Extensive Inter-Cyst DNA Methylation Variation in Autosomal Dominant Polycystic Kidney Disease Revealed by Genome Scale Sequencing.

Autosomal dominant polycystic kidney disease (ADPKD) is a heritable disease characterized by bilateral renal enlargement due to the growth of cysts throughout the kidneys. Inheritance of a disease-causing mutation is required to develop ADPKD, which results in end-stage kidney disease and is associated with a high morbidity. The pathology underlying cyst formation is not well understood. To address this, we have previously shown the global methylome is altered in ADPKD tissue, suggesting a role of DNA methylation in disease-state renal tissue. As cysts are believed to arise independently, we hypothesize that DNA methylation changes vary accordingly. Here we further investigate the role of DNA methylation within independent cysts to characterize key intra-individual changes. We demonstrate that fragments within CpG islands and gene bodies harbor the greatest amount of variation across the ADPKD kidney, while intergenic fragments are comparatively stable. A proportion of variably methylated genes were also differentially methylated in ADPKD tissue. Our data provide evidence that individual molecular mechanisms are operating in the development of each cyst.

Comparative assessment of DNA methylation patterns between reduced representation bisulfite sequencing and Sequenom EpiTyper methylation analysis.

AIM: Validation of sequencing-based DNA methylation data is an important step for meaningful translation of findings. However, there has been limited assessment of different platforms to validate methylation data from next generation sequencing. METHODS: We performed a comparative methylation analysis between the genome-wide platform of reduced representation bisulfite sequencing with a targeted, Sequenom EpiTyper platform (four genes were analyzed in 15 cell lines covering 52 CpG sites). RESULTS: We show that the accuracy of validation substantially improves if results from multiple and adjacent CpG sites are combined rather than at single CpG sites. We demonstrate increased read number improves accuracy of reduced representation bisulfite sequencing results. Further, by using series of replicates, we document variation in samples analyzed by Sequenom EpiTyper, indicating the importance of including replicates to increase precision. CONCLUSION: The results reveal potential sources of bias and provide a guideline for refining study design for DNA methylation analysis.

scan_tcga tools for integrated epigenomic and transcriptomic analysis of tumor subgroups.

AIM: The Cancer Genome Atlas contains multiple levels of genomic data (mutation, gene expression, DNA methylation, copy number variation) for 33 cancer types for almost 11,000 patients. However, a dearth of appropriate software tools makes it difficult for bench scientists to use these data effectively. MATERIALS & METHODS: Here, we present a suite of flexible, fast and command line-based scripts that will allow retrieval and analysis of DNA methylation (tool: scan_tcga_methylation.awk), mRNA (tool: scan_tcga_mRNA.awk) and miRNA expression (tool: scan_tcga_miRNAs.awk) from cancer genome atlas network level 3 data. RESULTS: We demonstrate the utility of these tools by analyzing DNA methylation and mRNA expression signatures of 60 frequently deregulated cancer genes and also of 30 miRNAs in primary (n = 102) and metastatic melanoma patients (n = 367). CONCLUSION: Our analysis illustrates the validity of the scan_tcga tools and reveals the epigenomic signatures and importance of identifying smaller patient subgroups with distinct molecular profiles.

Placental Hypomethylation Is More Pronounced in Genomic Loci Devoid of Retroelements.

The human placenta is hypomethylated compared to somatic tissues. However, the degree and specificity of placental hypomethylation across the genome is unclear. We assessed genome-wide methylation of the human placenta and compared it to that of the neutrophil, a representative homogeneous somatic cell. We observed global hypomethylation in placenta (relative reduction of 22%) compared to neutrophils. Placental hypomethylation was pronounced in intergenic regions and gene bodies, while the unmethylated state of the promoter remained conserved in both tissues. For every class of repeat elements, the placenta showed lower methylation but the degree of hypomethylation differed substantially between these classes. However, some retroelements, especially the evolutionarily younger Alu elements, retained high levels of placental methylation. Surprisingly, nonretrotransposon-containing sequences showed a greater degree of placental hypomethylation than retrotransposons in every genomic element (intergenic, introns, and exons) except promoters. The differentially methylated fragments (DMFs) in placenta and neutrophils were enriched in gene-poor and CpG-poor regions. The placentally hypomethylated DMFs were enriched in genomic regions that are usually inactive, whereas hypermethylated DMFs were enriched in active regions. Hypomethylation of the human placenta is not specific to retroelements, indicating that the evolutionary advantages of placental hypomethylation go beyond those provided by expression of retrotransposons and retrogenes.

Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual epigenetic variation.

The extent of variation in DNA methylation patterns in healthy individuals is not yet well documented. Identification of inter-individual epigenetic variation is important for understanding phenotypic variation and disease susceptibility. Using neutrophils from a cohort of healthy individuals, we generated base-resolution DNA methylation maps to document inter-individual epigenetic variation. We identified 12851 autosomal inter-individual variably methylated fragments (iVMFs). Gene promoters were the least variable, whereas gene body and upstream regions showed higher variation in DNA methylation. The iVMFs were relatively enriched in repetitive elements compared to non-iVMFs, and were associated with genome regulation and chromatin function elements. Further, variably methylated genes were disproportionately associated with regulation of transcription, responsive function and signal transduction pathways. Transcriptome analysis indicates that iVMF methylation at differentially expressed exons has a positive correlation and local effect on the inclusion of that exon in the mRNA transcript.