Project description:BACKGROUND: The newly released 450k DNA methylation array from Illumina, Inc. offers the possibility to analyze more than 480,000 individual CpG sites in a user friendly standardized format. In this study the relationship between the ?-values provided by the Illumina, Inc. array for each individual CpG dinucleotide and the quantitative methylation levels obtained by pyrosequencing were analyzed. In addition, the representation of microRNA genes and imprinted loci on the Illumina, Inc. array was assessed in detail. Genomic DNA from 4 human breast cancer cell lines (IPH-926, HCC1937, MDA-MB-134, PMC42) and 18 human breast cancer specimens as well as 4 normal mammary epithelial fractions was analyzed on 450k DNA methylation arrays. The ?-values for 692 individual CpG sites from 62 different genes were cross-validated using conventional quantitative pyrosequencing. FINDINGS: The newly released 450k methylation array from Illumina, Inc. shows a high concordance with quantitative pyrosequencing if identical CpG sites are analyzed in cell lines (Spearman r?=?0.88, p???0.0001), which is somewhat reduced in primary tumor specimens (Spearman r?=?0.86, p???0.0001). 80.7% of the CpG sites show an absolute difference in methylation level of less than 15 percentage points. If different CpG sites in the same CpG islands are targeted the concordance is lower (r?=?0.83 in cell lines and r?=?0.7 in primary tumors). The number of CpG sites representing microRNA genes and imprinted loci is very heterogeneous (range: 1 - 70 CpG sites for microRNAs and 1 - 288 for imprinted loci). CONCLUSIONS: The newly released 450k methylation array from Illumina, Inc. provides a genome-wide quantitative representation of DNA methylation aberrations in a convenient format. Overall, the congruence with pyrosequencing data is very good. However, for individual loci one should be careful to translate the ?-values directly into percent methylation levels.
Project description:Epigenome-wide association studies (EWAS) have focused primarily on DNA methylation as a chemically stable and functional epigenetic modification. However, the stability and accuracy of the measurement of methylation in different tissues and extraction types is still being actively studied, and the longitudinal stability of DNA methylation in commonly studied peripheral tissues is of great interest. Here, we used data from two studies, three tissue types, and multiple time points to assess the stability of DNA methylation measured with the Illumina Infinium HumanMethylation450 BeadChip array. Redundancy analysis enabled visual assessment of agreement of replicate samples overall and showed good agreement after removing effects of tissue type, age, and sex. At the probe level, analysis of variance contrasts separating technical and biological replicates clearly showed better agreement between technical replicates versus longitudinal samples, and suggested increased stability for buccal cells versus blood or blood spots. Intraclass correlations (ICCs) demonstrated that inter-individual variability is of similar magnitude to within-sample variability at many probes; however, as inter-individual variability increased, so did ICC. Furthermore, we were able to demonstrate decreasing agreement in methylation levels with time, despite a maximal sampling interval of only 576 days. Finally, at 6 popular candidate genes, there was a large range of stability across probes. Our findings highlight important sources of technical and biological variation in DNA methylation across different tissues over time. These data will help to inform longitudinal sampling strategies of future EWAS.
Project description:BackgroundAs the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets.ResultsThe standard index of DNA methylation at any specific CpG site is ? = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (?s) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive.ConclusionsCareful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.
Project description:DNA methylation has been shown to be spatially dependent across chromosomes. Previous studies have focused on the influence of genomic context on the dependency structure, while not considering differences in dependency structure between individuals. We modeled spatial dependency with a flexible framework to quantify the dependency structure, focusing on inter-individual differences by exploring the association between dependency parameters and technical and biological variables. The model was applied to a subset of the Finnish Twin Cohort study (N = 1611 individuals). The estimates of the dependency parameters varied considerably across individuals, but were generally consistent across chromosomes within individuals. The variation in dependency parameters was associated with bisulphite conversion plate, zygosity, sex and age. The age differences presumably reflect accumulated environmental exposures and/or accumulated small methylation differences caused by stochastic mitotic events, establishing recognizable, individual patterns more strongly seen in older individuals.
Project description:The Illumina Infinium HumanMethylation450 BeadChip (450k) is widely used for the evaluation of DNA methylation levels in large-scale datasets, particularly in cancer. The 450k design allows copy number variant (CNV) calling using existing bioinformatics tools. However, in cancer samples, numerous large-scale aberrations cause shifting in the probe intensities and thereby may result in erroneous CNV calling. Therefore, a baseline correction process is needed. We suggest the maximum peak of probe segment density to correct the shift in the intensities in cancer samples.CopyNumber450kCancer is implemented as an R package. The package with examples can be downloaded at http://cran.r-project.orgnour.marzouka@medsci.uu.seSupplementary data are available at Bioinformatics online.
Project description:We propose an extension to quantile normalization that removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using data sets from The Cancer Genome Atlas and a large case-control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.
Project description:The Illumina Infinium HumanMethylation450 BeadChip is frequently used in epigenetic research. Besides quantile normalization there is currently no standard method to normalize the data between arrays. We describe some properties of the data generated by this platform and present a normalization method based on local regression. We compare the performance of this method with other commonly used approaches in three benchmarks (correlation between 21 pairs of technical replicates, detection of differential methylation and correlation of methylation levels for smoking-associated CpG sites with smoking behavior of 655 participants of an epidemiological study). Results indicate that the proposed method improves reproducibility, whereas some commonly used methods can have adverse effects.
Project description:DNA methylation profile for the samples from 143 prostate cancer patients are provided. DNA methylation profiling of 143 prostate cancer patients. *** Clinical data will be provided when the data are open to the public.