 (link)). For replication of the significant interaction finding, genotyping of the Val66Met and Ser9Gly polymorphisms in the TB, GBP, and BN repliation samples were done using TaqMan SNP genotyping assays at CAMH.
The Norwegian replication samples were genotyped at Expression Analysis (Durham, NC, USA) using the Affymetrix Genome-Wide Human SNP array 6.0 (Affymetrix Inc, Santa Clara, CA, USA). Quality control was performed using PLINK (Purcell et al. 2007 (link)). Details on quality control have been described previously (Finseth et al. 2013 ).
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3

Medulloblastoma Cell Line Dynamics

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In this study, we re-analyzed the experimental data in which, human medulloblastoma cell lines were exposed to four experimental conditions (CTRL, SHH+, EGF+, and SHH+EGF+) and sampled over 24 hours after the exposure to the agents. Gene expression data was generated with an Illumina microarray platform. There were three biological replicates available and we chose to take the median of the replicates for the analysis, since it is robust to unexpected variations. The fold-change ratios were calculated with respect to time 0 under the control. Further details of the experimental materials and methods are described in the literature [8 (link)]. The data set is available on the GEO website with the series name GSE46045.
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4

Transcriptomic Metric Evaluation in Blunt Trauma

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The transcriptomic metric was subsequently evaluated in an additional dataset of blunt trauma patients. This was a secondary analysis of the Activation of Coagulation and Inflammation in Trauma (ACIT2) study (NHS REC: 07/Q0603/29; E-MTAB-5882; https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-5882/), conducted between December 2008 and June 2012, including 6 control subjects and 26 critically ill blunt trauma patients,23 (link) as published in their correction.24 (link)Blood samples were collected on arrival and within 12 hours of injury, and at 24 hours and 72 hours following admission. Transcriptomic analysis was performed on whole blood collected with PAXGene tubes, and gene expression was measured with an Illumina microarray platform. Since the expression of all 63 genes was not available, the transcriptomic metric was constructed using the expression of 58 of the 63 genes (S2 Appendix, http://links.lww.com/SLA/B564). Due to the differing analysis and clinical reporting, outcome variables were dichotomized based on available clinical outcomes used in the original report.
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5

Profiling NPBSCs Gene Expression

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Example 8

The Illumina microarray platform was used to profile the global gene expression of NPBSCs at passage 10 (P10) and passage 20 (P20), human embryonic stem cells (HUES6), induced pluripotent stem cells (IPSCs) as well as primitive neural stem cells (pNSCs) and human neural progenitor cells (hNPCs), which were derived as described by Li et alia 2011 and Koch et alia, 2009, respectively. The heatmap demonstrates that NPBSCs express markers that are unique to these cells and distinguish NPBSCs from the other cell types previously published.

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6

Genome Scan for Hnf1a Modifier Genes

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The genome scan was performed on genomic DNA extracted from spleen or liver from the 28 most resistant (that had reached a minimal body growth of at least 8 g at P25) and the 58 most sensitive N2 Hnf1a−/− mice using a panel of 1449 polymorphic SNPs available in the Illumina-GoldenGate Mouse Linkage Panel (OPA GS0006826). 707 SNPs are different between 129S2 and CBA strains allowing to discriminate allelic contribution of each strain. SNP genotyping was carried out on the Integragen Illumina microarray platform (Evry, France). A second set of 22 resistant and 33 sensitive N2 Hnf1a−/− animals were manually genotyped for 26 polymorphic markers (see Supplementary Table S2). In the QTL region, modifier candidate genes were searched based on bioinformatic detection of non-synonymous SNPs between sensitive and resistant strains with publicly available SNP data from the last version of the Mouse Genomes Project (https://www.sanger.ac.uk/sanger/Mouse_SnpViewer/rel-1303)22 (link).
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7

Genotyping and Imputation Procedures

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The genotype data used in this study were obtained from a superset of samples that were genotyped and imputed as part of the full LIBD cohort, using previously described procedures [23] . Briefly, samples from the full cohort were genotyped across multiple Illumina microarray platforms (see Supplementary Methods) and underwent a standard quality control (QC) protocol [25] to remove low-quality and low-frequency variants. Haplotypes were phased using SHAPEIT [26] and then imputed using IMPUTE2 [27] with reference to 1000 Genomes phase 3. Imputed genotype dosages were converted to hard-call genotypes for variants with imputation posterior probabilities >0.9.
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8

Measuring Cytosolic and Membrane-bound GSTs

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Expression of cytosolic and membrane-bound GSTs was measured across the BXD family using Affymetrix and Illumina microarray platforms in brain and liver. Representative probe sets (S1 Table) were selected for each gene based on probe set specificity and mean expression. SNPs and other sequence variants, such as indels (insertions and deletions) or CNVs (copy number variants), overlapping probes have an important impact on the false discovery rate of expression differences and on identification of local expression quantitative trait loci (cis-eQTLs) [39 (link)–41 (link)]. No representative probe set target sequences overlap SNPs or other sequence variants that could interfere with GST measurements in this study.
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