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Humanmethylation27 beadchip

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The HumanMethylation27 BeadChip is a microarray-based DNA methylation analysis platform developed by Illumina. It is designed to interrogate the methylation status of over 27,000 CpG sites located across the human genome. The BeadChip provides a targeted, high-throughput method for DNA methylation profiling.

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64 protocols using humanmethylation27 beadchip

1

Integrative Gastric Cancer DNA Methylation Analysis

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We downloaded TCGA GC DNAm profiles (Illumina Human Methylation 450 BeadChip, Illumina Human Methylation 27 BeadChip), expression profiles, and corresponding clinical data through the UCSC Xena database (https://xena.ucsc.edu/) (Wang et al., 2019 (link)). The Illumina Human Methylation 450 BeadChip DNAm dataset contained two normal samples and 395 GC samples, while the Illumina Human Methylation 27 BeadChip DNAm dataset contained 25 normal samples and 48 GC samples. The expression profile dataset contained 32 normal samples and 372 GC samples. Table 1 lists the clinicopathological characteristics of the patients with GC. We downloaded the GC DNAm profile dataset GSE30601 from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) (Kurashige et al., 2016 (link)). The GSE30601 dataset was based on the GPL8490 platform (Illumina Human Methylation 27 BeadChip), containing 94 normal samples and 203 GC samples. The data from TCGA GC DNAm profiles were sorted and merged as the training dataset; the GEO GC DNAm profile dataset was used as the validation dataset. Because of the availability of public data in TCGA and GEO databases, this study did not require ethical approval or informed consent.
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2

DNA Methylation Analysis of Monozygotic Twins

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Data acquisition. The DNA methylation dataset, GSE38291 (16) , comprising data regarding 11 pairs of monozygotic twins discordant for type 2 diabetes, was downloaded from the Gene Expression Omnibus (http://www. ncbi.nlm.nih.gov/geo/) database. Each pair of monozygotic twins included one individual with T2D and one normal individual (GSM938065-GSM938086). The Illumina HumanMethylation27 BeadChips (Illumina Inc., San Diego, CA, USA), containing a pair of methylated and unmethylated probes designed for each CpG site, were used to detect the DNA methylation in the gene promoter region.
Quantification of DNA methylation signals. The raw intensities of methylated and unmethylated probes for each sample were extracted based on the Illumina HumanMethylation27 BeadChip. The intensity data were then normalized using quantile normalization. The M-value of each CpG site was calculated as the log 2 ratio of the normalized intensities of methylated probe versus unmethylated probe (17) . The M-values of all probes in the promoter of a single gene were calculated and the mid-value was considered to be the methylation level of this gene promoter.
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3

Genome-wide Methylation Profiling of Colorectal Cancer

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Methylation at the single-nucleotide resolution level for a total of 27,578 CpG sites was determined using HumanMethylation27 Beadchip (Illumina, San Diego, CA) for a panel of 45 colorectal cancer cell lines (See Supplementary Methods; ArrayExpress MTAB-7867). Promoter methylation data for a cohort of 223 primary colorectal tumors (Illumina HumanMethylation27 Beadchip) was available from The Cancer Genome Atlas (TCGA) [3 (link)]. In this study, tumors from all stages (American Joint Committee on Cancer staging system) and histologic grade were collected from newly diagnosed patients with colon or rectum adenocarcinomas undergoing surgical resection. None of the patients received neoadjuvant chemotherapy or radiotherapy. For bisulfite sequencing analysis, genomic DNA was bisulfite treated with EZ DNA Methylation-Gold Kit (Zymo Research, Irvine, CA) following the manufacturer’s instructions and then PCR-amplified. Primers used are listed in Additional file 1: Table S1.
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4

Genome-wide DNA Methylation Profiling

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DNA was isolated using the Wizard Genomic DNA Purification Kit (Promega, WI, USA). For the initial analyses, DNA methylation profiling of 19 cell lines and four bone samples was performed using the Illumina HumanMethylation27 BeadChip (Illumina Inc., California, USA), covering 27,000 CpG sites across the genome [10 (link)]. For an extended validation, DNA methylation profiling was performed on 10 additional patient samples and four bone samples using the Infinium HumanMethylation450 BeadChip from Illumina, covering 485,000 CpG sites across the genome. Data extraction and initial quality control of the bead summary raw data were performed using GenomeStudio V2011.1 and the Methylation module v1.9.0, both provided by Illumina. For each sample, Beta values for each probe (average ratio of signal from methylated probe relative to the sum of both methylated and unmethylated probes) were exported for downstream analysis.
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5

