scholarly journals High Resolution Genome Wide DNA Methylation Analysis in a Large Trial Group Reveals a Novel Epigenetically Defined Subgroup of Myeloma Patients Characterized By Developmental Gene Hypermethylation

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2189-2189
Author(s):  
Martin F Kaiser ◽  
Alexander Murison ◽  
Charlotte Pawlyn ◽  
Eileen M Boyle ◽  
David C Johnson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Resolution ◽  
Methylation Pattern ◽  
Gene Set Enrichment Analysis ◽  
Epigenetic Changes ◽  
Dna Hypomethylation ◽  
Dna Hypermethylation ◽  
Epigenetic Programming ◽  
Genome Wide ◽  
Dna Methylation Pattern

Abstract Introduction Multiple myeloma is a clinically highly heterogeneous disease, which is reflected by both a complex genome and epigenome. Dynamic epigenetic changes are involved at several stages of myeloma biology, such as transformation and disease progression. Our previous genome wide epigenetic analyses identified prognostically relevant DNA hypermethylation at specific tumor suppressor genes (Kaiser MF et al., Blood 2013), indicating that specific epigenetic programming influences clinical behavior. This clinically relevant finding prompted further investigation of the epigenomic structure of myeloma and its interaction with genetic aberrations. Material and Methods Genome wide DNA methylation of CD138-purified myeloma cells from 464 patients enrolled in the NCRI Myeloma XI trial at presentation were analyzed using the high resolution 450k DNA methylation array platform (Illumina). In addition, 4 plasma cell leukemia (PCL) cases (two t(11;14) and two (4;14)) and 7 myeloma cell lines (HMCL) carrying different translocations were analysed. Analyses were performed in R Bioconductor packages after filtering and removal of low quality and non-uniquely mapping probes. Results Variation in genome wide DNA methylation was analyzed using unsupervised hierarchical clustering of the 10,000 most variable probes, which revealed epigenetically defined subgroups of disease. Presence of recurrent IGH translocations was strongly associated with specific epigenetic profiles. All 60 cases with t(4;14) clustered into two highly similar sub-clusters, confirming that overexpression of the H3K36 methyltransferase MMSET in t(4;14) has a defined and specific effect on the myeloma epigenome. Interestingly, HMCLs KMS-11 and LP-1, which carry t(4;14), MM1.S, a t(14;16) cell line with an E1099K MMSET activating mutation as well as two PCLs with t(4;14) all clustered in one sub-clade. The majority (59/85) of t(11;14) cases showed global DNA hypomethylation compared to t(4;14) cases and clustered in one subclade, indicating a epigenetic programming effect associated with CCND1, with a subgroup of t(11;14) cases showing a variable DNA methylation pattern. In addition to translocation-defined subgroups, a small cluster of samples with a distinct epigenetic profile was identified. In total 7 cases with a shared specific DNA methylation pattern (median inter-sample correlation 0.4) were identified. The group was characterized by DNA hypermethylation (4,341 hypermethylated regions vs. 750 hypomethylated regions) in comparison to all other cases. Intersection of regions hypermethylated in this subgroups with ENCODE datasets revealed mapping to poised enhancers and promoters in H1-hESC, indicating functionally relevant epigenetic changes. Gene set enrichment analysis (KEGG) demonstrated enrichment of developmental pathway genes, e.g. Hedgehog signaling (adj p=5x10exp-13), amongst others and all four HOX clusters were differentially methylated in this group. Of note, three of seven cases in this subgroup carried a t(11;14) and all t(11;14) or t(11;14)-like HMCLs clustered closely together with these patient cases, but not with the cluster carrying the majority of t(11;14) myeloma or t(11;14) PCLs. This potentially indicates that t(11;14) HMCL could be derived from a subgroup of patients with specific epigenetic characteristics. Conclusion Our results indicate that the recurrent IGH translocations are fundamentally involved in shaping the myeloma epigenome through either direct upregulation of epigenetic modifiers (e.g. MMSET) or through insufficiently understood mechanisms. However, developmental epigenetic processes seem to independently contribute to the complexity of the epigenome in some cases. This work provides important insights into the spectrum of epigenetic subgroups of myeloma and helps identify subgroups of disease that may benefit from specific epigenetic therapies currently being developed. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

scholarly journals DNA methylation and expression analyses reveal epialleles for the foliar disease resistance genes in peanut (Arachis hypogaea L.)

2019 ◽  
Author(s):  
Ramesh S. Bhat ◽  
J. Rockey ◽  
Kenta Shirasawa ◽  
I. S. Tilak ◽  
M. P. Brijesh Patil ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Methylation Pattern ◽  
Chromosome 17 ◽  
Foliar Disease ◽  
Genome Wide ◽  
Arachis Hypogaea L ◽  
Dna Sequence Polymorphism ◽  
Dna Methylation Pattern ◽  
Resistant Genotypes

Abstract Objective Low DNA sequence polymorphism despite enormous phenotypic variations in peanut indicates the possible role of epigenetic variations. An attempt was made to analyze genome-wide DNA methylation pattern and its influence on gene expression across 11 diverse genotypes of peanut. Results The genotypes were subjected to bisulfite sequencing after 21 days of sowing (DAS). CHG regions showed the highest (3,05,37,376) of DNA methylation followed by CpG (3,03,56,066) and CHH (1,59,93,361) across 11 genotypes. The B sub-genome exhibited higher DNA methylation sites (4,62,94,063) than the A sub-genome (3,04,15,166). Overall, the DNA methylation was more frequent in inter-genic regions than in the genic regions. A few genes showed altered methylation and expression between the parent and its EMS-derived mutant. Foliar disease resistant genotypes showed significant differential DNA methylation at 766 sites corresponding to 25 genes. Of them, two genes (Arahy.1XYC2X on chromosome 01 and Arahy.00Z2SH on chromosome 17) coding for senescence-associated protein showed differential expression with resistant genotypes recording higher fragments per kilobase of transcript per million mapped reads (FPKM). Overall, the study indicated the variation in the DNA methylation pattern among the diverse genotypes of peanut and its influence of gene expression, indicating the application of these epialleles in peanut breeding.

Evaluation of selected genes’ methylation in nonfunctioning pituitary adenomas – verification of literature report

2017 ◽  
Vol 5 ◽  
pp. 37-44
Author(s):  
Paulina Kober ◽  
Mateusz Bujko ◽  
Krzysztof Goryca ◽  
Maria Maksymowicz ◽  
Jacek Kunicki ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Pituitary Adenomas ◽  
Methylation Status ◽  
Methylation Pattern ◽  
Published Data ◽  
Dna Hypermethylation ◽  
Literature Report ◽  
Regulatory Regions ◽  
Nonfunctioning Pituitary Adenomas ◽  
Dna Methylation Pattern

Pituitary adenomas are among the most common intracranial tumors. Previous studies have shown that epigenetic disorders, i.e. abnormal DNA methylation pattern within regulatory regions of specific genes play an important role in the pathogenesis of nonfunctioning pituitary adenomas (NFPA).In this article, using data from DNA methylation profiling with Infinium HumanMethylation450 (Illumina) microarray technology, we analyzed the DNA methylation pattern in the regulatory regions of se-lected 16 genes, in which, according to previously published results, abnormal methylation of DNA is present in adenomas.The differences in DNA methylation between pituitary adenoma and normal pituitary and the frequency of increased DNA methylation in individual regions were assessed based on experimental data for 41 patients and 6 normal tissue sections.In case of 7 out of 16 analyzed genes, significantly higher levels of DNA methylation were detected in NFPA: LGALS3, MMP14, NDRG2, RASSF1A, THBS1, TIMP3 and TP73. Our results confirm also the frequent occurrence of DNA hypermethylation in these genes in patients. The greatest discrepancies between our results and previously published data concern the methylation status of CDH1, GADD45G, GSTP1and P16 genes. The obtained results show, unlike in the available literature, that the promoter methylation of these genes occurs only in a small proportion of the NFPA patients. The possible causes of these discrepancies were discussed, with particular emphasis on the differences in laboratory techniques that can determine the quality and reliability of DNA methylation assays.

scholarly journals A model for the aberrant DNA methylomes in aging cells and cancer cells

2019 ◽  
Vol 47 (4) ◽  
pp. 997-1003 ◽  
Author(s):  
Huiming Zhang ◽  
Kang Zhang ◽  
Jian-Kang Zhu
Keyword(s):  
Dna Methylation ◽  
Cancer Cells ◽  
Developmental Stages ◽  
Methylation Pattern ◽  
Epigenetic Mark ◽  
Dna Hypomethylation ◽  
Genome Wide ◽  
Abnormal Cells ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract DNA methylation at the fifth position of cytosine is a major epigenetic mark conserved in plants and mammals. Genome-wide DNA methylation patterns are dynamically controlled by integrated activities of establishment, maintenance, and removal. In both plants and mammals, a pattern of global DNA hypomethylation coupled with increased methylation levels at some specific genomic regions arises at specific developmental stages and in certain abnormal cells, such as mammalian aging cells and cancer cells as well as some plant epigenetic mutants. Here we provide an overview of this distinct DNA methylation pattern in mammals and plants, and propose that a methylstat, which is a cis-element responsive to both DNA methylation and active demethylation activities and controlling the transcriptional activity of a key DNA methylation regulator, can help to explain the enigmatic DNA methylation patterns in aging cells and cancer cells.

scholarly journals DNA methylation and expression analyses reveal epialleles for the foliar disease resistance genes in peanut (Arachis hypogaea L.)

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
R. S. Bhat ◽  
J. Rockey ◽  
Kenta Shirasawa ◽  
I. S. Tilak ◽  
M. P. Brijesh Patil ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Methylation Pattern ◽  
Chromosome 17 ◽  
Foliar Disease ◽  
Genome Wide ◽  
Arachis Hypogaea L ◽  
Dna Sequence Polymorphism ◽  
Dna Methylation Pattern ◽  
Resistant Genotypes

Abstract Objective Low DNA sequence polymorphism despite enormous phenotypic variations in peanut indicates the possible role of epigenetic variations. An attempt was made to analyze genome-wide DNA methylation pattern and its influence on gene expression across 11 diverse genotypes of peanut. Results The genotypes were subjected to bisulfite sequencing after 21 days of sowing (DAS). CHG regions showed the highest (30,537,376) DNA methylation followed by CpG (30,356,066) and CHH (15,993,361) across 11 genotypes. The B sub-genome exhibited higher DNA methylation sites (46,294,063) than the A sub-genome (30,415,166). Overall, the DNA methylation was more frequent in inter-genic regions than in the genic regions. The genes showing altered methylation and expression between the parent (TMV 2) and its EMS-derived mutant (TMV 2-NLM) were identified. Foliar disease resistant genotypes showed significant differential DNA methylation at 766 sites corresponding to 25 genes. Of them, two genes (Arahy.1XYC2X on chromosome 01 and Arahy.00Z2SH on chromosome 17) coding for senescence-associated protein showed differential expression with resistant genotypes recording higher fragments per kilobase of transcript per million mapped reads (FPKM) at their epialleles. Overall, the study indicated the variation in the DNA methylation pattern among the diverse genotypes of peanut and its influence of gene expression.

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