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DNA methylation profiling for 850k reannotation and normalization evaluation [450k]

ABSTRACT: Illumina Infinium DNA Methylation (5mC) profiling arrays are a popular technology to measure genome-scale distribution of 5mC at low cost and high throughput, especially in cancer and other complex diseases. Following the success of the HumanMethylation450 array (450k), Illumina released the MethylationEPIC array (850k) featuring increased coverage of enhancers in addition to regulatory regions primarily covered by the 450k (i.e. promoters, gene bodies). Despite its widespread use, the analysis of 850k data remains suboptimal as it mostly still relies on Illumina’s default annotation, which underestimates enhancers and long noncoding RNAs (lncRNAs). We thus developed an approach, based on ENCODE and LNCipedia databases, that greatly improves Illumina’s default annotation of enhancers and long noncoding transcripts. Comparisons between the re-annotated 850k and its precursor, the 450k, or RRBS, another high-throughput 5mC profiling technology, revealed that the 850k covers at least three times more enhancers and lncRNAs than the other two technologies. We further investigated the reproducibility of the three technologies and applied various normalisation methods to 850k data, showing that most of them reduce variability to a level below that of RRBS. When analyzed with our new annotation and normalization pipeline, profiling for 5mC changes in breast cancer biopsies with the 850k highlighted aberrant enhancers methylation as the predominant feature, confirming previous reports. In conclusion, our study provides an updated analysis pipeline for 850k data based on a refined probe annotation and normalization that allows for the improved analysis of methylation at enhancers and long noncoding transcripts.

ORGANISM(S): Homo sapiens

PROVIDER: GSE198626 | GEO | 2022/11/11

REPOSITORIES: GEO

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Project description:Prenatal exposure to neurotoxicants such as lead (Pb) may cause stable changes in the DNA methylation (5mC) profile of the fetal genome. However few studies have examined its effect on the DNA de-methylation pathway, specifically the dynamic changes of the 5-hydroxymethylcytosine (5hmC) profile. Therefore, in this study, we investigate the relationship between Pb exposure and 5mC and 5hmC modifications during early development. To study the changes in the 5hmC profile, we use a novel modification of the Infinium™ Human methylation 450K assay (Illumina, Inc.), which we named HMeDIP-450K assay, in an in vitro human embryonic stem cell model of Pb-exposure. We model Pb-exposure associated 5hmC changes as clusters of correlated, adjacent CpG sites, which are co-responding to Pb. We further extend our study to look at Pb-dependent changes in high density 5hmC regions in umbilical cord blood DNA from 48 mother-infant pairs from the Early Life Exposure in Mexico to Environmental Toxicants (ELEMENT) cohort. For our study, we randomly selected UCB from 24 male and 24 female children from the 1st and 4th quartiles of Pb levels. Our data show that Pb-associated changes in the 5hmC and 5mC profiles can be divided into sex-dependent and sex-independent categories. Interestingly, differential 5mC sites are better markers of Pb-associated sex-dependent changes compared to differential 5hmC sites. In this study we identified several 5hmC and 5mC genomic loci, which we believe might have some potential as early biomarkers of prenatal Pb-exposure. Human Methylation 450K array coupled with 5-hydroxymethylcytosine (5hmC) IP or HMeDIP-450K array, was used to determine the high density 5hmC profile of 46 Umbilical cord blood samples from the ELLEMENT cohort. HM450K array, without IP was used to determine the 5-methylcytosine(5mC) plus 5hmC profile. The 5hmC region detected from the HMeDIP-450K array was subtracted from the HM450K(without IP) to get putative high density 5mC regions.

Project description:Background: As 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 characterised. 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 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. Results: The standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities. Betas calculated from raw signal intensities (the default GenomeStudio behaviour) 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. Conclusions: Careful selection of preprocessing steps can minimise 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 an R software package called wateRmelon, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilise the same normalization methods and data quality tests on 450K data.

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DNA methylation profiling for 850k reannotation and normalization evaluation [450k]

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