Dataset Information

De novo identification of differentially methylated regions in the human genome.

ABSTRACT:

Background

The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model.

Results

We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons.

Conclusions

The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

SUBMITTER: Peters TJ

PROVIDER: S-EPMC4429355 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

De novo identification of differentially methylated regions in the human genome.

Peters Timothy J TJ Buckley Michael J MJ Statham Aaron L AL Pidsley Ruth R Samaras Katherine K V Lord Reginald R Clark Susan J SJ Molloy Peter L PL

Epigenetics & chromatin 20150127

<h4>Background</h4>The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the diffe ...[more]

PMID: 25972926

Similar Datasets

Project description:BackgroundCutaneous squamous cell carcinoma (cSCC) occurs 65-200 times more in immunosuppressed organ transplant patients than in the general population. T cells, which are targeted by the given immunosuppressive drugs, are involved in anti-tumor immune surveillance and are functionally regulated by DNA methylation. Prior to kidney transplantation, we aim to discover differentially methylated regions (DMRs) in T cells involved in de novo post-transplant cSCC development.MethodsWe matched 27 kidney transplant patients with a future de novo cSCC after transplantation to 27 kidney transplant patients without cSCC and studied genome-wide DNA methylation of T cells prior to transplantation. From 11 out of the 27 cSCC patients, the DNA methylation of T cells after transplantation was also examined to assess stability of the observed differences in DNA methylation. Raw methylation values obtained with the 450k array were confirmed with pyrosequencing.ResultsWe found 16 DMRs between patients with a future cSCC and those who do not develop this complication after transplantation. The majority of the DMRs were located in regulatory genomic regions such as flanking bivalent transcription start sites and bivalent enhancer regions, and most of the DMRs contained CpG islands. Examples of genes annotated to the DMRs are ZNF577, coding for a zinc-finger protein, and FLOT1, coding for a protein involved in T cell migration. The longitudinal analysis revealed that DNA methylation of 9 DMRs changed significantly after transplantation. DNA methylation of 5 out of 16 DMRs was relatively stable, with a variation in beta-value lower than 0.05 for at least 50% of the CpG sites within that region.ConclusionsThis is the first study demonstrating that DNA methylation of T cells from patients with a future de novo post-transplant cSCC is different from patients without cSCC. These results were obtained before transplantation, a clinically relevant time point for cSCC risk assessment. Several DNA methylation profiles remained relatively stable after transplantation, concluding that these are minimally affected by the transplantation and possibly have a lasting effect on post-transplant cSCC development.

Dataset Information

De novo identification of differentially methylated regions in the human genome.

Background

Results

Conclusions

Publications

De novo identification of differentially methylated regions in the human genome.

Similar Datasets

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