BackgroundAbnormal sex chromosome numbers in humans are observed in Turner (45,X) and Klinefelter (47,XXY) syndromes. Both syndromes are associated with several clinical phenotypes, whose molecular mechanisms are obscure, and show a range of inter-individual penetrance. In order to understand the effect of abnormal numbers of X chromosome on the methylome and its correlation to the variable clinical phenotype, we performed a genome-wide methylation analysis using MeDIP and Illumina’s Infinium assay on individuals with four karyotypes: 45,X, 46,XY, 46,XX, and 47,XXY.ResultsDNA methylation changes were widespread on all autosomal chromosomes in 45,X and in 47,XXY individuals, with Turner individuals presenting five times more affected loci. Differentially methylated CpGs, in most cases, have intermediate methylation levels and tend to occur outside CpG islands, especially in individuals with Turner syndrome. The X inactivation process appears to be less effective in Klinefelter syndrome as methylation on the X was decreased compared to normal female samples. In a large number of individuals, we verified several loci by pyrosequencing and observed only weak inter-loci correlations between the verified regions. This suggests a certain stochastic/random contribution to the methylation changes at each locus. Interestingly, methylation patterns on some PAR2 loci differ between male and Turner syndrome individuals and between female and Klinefelter syndrome individuals, which possibly contributed to this distinguished and unique autosomal methylation patterns in Turner and Klinefelter syndrome individuals.ConclusionsThe presented data clearly show that gain or loss of an X chromosome results in different epigenetic effects, which are not necessary opposite.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0112-2) contains supplementary material, which is available to authorized users.

BackgroundHypomethylation of long interspersed element (LINE)-1 has been observed in tumorigenesis when using degenerate assays, which provide an average across all repeats. However, it is unknown whether individual LINE-1 loci or different CpGs within one specific LINE-1 promoter are equally affected by methylation changes. Conceivably, studying methylation changes at specific LINE-1 may be more informative than global assays for cancer diagnostics. Therefore, with the aim of mapping methylation at individual LINE-1 loci at single-CpG resolution and exploring the diagnostic potential of individual LINE-1 locus methylation, we analyzed methylation at 11 loci by pyrosequencing, next-generation bisulfite sequencing as well as global LINE-1 methylation in bladder, colon, pancreas, prostate, and stomach cancers compared to paired normal tissues and in blood samples from some of the patients compared to healthy donors.ResultsMost (72/80) tumor samples harbored significant methylation changes at at least one locus. Notably, our data revealed not only the expected hypomethylation but also hypermethylation at some loci. Specific CpGs within the LINE-1 consensus sequence appeared preferentially hypomethylated suggesting that these could act as seeds for hypomethylation. In silico analysis revealed that these CpG sites more likely faced the histones in the nucleosome. Multivariate logistic regression analysis did not reveal a significant clinical advantage of locus-specific methylation markers over global methylation markers in distinguishing tumors from normal tissues.ConclusionsMethylation changes at individual LINE-1 loci are heterogeneous, whereas specific CpGs within the consensus sequence appear to be more prone to hypomethylation. With a broader selection of loci, locus-specific LINE-1 methylation could become a tool for tumor detection.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0051-y) contains supplementary material, which is available to authorized users.

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While our understanding of cellular and molecular processes has grown exponentially, issues related to the cell microenvironment and cellular heterogeneity have sparked a new debate concerning the cell identity. Cell composition (chromatin and nuclear architecture) poses a strong risk for dynamic changes in the diseased condition. Since chromatin accessibility patterns play a major role in human diseases, it is therefore anticipated that a deconvolution tool based on open chromatin data will provide better performance in identifying cell composition. Herein, we have designed the deconvolution tool "DeconPeaker," which can precisely define the uniqueness among subpopulations of cells using open chromatin datasets. Using this tool, we simultaneously evaluated chromatin accessibility and gene expression datasets to estimate cell types and their respective proportions in a mixture of samples. In comparison to other known deconvolution methods, we observed the lowest average root-mean-square error (RMSE = 0.042) and the highest average correlation coefficient (r = 0.919) between the prediction and "true" proportion. As a proof-of-concept, we also tested chromatin accessibility data from acute myeloid leukemia (AML) and successfully obtained unique cell types associated with AML progression. Furthermore, we showed that chromatin accessibility represents more essential characteristics in the identification of cell types than gene expression. Taken together, DeconPeaker as a powerful tool has the potential to combine different datasets (primarily, chromatin accessibility and gene expression) and define different cell types in mixtures. The Python package of DeconPeaker is now available at https://github.com/lihuamei/DeconPeaker.

