Project description:This cohort is an extension of our previous dataset (Spiers et al) containing DNA methylation profiled with the EPIC array on an additional 40 human fetal brain samples. Please note that these samples are from the same cohort as GSE58885.
Project description:Genome-wide patterns of DNA methylation were quantified using the Illumina Infinium EPIC array (“EPIC array”) in DNA samples isolated from buccal swabs collected at ages 5, 10 and 18 and whole blood samples collected at age 18 from 118 Monozygotic twin pairs from the Environmental Risk (E-Risk) Longitudinal Twin Study. Comparison of DNA methylation profiles of 233 age 18 blood samples with data on EPIC and Illumina 450K methylation arrays.
Project description:DNA methylation is the most studied epigenetic modification due to its role in regulating gene expression and aberrations in methylation involved in the pathogenesis of cancer and several diseases. The method of choice to evaluate genome-wide methylation has been the Illumina HumanMethylation450 BeadChip (450K), but it was recently replaced with the MethylationEPIC BeadChip (EPIC). We therefore sought to validate the EPIC array in comparison to the 450K array for both fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) pediatric brain tumors. We also performed analysis on the EPIC array with paired FF and FFPE samples, to adapt to a clinical setting where FFPE is routinely used. Further, we compared two restoration methods, REPLI-g and Infinium, for FFPE-derived DNA on the EPIC array.
Project description:DNA methylation is the most studied epigenetic modification due to its role in regulating gene expression and aberrations in methylation involved in the pathogenesis of cancer and several diseases. The method of choice to evaluate genome-wide methylation has been the Illumina HumanMethylation450 BeadChip (450K), but it was recently replaced with the MethylationEPIC BeadChip (EPIC). We therefore sought to validate the EPIC array in comparison to the 450K array for both fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) pediatric brain tumors. We also performed analysis on the EPIC array with paired FF and FFPE samples, to adapt to a clinical setting where FFPE is routinely used. Further, we compared two restoration methods, REPLI-g and Infinium, for FFPE-derived DNA on the EPIC array.
Project description:DNA methylation microarray analysis was performed on human donor whole blood samples from patients with and without AMD. A total of 30 patient samples including 16 Normal, 3 AREDS grade 2 (early AMD) and 11 AREDS grade 3 (intermediate AMD) (AMD total, n = 14) were selected. Samples were obtained from individuals phenotyped according to the Age-Related Eye Disease Study (AREDS) classification. DNAm levels were measured using the EPIC-array (Illumina Inc., San Diego, CA, USA). Samples run on the EPIC-array were randomized and balanced for disease status and smoking status to minimise chip and row specific effects. The EPIC-array incorporated technical controls into the experimental design. In total, 500 ng (50 ng/μL) total peripheral whole blood-derived gDNA was bisulfite converted using the EZ-96 DNA methylation kit (Zymo Research, Irvine, CA, USA) and hybridised to the EPIC-array according to the manufacturer’s instructions. Quality control analysis was performed using GenomeStudio (v2011.1). Raw IDAT files were then read into R (version 3.31) using the read.metharray.exp function within the minfi package. DNA methylation microarray data was collected in order to assess the estimated DNA methylation age using the Horvath multi-tissue, Hannum and Skin & Blood epigenetic clocks and to identify loci of differential methylation between the experimental groups.
Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.
Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.