Methylation profiling was completed at the microarray centre at the Centre for Applied Genomics at the Hospital for Sick Children (Toronto, Canada). Bisulphite conversion was completed using the EZ DNA Methylation kit (Zymo Research) according to the manufacturerʼs guidelines. Genome-wide DNA methylation patterns were analyzed using the HumanMethylation450 BeadChip platform according to manufacturer specifications (Illumina, San Diego, CA). Raw data underwent quality control and pre-processing using the R package “minifi”55 (link) and normalized using the R package “noob”56 (link). Probes with a SNP at or near the CpG, plus those on the X and Y chromosomes were removed. t-SNE plots were completed using the R package “t-SNE”57 . Raw.idat files are available at at the GEO wesbite under the ascension code GSE135017.
Humanmethylation450 beadchip platform
Manufactured by Illumina
Sourced in United States
The HumanMethylation450 BeadChip platform is a high-throughput microarray-based technology designed for genome-wide DNA methylation analysis. The platform allows for the interrogation of over 450,000 CpG sites across the human genome, providing a comprehensive view of DNA methylation patterns.
Automatically generated - may contain errors
Lab products found in correlation
Nanodrop 1000 spectrophotometer, by Thermo Fisher Scientific (2 mentions)
Ez dna methylation kit, by Zymo Research (1 mentions)
Sureprint g3 human ge v2 8 60 k microarray 039381, by Agilent Technologies (1 mentions)
Human gene expression array, by Thermo Fisher Scientific (1 mentions)
Human transcriptome array 2, by Thermo Fisher Scientific (1 mentions)
Snp 6.0 arrays, by Illumina (1 mentions)
Humanht 12 v4.0 expression beadchip platform, by Illumina (1 mentions)
Nextseq 500 platform, by Illumina (1 mentions)
Affymetrix human genome u133 plus 2.0 array, by Thermo Fisher Scientific (1 mentions)
Iscan reader, by Illumina (1 mentions)
Quant it picogreen dsdna assay kit, by Thermo Fisher Scientific (1 mentions)
Genomestudio v2011, by Illumina (1 mentions)
16 protocols using humanmethylation450 beadchip platform
1
DNA Methylation Profiling using Illumina HumanMethylation450 BeadChip
2
Transcriptional Profiling of Retinoblastoma
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Three sets of raw microarray data consisting of the expression profile of retinoblastoma were retrieved from Gene Expression Omnibus Database (GEO) (https://www.ncbi.nlm.nih.gov/geo/ ). These data consist of genome-scale DNA methylation profiling in Retinoblastoma by using Illumina Human Methylation 450 Bead Chip platform and samples from the normal human eye and five ocular diseases (GSE57362, 25 Samples) (Berdasco et al., 2017 (link)), Profiling of miRNAs in human retinoblastoma by using 2k custom array and RNA was extracted from two retinoblastoma and two matched normal retina samples (GSE7072, four Samples) (Huang et al., 2007 (link)), Distinct Gene Expression Profiles Define Anaplastic Grade in Retinoblastoma by using Affymetrix Human Gene 2ST Array and RNA was extracted from the 28 retinoblastoma and three matched normal retina samples (GSE110811, 31 Samples) (Hudson et al., 2018 (link)). Microarray datasets contain cancer and normal samples. The details of the datasets are given in Table 1 .
3
Genome-Wide DNA Methylation Analysis
4
Differential Methylation Analysis of CD in Blood
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We obtained the methylation data from a recent study that conducted differential methylation analysis using 121 CD cases and 191 healthy controls (Ventham et al., 2016 (link)) (GEO accession ID: GSE87648). The study provided whole genome methylation using Illumina HumanMethylation450 BeadChip platform (GPL13534), which contained ∼485,000 probes. We requested the methylation results from the author of the study. This differential methylation genes was generated using whole blood leukocyte samples. In the original work (Ventham et al., 2016 (link)), the authors normalized the methylation matrix using the R package lumi and estimated the cell proportion by the R package minfi. Lastly, Limma was used to identify differentially methylated CpG probes. Probes were mapped to genes according to the annotation file of the chip (Jiang et al., 2016 (link)). For genes with multiple probes, we selected the most significant probe for the gene.
5
Multi-Omics Data Integration and Preprocessing
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Three types of omics data were obtained, including 17,874 mRNA expression probes, 443,207 methylation CpG sites, and 416 miRNAs. We converted 17,874 mRNA expression probes to 17,358 gene level expressions by taking the mean value of multiple probes as the gene level expression, following the annotation from the Affymetrix GeneChip Human Exon 1.0 ST platform. Using the annotation from the Illumina Human Methylation 450 BeadChip platform, we mapped 443,207 CpG sites to 27,604 genes. We then took the mean beta value of multiple CpG sites in a gene as the gene level methylation signal. For miRNA, we filtered out biological features which had >30% of missing values across patients, leaving 212 miRNA features. There was no missing data in mRNA expression. Missing values in both methylation and miRNA data were imputed with the K nearest neighbor (KNN) imputation method [19] (link).
6
Genome-wide Methylation Profiling Protocol
7
Diagnostic Model for Periodontitis
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Two sets of Illumina HumanMethylation450 BeadChip platform data sets GSE59939 [57 (link)] and GSE53849 were selected as independent external verification data sets. After downloading the standardized data, the methylation level of characteristic CpGs was extracted and substituted into the model to assess the prediction ability of the model. Furthermore, a set of expression profile data set GSE10334 [58 (link)] was used to extract the expression profile of immune genes from the characteristic CpGs annotation to the promoter. A diagnostic model was established to distinguish normal healthy samples from periodontitis.
8
Colorectal Cancer Methylation and Expression
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DNA methylation data for GSE48684 were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/ ), which includes 41 normal colon samples, 42 colon adenomas, and 64 colorectal cancers. The methylation data were based on the Illumina Human Methylation 450 Bead Chip platform.8 (link) Gene expression data were obtained from the GEO database under accession numbers GSE89076, GSE81558 and GSE113513.9 (link),10 (link) GSE89076 includes 41 colorectal carcinoma tissues and 30 adjacent normal tissues, with data based on the Agilent-039494 SurePrint G3 Human GE v2 8 × 60 K Microarray 039381. GSE81558 includes 23 sporadic colorectal adenocarcinomas and 19 liver metastases from 23 patients with liver metabolism and 9 non-tumoral colorectal tissues. The 23 sporadic colorectal adenocarcinomas and 9 non-tumoral tissues were selected for further analysis. GSE113513 contains 14 matched colorectal cancer tissue and normal tissue samples from 14 patients. Both GSE81558 and GSE113513 were based on the Affymetrix Human Gene Expression Array.
9
Placental Methylation and Expression in GDM
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Microarray dataset GSE70494 (including gene expression dataset (GSE70493) and methylation dataset [GSE70453]) deposited by Binder et al were downloaded from the Gene Expression Omnibus database[16 (link)] (https://www.ncbi.nlm.nih.gov/ ). The GSE70453 methylation dataset was obtained from the Affymetrix Human Transcriptome Array 2.0 platform and includes 32 GDM placenta tissue samples and 31 healthy control placenta tissue samples. The GSE70493 gene expression profile dataset was obtained from the Illumina HumanMethylation450 BeadChip platform and contains 41 GDM placenta tissue samples and 41 healthy control placenta tissue samples. A total of 55 samples with both methylation and expression levels were selected, including 25 healthy control placenta tissue samples and 30 GDM placenta tissue samples.
10
Comprehensive Genomic Analysis of BRCAness
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We identified 40 BRCAness genes from literatures (ATM, ATR, AURKA, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDK12, CHD4, CHEK1, CHEK2, EMSY, ERCC1, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCI, KMT2A, MRE11A, MYC, NBS1, PALB2, PARP1, PAXIP1, PLK1, PTEN, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, SAMHD1, SEM1, TP53, TP53BP1, WEE1, WRN) [16 (link),36 (link),37 (link)]. We collected the BRCAness genomic and clinical information from these two resources: UCSC xena (http://xena.ucsc.edu/ , accessed on 18 November 2020) and PanCanAtlas (https://gdc.cancer.gov/node/905/ , accessed on 20 November 2020) covering 33 cancer types [38 (link)]. The details of data information are as follows: Variation data from over 10,000 cancer patients were from TCGA MAF file in PanCanAtlas; copy number variation (CNV) data detected by Affymetrix SNP 6.0 arrays were from UCSC xena; DNA methylation data detected by Illumina HumanMethylation450 BeadChip platform were from PanCanAtlas; RNA-seq data with normalized batch effects and log2 (norm_value+1) gene expression for all 33 cancer types were from PanCanAtlas; Clinical survival data were from UCSC xena. GISTIC2 was used to identify the genomic regions with significant gain or loss [39 (link)].
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