Uveal melanoma (UM) is the most frequent primary intraocular tumor in Caucasian adults and is potentially fatal if metastases develop. While several prognostic genetic changes have been identified in UM, epigenetic influences are now getting closer attention. Recent technological advances have allowed to exam the human genome to a greater extent and have improved our understanding of several diseases including malignant tumors. In this context, there has been tremendous progress in the field of UM pathogenesis. Herein, we review the literature with emphasis on genetic alterations, epigenetic modifications and signaling pathways as well as possible biomarkers in UM. In addition, different research models for UM are discussed. New insights and major challenges are outlined in order to evaluate the current status for this potentially devastating disease.

The BAP1 (BRCA1-associated protein 1) gene is associated with a variety of human cancers. With its gene product being a nuclear ubiquitin carboxy-terminal hydrolase with deubiquitinase activity, BAP1 acts as a tumor suppressor gene with potential pleiotropic effects in multiple tumor types. Herein, we focused specifically on uveal melanoma (UM) in which BAP1 mutations are associated with a metastasizing phenotype and decreased survival rates. We identified the ubiquitin carboxyl hydrolase (UCH) domain as a major hotspot region for the pathogenic mutations with a high evolutionary action (EA) score. This also includes the mutations at conserved catalytic sites and the ones overlapping with the phosphorylation residues. Computational protein interaction studies revealed that distant BAP1-associated protein complexes (FOXK2, ASXL1, BARD1, BRCA1) could be directly impacted by this mutation paradigm. We also described the conformational transition related to BAP1-BRCA-BARD1 complex, which may pose critical implications for mutations, especially at the docking interfaces of these three proteins. The mutations affect - independent of being somatic or germline - the binding affinity of miRNAs embedded within the BAP1 locus, thereby altering the unique regulatory network. Apart from UM, BAP1 gene expression and survival associations were found to be predictive for the prognosis in several (n = 29) other cancer types. Herein, we suggest that although BAP1 is conceptually a driver gene in UM, it might contribute through its interaction partners and its regulatory miRNA network to various aspects of cancer. Taken together, these findings will pave the way to evaluate BAP1 in a variety of other human cancers with a shared mutational spectrum.

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Background Long interspersed nuclear elements ( LINE ‐1) sequences constitute a substantial portion of the human genome, and their methylation often correlating with global genomic methylation. Previous studies have highlighted the feasibility of using LINE ‐1 methylation to discriminate tumors from healthy tissues. However, most studies are based on only a few specific LINE ‐1 CpG sites. Methods Herein, we have performed a systematic fine‐scale analysis of methylation at 14 CpGs located in the 5′‐region of consensus LINE ‐1, in bladder, colon, prostate, and gastric tumor tissues using a global degenerate approach. Results Our results reveal variable methylation levels between different CpGs, as well as some tissue‐specific differences. Trends toward hypomethylation were observed in all tumors types to certain degrees, showing statistically significance in bladder and prostate tumors. Our data points toward the presence of unique LINE ‐1 DNA methylation patterns for each tumor type and tissue, indicating that not the same CpGs will be informative for testing in all tumor types. Conclusion This study provides an accurate guide that will help to design further assays that could avoid artifacts and explain the variability of obtained LINE ‐1 methylation values between different studies.