Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Methylome analysis reveals alterations in DNA methylation in the regulatory regions of left ventricle development genes in human dilated cardiomyopathy

ABSTRACT: This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

ORGANISM(S): Homo sapiens

SUBMITTER: Bong-seok Jo

PROVIDER: E-GEOD-81339 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Methylome analysis reveals alterations in DNA methylation in the regulatory regions of left ventricle development genes in human dilated cardiomyopathy.

Jo Bong-Seok BS Koh In-Uk IU Bae Jae-Bum JB Yu Ho-Yeong HY Jeon Eun-Seok ES Lee Hae-Young HY Kim Jae-Joong JJ Choi Murim M Choi Sun Shim SS

Genomics 20160712 2

Dilated cardiomyopathy (DCM) is one of the main causes of heart failure (called cardiomyopathies) in adults. Alterations in epigenetic regulation (i.e., DNA methylation) have been implicated in the development of DCM. Here, we identified a total of 1828 differentially methylated probes (DMPs) using the Infinium 450K HumanMethylation Bead chip by comparing the methylomes between 18 left ventricles and 9 right ventricles. Alterations in DNA methylation levels were observed mainly in lowly methylat ...[more]

PMID: 27417303

Similar Datasets

Project description:Background: Germ Cell Cancers (GCC), originating from Primordial Germ Cells /gonocytes, are the most common cancer in young men, subdivided in seminoma (SE) and non-seminoma (NS, stem cell component: embryonal carcinoma (EC)). Somatic mutations are rarely found in GCC. It has been proposed that disruption of the epigenetic constitution, either primarily or secondary (e.g. environmental influences), is involved in cancer, and specifically in GCC. Results: This study aims at identifying epigenetic footprints of SE and EC cell lines in genome-wide profiles by studying the interaction between gene expression, DNA CpG methylation and histone modifications, and their function in GCC and related disruption of germ cell maturation. Two well characterized GCC-derived cell lines were compared, one representative for SE (TCam-2) and the other for EC (NCCIT). Data was acquired using the Illumina HumanHT-12-v4 (gene expression) and HumanMethylation450 BeadChip (methylation) microarrays as well as ChIP sequencing (activating histone modifications (H3K4me3, H3K27ac)). The data show that known germ cell markers are not only present and differentiating between SE and NS at the expression level, but also in the epigenetic landscape. Conclusion: The overall similarity between TCam-2 / NCCIT supports an erased embryonic gem cell arrested in early gonadal development as common origin. Subtle difference in the (integrated) epigenetic and expression profiles indicated TCam-2 to exhibit a more germ cell like profile (enrichment Androgen regulation) while NCCIT proved more pluripotent. The results provide insight into an integrated analysis of the functional genome in GCC cell lines. Two wildtype germ cell cancer (type II germ cell tumor) cell lines were analyzed. TCam-2 (representative for the seminomatous subtype of germ cell cancer) , [1, 2]) and NCCIT (representative of the non-seminomatous (embryonal carcinoma) subtype of germ cell cancer, [3]). 1. Mizuno, Y., et al., [Establishment and characterization of a new human testicular germ cell tumor cell line (TCam-2)]. Nihon Hinyokika Gakkai Zasshi, 1993. 84(7): p. 1211-8. 2. de Jong, J., et al., Further characterization of the first seminoma cell line TCam-2. Genes Chromosomes Cancer, 2008. 47(3): p. 185-96. 3. Teshima, S., et al., Four new human germ cell tumor cell lines. Lab Invest, 1988. 59(3): p. 328-36.