DNA Methylation Profiling of Osteosarcoma

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DNA methylation data for OS (accession no. GSE36002) (15 (link)) was obtained from the GEO in the National Center for Biotechnology Information database (www.ncbi.nlm.nih.gov/gds), which was deposited in the GPL8490 platform (Illumina Human Methylation27 BeadChip; Illumina Inc., San Diego, CA, USA). GSE36002 included 25 samples (19 OS cell lines, and six normal samples derived from two osteoblast and four normal bone samples). Specifically, the 19 OS cell lines were obtained from EuroBoNeT (eurobonet.pathobiology.eu/cd/index.php). The two normal bone samples were collected from patients with cancer (one with OS and one with renal cell cancer) at the Norwegian Radium Hospital (Oslo, Norway). The normal bone was obtained from a site as distant as possible from the tumor site. The other two normal bone samples from different donors were purchased from Capital Biosciences, Inc. (Gaithersburg, MD, USA). The two human osteoblast cultures separated from the calvariae of different donors were purchased from ScienCell Research Laboratories, Inc. (San Diego, CA, USA).
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6

Genome-wide DNA methylation profiling

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For all subjects, peripheral blood samples were collected at the visit time. The buffy coat and plasma samples were separated within two hours and stored at -80°C immediately. DNA was extracted from the buffy coat using Qiagen® QiAamp® Blood Kit. The HumanMethylation27 BeadChip and the HumanMethylation450 BeadChip from Illumina (San Diego, CA, USA) were used for the genome wide DNA methylation profiling in the initial and the second EWAS panels respectively, as described previously (Wang et al., 2010 (link); Xu et al, 2013 (link)). The methylation levels of the selected CpG sites for replications were determined by pyrosequencing technology (Wang et al, 2010 (link)), which is based on the principle of sequencing by synthesis. For methylation analysis, pyrosequencing not only offers individual methylation high-resolution results for all CpG sites, but also has built-in control for bisulfite treatment to improve accuracy and reproducibility. For each CpG site, a 100–350-bp region was amplified by polymerase chain reaction (PCR) using a pair of primers complementary to the bisulfite-treated DNA sequence. Therefore, in addition to the targeted CpG site, the pyrosequencing assay may involve several surrounding CpG sites.
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7

Integrative Methylation and Expression Analysis of OSCC

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All microarray data were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The methylation microarray (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38532) included 40 OSCC samples and 40 nontumor pairwise samples, based on the Illumina HumanMethylation27 BeadChip (GPL8490 platform). The gene expression microarray (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30784) used as the training dataset contained 167 OSCC samples and 45 normal oral tissues. The gene expression microarray (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31056) used for validation contained samples from 21 OSCC patients and 24 normal tissue samples. The Affymetrix Human Genome U133 Plus 2.0 array was used to annotate the probes in both cases. This integrated study was a second analysis of GEO data; as such, patient consent was not required.
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8

Differential Methylation Analysis of LUAD

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The 338 LUADs and non-malignant samples in the GEO database profiled by Illumina Infinium HumanMethylation27 BeadChip were used for differential methylation analysis. The datasets from the five experiments were combined using R package illuminaio by common probe IDs. Array data produced by different studies are confounded by non-biological variables such as different technicians or the environments. These biases are termed as “batch effects” and cannot be eliminated unless all the samples are performed in a single batch. Here, we adjusted the batch effects by applying gene-wise one-way ANOVA adjustment for expression values using the pamr.batchadjust function from the pamr package. Differential methylation analysis was performed using linear model provided in the limma R package (19 (link)). Probes that were differentially methylated between LUADs and non-malignant tissues were selected with thresholds of |logFC| > 1 and adjusted p < 0.05. Gene oncology and Reactome pathway enrichment analysis were performed using DAVID version 6.8 (20 (link)).
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9

Validating HGSOC Methylation Patterns in TCGA

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Illumina Human Methylation27 Beadchip data on HGSOC from The Cancer Genome Atlas data portal (http://cancergenome.nih.gov/dataportal) (“TCGA Cohort”) was used for independent validation of correlations observed in the Hammersmith cohort. Level 2 expression data on Affymetrix HGU133A microarrays, level 3 methylation data and annotated clinical data were obtained. The expression microarray data was pre-processed and normalised across samples.
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10

Validating Glioblastoma Methylation Profiles

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To validate the identified DMGs from GSE50923, another relevant DNA Methylation Profiling dataset, GSE22867 (29 (link)), was downloaded from the GEO database and used for data validation. GSE22867 included 55 GBM samples and 3 control brain samples. The platform was GPL8490 Illumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2). The β-value was calculated based on the methylated and unmethylated signal of the sample data, and a t-test was implemented using the genefilter package (version 1.56.0) (30 ) to identify significant differentially methylated CpGs (P<0.05). In addition, selected CpG sites exhibited a mean methylation (β-value) difference ≥0.05 between the disease group and the control group. Subsequently, the genes covering the differentially methylated CpGs were identified and compared with the identified DMGs from GSE50923.
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