Project description:Genome-wide DNA methylation studies are becoming increasingly important in unraveling the epigenetic basis of cell biology, aging and human conditions. The aim of the present study was to explore whether different methods for extracting DNA from whole blood can affect DNA methylation outcome, potentially confounding DNA methylation studies. DNA was isolated from healthy blood donors (n = 10) using three different extraction methods (i.e. two automatic extractions methods based on magnetic beads or isopropanol precipitation, and manual organic extraction). DNA methylation was analyzed using the Infinium HumanMethylation450 Bead Chip (Infinium 450K) (n = 30 samples in total), which is a frequently used method in genome-wide DNA methylation analyses. Overall, the different extraction methods did not have a significant impact on the global DNA methylation patterns. However, DNA methylation differences between organic extraction and each of the automated methods were in general larger than differences between the two automated extraction methods. No CpG sites or regions reached genome-wide significance when testing for differential methylation between extraction methods. Although this study is based on a small sample, these results suggest that extraction method is unlikely to confound Infinium 450K methylation analysis in whole blood.
Project description:Illumina HumanMethylation450 BeadChip (450K) has been commonly used to investigate DNA methylation in human tissues. Recently, it has been replaced by Illumina HumanMethylationEPIC BeadChip (EPIC) covering over 850,000 CpGs distributed genome-wide. Many consortia have now datasets coming from both arrays and aspire to analyze the two together. The placenta shows a high number of intermediate methylation levels and is often investigated for obstetric/birth outcomes, and potentially for long-term programming in offspring. We performed a systematic comparison between the two arrays using 108 duplicate placental samples from Gen3G birth cohort. We find that placenta shows a high per-sample correlation between the arrays, and higher median correlations at individual CpGs than those reported for blood. We identify 26,340 probes with absolute difference in per cent methylation >10%. We conclude that EPIC and 450K placental data can be combined, and we provide two lists of CpGs that should be excluded to avoid misleading results.
Project description:We present shinyMethyl, a Bioconductor package for interactive quality control of DNA methylation data from Illumina 450k arrays. The package summarizes 450k experiments into small exportable R objects from which an interactive interface is launched. Reactive plots allow fast and intuitive quality control assessment of the samples. In addition, exploration of the phenotypic associations is possible through coloring and principal component analysis. Altogether, the package makes it easy to perform quality assessment of large-scale methylation datasets, such as epigenome-wide association studies or the datasets available through The Cancer Genome Atlas portal. The shinyMethyl package is implemented in R and available via Bioconductor. Its development repository is at https://github.com/jfortin1/shinyMethyl.
Project description:This dataset includes gene expression data from 103 primary tumour samples. 86 samples from this dataset have already been deposited into GEO (GSE36924), and has been duplicated here since the data has been processed differently. This data is also available through the International Cancer Genome Consortium (ICGC) Data Portal (http://dcc/icgc.org), under the project code: Pancreatic Cancer (QCMG, AU). Access to the restricted clinical data must be made through the ICGC Data Access Compliance Office (http://www.icgc.org/daco). Overall design: This dataset contains gene expression array data from 103 primary pancreatic ductal adenocarcinoma samples. All samples have 1 biological replicate. These data have corresponding methylation 450K array data (GSE49149).
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:Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation ?-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.
Project description:Epigenetic modifications, such as DNA methylation, due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear.We investigated epigenome-wide methylation in cord blood of newborns in relation to maternal smoking during pregnancy.We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium HumanMethylation450 BeadChip (450K).We found differential DNA methylation at epigenome-wide statistical significance (p-value < 1.06 × 10-7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway, which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke.We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure.
Project description:DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ?480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus ?-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.
Project description:Although clonal selection by genetic driver aberrations in cancer is well documented, the ability of epigenetic alterations to promote tumor evolution is undefined. We used 450k arrays and next-generation sequencing to evaluate intratumor heterogeneity and evolution of DNA methylation and genetic aberrations in chronic lymphocytic leukemia (CLL). CLL cases exhibit vast interpatient differences in intratumor methylation heterogeneity, with genetically clonal cases maintaining low methylation heterogeneity and up to 10% of total CpGs in a monoallelically methylated state. Increasing methylation heterogeneity correlates with advanced genetic subclonal complexity. Selection of novel DNA methylation patterns is observed only in cases that undergo genetic evolution, and independent genetic evolution is uncommon and is restricted to low-risk alterations. These results reveal that although evolution of DNA methylation occurs in high-risk, clinically progressive cases, positive selection of novel methylation patterns entails coevolution of genetic alteration(s) in CLL.
Project description:BACKGROUND:In order to gain insight into the contribution of DNA methylation to disease progression of chronic lymphocytic leukemia (CLL), using 450K Illumina arrays, we determined the DNA methylation profiles in paired pre-treatment/relapse samples from 34 CLL patients treated with chemoimmunotherapy, mostly (n = 31) with the fludarabine-cyclophosphamide-rituximab (FCR) regimen. RESULTS:The extent of identified changes in CLL cells versus memory B cells from healthy donors was termed "epigenetic burden" (EB) whereas the number of changes between the pre-treatment versus the relapse sample was termed "relapse changes" (RC). Significant (p < 0.05) associations were identified between (i) high EB and short time-to-first-treatment (TTFT); and, (ii) few RCs and short time-to-relapse. Both the EB and the RC clustered in specific genomic regions and chromatin states, including regulatory regions containing binding sites of transcription factors implicated in B cell and CLL biology. CONCLUSIONS:Overall, we show that DNA methylation in CLL follows different dynamics in response to chemoimmunotherapy. These epigenetic alterations were linked with specific clinical and biological features.