Project description:Germ cell tumors (GCT) originate from germ cells at different developmental stages (GCT type I – V) They are thought to inherit their methylation profile from (early embryonic) germ cells which undergo a characteristic epigenetic “reset” during maturation. This study aims to provide insight into the developmental timing and underlying biology of the various subtypes of GCTs and their (embryonic) cells of origin by identifying specific and global methylation differences between GCT subtypes. In total, 91 type I-IV GCTs and four cell lines were profiled using the Illumina HumanMethylation450 BeadChip (450K) platform. The data were pre-processed using a validated pipeline and analyzed using an in-house generated extension of the annotation manifest. Marked methylation differences were identified between GCT subtypes both on the global and local level (i.e. differentially methylated regions, imprinting control regions, promoters, etc). GCT subtypes indeed show major similarities to specific stages of (early) developing embryonic germ cells with regard to their methylation profile. The extended annotation manifest for the Illumina 450K platform and methylation datasets are readily available on GEO (GEO accession: GSE58538, GPL18809), providing an integrated hypothesis generating data source for future research. 91 germ cell tumors of various histologies were investigated for their methylation profile. Methylation detection was performed using Illumina’s HumanMethylation450 BeadChip. 14 type I teratomas (TE) were included of which 6 were located sacral (3 male: I.TE.s.m; 3 female: I.TE.s.f), 4 were located in the testis (I.TE.t) and 3 were located in the ovary (I.TE.o). 30 pure embryonal carcinomas (EC) were included as well as 21 mixed non seminomas (mNS). 12 seminomas of the testis (SE) were included as well as 4 dysgerminomas (their couterpart in the ovary). Finally, 4 spermatocytic seminomas (SS) and three dermoid cysts were analyzed. For a detailed overview the histological classification of germ cell tumors please see the publication linked to this data or associated literature [1-3]. Four cell lines were included, al modelling type II GCTs. Cell lines derived from EC include NT2[4-8], NCCIT [5, 9] and 2102EP[4-8]. TCam-2 closely resembles SE [10-12]. 1. Oosterhuis, J.W. and L.H. Looijenga, Testicular germ-cell tumours in a broader perspective. Nat Rev Cancer, 2005. 5(3): p. 210-22. 2. Looijenga, L.H., Human testicular (non)seminomatous germ cell tumours: the clinical implications of recent pathobiological insights. J Pathol, 2009. 218(2): p. 146-62. 3. Woodward, P.J., et al., Testicular germ cell tumors, in World Health Organization Classification of Tumours Pathology and Genetics of the Urinary System and Male Genital Organs., J.N. Eble, et al., Editors. 2004, IARC Press: Lyon. p. 17-278. 4. Andrews, P.W., et al., A comparative study of eight cell lines derived from human testicular teratocarcinoma. Int J Cancer, 1980. 26(3): p. 269-80. 5. Andrews, P.W., et al., Comparative analysis of cell surface antigens expressed by cell lines derived from human germ cell tumours. Int J Cancer, 1996. 66(6): p. 806-16. 6. Wang, N., et al., Nonrandom abnormalities in chromosome 1 in human testicular cancers. Cancer Res, 1980. 40(3): p. 796-802. 7. Fogh, J. and G. Trempe, New Human Tumor Cell Lines, in Human Tumor Cells in Vitro, J. Fogh, Editor. 1975, Springer US. p. 115-159. 8. Fogh, J., Cultivation, characterization, and identification of human tumor cells with emphasis on kidney, testis, and bladder tumors. Natl Cancer Inst Monogr, 1978(49): p. 5-9. 9. Teshima, S., et al., Four new human germ cell tumor cell lines. Lab Invest, 1988. 59(3): p. 328-36. 10. Eckert, D., et al., TCam-2 but not JKT-1 cells resemble seminoma in cell culture. Cell Tissue Res, 2008. 331(2): p. 529-38. 11. de Jong, J., et al., Further characterization of the first seminoma cell line TCam-2. Genes Chromosomes Cancer, 2008. 47(3): p. 185-96. 12. Mizuno, Y., et al., [Establishment and characterization of a new human testicular germ cell tumor cell line (TCam-2)]. Nihon Hinyokika Gakkai Zasshi, 1993. 84(7): p. 1211-8.

Project description:Abstract The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina Human Methylation 450k BeadChip is widely used to quantify DNA methylation, nevertheless the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate datasets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished datasets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. We evaluated the performance of different analysis pipelines and demonstrated that a) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; b) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); c) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive dataset suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450k arrays. DNA samples from peripheral blood or CD14+ monocytes were included in the study. DNA methylation levels were profiled using Illumina 450K arrays. Specifically, 50 biological sample replicates from PB and 36 biological sample replicates from monocytes were randomly assigned to 8 BeadChips with technical replicates and processed in one run (a total of 96 DNA samples). Eight samples were technically replicated in pairs, while one sample was represented in a trio of replicates. Different analysis pipelines were compared, however, the file uploaded refers to the best scored. In our publication we used this one to make all analyses and conclusions.

Dataset Information

Methylome analysis reveals alterations in DNA methylation in the regulatory regions of left ventricle development genes in human dilated cardiomyopathy

Publications

Methylome analysis reveals alterations in DNA methylation in the regulatory regions of left ventricle development genes in human dilated cardiomyopathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets