scholarly journals A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

2021 ◽  
Author(s):  
Amy M. Inkster ◽  
Victor Yuan ◽  
Chaini Konwar ◽  
Allison M. Matthews ◽  
Carolyn J. Brown ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sex Differences ◽  
Expression Patterns ◽  
Cohort Analysis ◽  
450K Array ◽  
Term Placenta ◽  
Cpg Sites ◽  
Somatic Tissues ◽  
Sample Position ◽  
Independent Cohort

ABSTRACTBackgroundHuman placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal patterns of DNAme in the uncomplicated term placenta (n=343) using the Illumina 450K array.ResultsUsing a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex, and that replicated in an independent cohort of samples (n=293). Several of these differentially methylated CpG sites were part of larger correlated regions of differential DNAme, and many also exhibited sex-specific DNAme variability. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Interestingly, patterns of autosomal DNAme at these significantly differentially methylated CpGs organized placental samples along a continuum, rather than into discrete male and female clusters, and sample position along the continuum was significantly associated with maternal age and newborn birthweight standard deviation.ConclusionsOur results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs, and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

scholarly journals A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Amy M. Inkster ◽  
Victor Yuan ◽  
Chaini Konwar ◽  
Allison M. Matthews ◽  
Carolyn J. Brown ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sex Differences ◽  
Expression Patterns ◽  
Cohort Analysis ◽  
450K Array ◽  
Term Placenta ◽  
Cpg Sites ◽  
False Discovery ◽  
Somatic Tissues ◽  
Independent Cohort

Abstract Background Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array. Results At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females). Conclusions Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

scholarly journals DNA Methylation Landscape of 16 Canine Somatic Tissues by Methylation-Sensitive Restriction Enzyme-Based Next Generation Sequencing

2021 ◽  
Author(s):  
Jumpei Yamazaki ◽  
Yuki Matsumoto ◽  
Jaroslav Jelinek ◽  
Teita Ishizaki ◽  
Shingo Maeda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Next Generation Sequencing ◽  
Restriction Enzyme ◽  
Companion Animals ◽  
Next Generation ◽  
Cpg Sites ◽  
Somatic Tissues ◽  
Methylation Sensitive Restriction Enzyme ◽  
Generation Sequencing

Abstract Background: DNA methylation plays important functions in gene expression regulation that is involved in individual development and various diseases. DNA methylation has been well studied in human and model organisms, but only limited data exist in companion animals like dog. Results: Using methylation-sensitive restriction enzyme-based next generation sequencing (Canine DREAM), we obtained canine DNA methylation maps from 16 somatic tissues. In total, we evaluated 130,861 CpG sites. The majority of CpG sites were either highly methylated (>70%, 52.5%-64.6% of all CpG sites analyzed) or unmethylated (<30%, 22.5%-28.0% of all CpG sites analyzed) which are methylation patterns similar to other species. The overall methylation status of CpG sites across the 32 methylomes were remarkably similar. However, the tissue types were clearly defined by principle component analysis and hierarchical clustering analysis with DNA methylome. We found 6416 CpG sites located closely at promoter region of genes and inverse correlation between DNA methylation and gene expression of these genes. Conclusions: Our study provides basic dataset for DNA methylation profiles in dogs.

scholarly journals The influence of DNA methylation on monoallelic expression

2019 ◽  
Vol 63 (6) ◽  
pp. 663-676 ◽  
Author(s):  
Simão Teixeira da Rocha ◽  
Anne-Valerie Gendrel
Keyword(s):  
Dna Methylation ◽  
Expression Patterns ◽  
Monoallelic Expression ◽  
Imprinted Genes ◽  
Dependent Manner ◽  
Epigenetic Mechanisms ◽  
Cpg Sites ◽  
Mammalian Genomes ◽  
Parent Of Origin ◽  
Diploid Cells

Abstract Monoallelic gene expression occurs in diploid cells when only one of the two alleles of a gene is active. There are three main classes of genes that display monoallelic expression in mammalian genomes: (1) imprinted genes that are monoallelically expressed in a parent-of-origin dependent manner; (2) X-linked genes that undergo random X-chromosome inactivation in female cells; (3) random monoallelically expressed single and clustered genes located on autosomes. The heritability of monoallelic expression patterns during cell divisions implies that epigenetic mechanisms are involved in the cellular memory of these expression states. Among these, methylation of CpG sites on DNA is one of the best described modification to explain somatic inheritance. Here, we discuss the relevance of DNA methylation for the establishment and maintenance of monoallelic expression patterns among these three groups of genes, and how this is intrinsically linked to development and cellular states.

scholarly journals DNA methylation landscape of 16 canine somatic tissues by methylation-sensitive restriction enzyme-based next generation sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jumpei Yamazaki ◽  
Yuki Matsumoto ◽  
Jaroslav Jelinek ◽  
Teita Ishizaki ◽  
Shingo Maeda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Next Generation Sequencing ◽  
Restriction Enzyme ◽  
Companion Animals ◽  
Next Generation ◽  
Cpg Sites ◽  
Somatic Tissues ◽  
Methylation Sensitive Restriction Enzyme ◽  
Generation Sequencing

AbstractDNA methylation plays important functions in gene expression regulation that is involved in individual development and various diseases. DNA methylation has been well studied in human and model organisms, but only limited data exist in companion animals like dog. Using methylation-sensitive restriction enzyme-based next generation sequencing (Canine DREAM), we obtained canine DNA methylation maps of 16 somatic tissues from two dogs. In total, we evaluated 130,861 CpG sites. The majority of CpG sites were either highly methylated (> 70%, 52.5–64.6% of all CpG sites analyzed) or unmethylated (< 30%, 22.5–28.0% of all CpG sites analyzed) which are methylation patterns similar to other species. The overall methylation status of CpG sites across the 32 methylomes were remarkably similar. However, the tissue types were clearly defined by principle component analysis and hierarchical clustering analysis with DNA methylome. We found 6416 CpG sites located closely at promoter region of genes and inverse correlation between DNA methylation and gene expression of these genes. Our study provides basic dataset for DNA methylation profiles in dogs.

scholarly journals Correlation of Infinium HumanMethylation450K and MethylationEPIC BeadChip arrays in cartilage

2019 ◽  
Author(s):  
Kathleen Cheung ◽  
Marjolein J. Burgers ◽  
David A. Young ◽  
Simon Cockell ◽  
Louise N. Reynard
Keyword(s):  
Dna Methylation ◽  
Correlation Coefficient ◽  
Whole Blood ◽  
Pearson Correlation ◽  
Cell Types ◽  
Poor Correlation ◽  
450K Array ◽  
Human Cartilage ◽  
Cpg Sites ◽  
Cpg Site

AbstractBackgroundDNA methylation of CpG sites is commonly measured using Illumina Infinium BeadChip platforms. The Infinium MethylationEPIC array has replaced the Infinium Methylation450K array. The two arrays use the same technology, with the EPIC array assaying 865859 CpG sites, almost double the number of sites present on the 450K array. In this study, we compare DNA methylation values of shared CpGs of the same human cartilage samples assayed using both platforms.MethodsDNA methylation was measured in 21 human cartilage samples using the Illumina Infinium Methylation450K BeadChip and the Infinium methylationEPIC array. Additional matched 450K and EPIC data in whole tumour and whole blood were downloaded from GEO GSE92580 and GSE86833 respectively. Data were processed using the Bioconductor package Minfi. Additionally, DNA methylation of six CpG sites was validated for the same 21 cartilage samples by use of pyrosequencing.ResultsIn cartilage samples, overall sample correlations between methylation values generated by the two arrays were high (Pearson correlation coefficient r > 0.96). However, 50.5% of CpG sites showed poor correlation (r < 0.2) between arrays. Sites with limited variance and with either very high or very low methylation levels in cartilage exhibited lower correlation values, corroborating prior studies in whole blood. Bisulfite pyrosequencing did not highlight one array as generating more accurate methylation values that the other. For a specific CpG site, the array methylation correlation coefficient differed between cartilage, tumour and whole blood, reflecting the difference in methylation variance between cell types. These patterns can be observed across different tissues with different CpG site variances. When performing differential methylation analysis, the mean probe correlation co-efficient increased with increasing Δβ threshold used.ConclusionCpG sites with low variability within a tissue showed poor reproducibility between arrays. However, variance and thus reproducibility differs across different tissue types. Therefore, researchers should be cautious when analysing methylation of CpG sites that show low methylation variance within the cell type of interest, regardless of platform or method used to assay methylation.

scholarly journals DNA Methylation Is the Primary Silencing Mechanism for a Set of Germ Line- and Tumor-Specific Genes with a CpG-Rich Promoter

1999 ◽  
Vol 19 (11) ◽  
pp. 7327-7335 ◽  
Author(s):  
Charles De Smet ◽  
Christophe Lurquin ◽  
Bernard Lethé ◽  
Valérie Martelange ◽  
Thierry Boon
Keyword(s):  
Dna Methylation ◽  
Transcription Factors ◽  
Germ Line ◽  
Normal Tissues ◽  
Cpg Sites ◽  
Cell Clones ◽  
Somatic Tissues ◽  
Specific Antigens ◽  
Necessary And Sufficient

ABSTRACT A subset of male germ line-specific genes, theMAGE-type genes, are activated in many human tumors, where they produce tumor-specific antigens recognized by cytolytic T lymphocytes. Previous studies on gene MAGE-A1 indicated that transcription factors regulating its expression are present in all tumor cell lines whether or not they express the gene. The analysis of two CpG sites located in the promoter showed a strong correlation between expression and demethylation. It was also shown thatMAGE-A1 transcription was induced in cell cultures treated with demethylating agent 5′-aza-2′-deoxycytidine. We have now analyzed all of the CpG sites within the 5′ region of MAGE-A1 and show that for all of them, demethylation correlates with the transcription of the gene. We also show that the induction ofMAGE-A1 with 5′-aza-2′-deoxycytidine is stable and that in all the cell clones it correlates with demethylation, indicating that demethylation is necessary and sufficient to produce expression. Conversely, transfection experiments with in vitro-methylatedMAGE-A1 sequences indicated that heavy methylation suffices to stably repress the gene in cells containing the transcription factors required for expression. Most MAGE-type genes were found to have promoters with a high CpG content. Remarkably, although CpG-rich promoters are classically unmethylated in all normal tissues, those of MAGE-A1 and LAGE-1 were highly methylated in somatic tissues. In contrast, they were largely unmethylated in male germ cells. We conclude that MAGE-type genes belong to a unique subset of germ line-specific genes that use DNA methylation as a primary silencing mechanism.

scholarly journals Quantitative, genome-wide analysis of the DNA methylome in sporadic pituitary adenomas

2012 ◽  
Vol 19 (6) ◽  
pp. 805-816 ◽  
Author(s):  
Cuong V Duong ◽  
Richard D Emes ◽  
Frank Wessely ◽  
Kiren Yacqub-Usman ◽  
Richard N Clayton ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Growth Patterns ◽  
Transcript Expression ◽  
Discovery Cohort ◽  
Genome Wide Analysis ◽  
Cpg Sites ◽  
Functional Characterisation ◽  
Genome Wide ◽  
Genome Wide Survey ◽  
Independent Cohort

DNA methylation is one of the several epigenetic modifications that together with genetic aberrations are hallmarks of tumorigenesis including those emanating from the pituitary gland. In this study, we examined DNA methylation across 27 578 CpG sites spanning more than 14 000 genes in the major pituitary adenoma subtypes. Genome-wide changes were first determined in a discovery cohort comprising non-functioning (NF), growth hormone (GH), prolactin (PRL)-secreting and corticotroph (CT) adenoma relative to post-mortem pituitaries. Using stringent cut-off criteria, we validated increased methylation by pyrosequencing in 12 of 16 (75%) genes. Overall, these criteria identified 40 genes in NF, 21 in GH, six in PRL and two in CT that were differentially methylated relative to controls. In a larger independent cohort of adenomas, for genes in which hypermethylation had been validated, different frequencies of hypermethylation were apparent, where the KIAA1822 (HHIPL1) and TFAP2E genes were hypermethylated in 12 of 13 NF adenomas whereas the COL1A2 gene showed an increase in two of 13 adenomas. For genes showing differential methylation across and between adenoma subtypes, pyrosequencing confirmed these findings. In three of 12 genes investigated, an inverse relationship between methylation and transcript expression was observed where increased methylation of EML2, RHOD and HOXB1 is associated with significantly reduced transcript expression. This study provides the first genome-wide survey of adenoma, subtype-specific epigenomic changes and will prove useful for identification of biomarkers that perhaps predict or characterise growth patterns. The functional characterisation of identified genes will also provide insight of tumour aetiology and identification of new therapeutic targets.

scholarly journals DNA Methylation Network Estimation with Sparse Latent Gaussian Graphical Model

2018 ◽  
Author(s):  
Bernard Ng ◽  
Sina Jafarzadeh ◽  
Daniel Cole ◽  
Anna Goldenberg ◽  
Sara Mostafavi
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Latent Variables ◽  
Latent Class ◽  
Graphical Model ◽  
Expression Patterns ◽  
Methylation Data ◽  
Gaussian Graphical Model ◽  
Cpg Sites ◽  
Network Estimation

AbstractInferring molecular interaction networks from genomics data is important for advancing our understanding of biological processes. Whereas considerable research effort has been placed on inferring such networks from gene expression data, network estimation from DNA methylation data has received very little attention due to the substantially higher dimensionality and complications with result interpretation for non-genic regions. To combat these challenges, we propose here an approach based on sparse latent Gaussian graphical model (SLGGM). The core idea is to perform network estimation on q latent variables as opposed to d CpG sites, with q<<d. To impose a correspondence between the latent variables and genes, we use the distance between CpG sites and transcription starting sites of the genes to generate a prior on the CpG sites’ latent class membership. We evaluate this approach on synthetic data, and show on real data that the gene network estimated from DNA methylation data significantly explains gene expression patterns in unseen datasets.

scholarly journals Somatic cytochrome c (CYCS) gene expression and promoter-specific DNA methylation in a porcine model of prenatal exposure to maternal dietary protein excess and restriction

2011 ◽  
Vol 107 (6) ◽  
pp. 791-799 ◽  
Author(s):  
Simone Altmann ◽  
Eduard Murani ◽  
Manfred Schwerin ◽  
Cornelia C. Metges ◽  
Klaus Wimmers ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Porcine Model ◽  
Expression Patterns ◽  
Methylation Status ◽  
Special Focus ◽  
Cpg Sites ◽  
Low Protein ◽  
Protein Supply ◽  
The Impact

There is growing evidence that maternal nutrition during gestation has an important effect on offspring development as well as on their gene expression with long-term effects on the metabolic state. A potential mechanism forming long-lasting gene expression patterns is DNA methylation of cytosine in CpG dinucleotides within the promoter region of distinct genes. There has been special focus on mitochondrial dysfunction by prenatal malnourishment over the recent years. To this end, we investigated the gene expression of somatic cytochrome c (CYCS), an important member of the respiratory chain, in a porcine model of gestational protein over- and undersupply at 94 d post-conception and 1, 28 and 188 d of age, and analysed the association with the DNA methylation status within the CYCS promoter. Gene expression on day 1 post natum showed a significant increase in the low protein (LP) group (P = 0·0005) and a slight increase in the high protein (HP) group (P = 0·079) compared with the control (CO) group in the liver. The mean of the methylation level over forty-seven CpG sites from nucleotide (nt) − 417 to − 10 was significantly decreased in the LP (P = 0·007) and HP (P = 0·009) groups compared with that in the CO group. Excess and restricted protein supply during pregnancy led to hypomethylation of a number of CpG sites in the CYCS promoter, including those representing putative transcription factor-binding sites, associated with elevated expression levels. However, the impact of the low-protein gestation diet is more pronounced, indicating that the offspring could better adapt to excess rather than restricted protein supply.

scholarly journals Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

2021 ◽  
Author(s):  
Olivia A Grant ◽  
Yucheng Wang ◽  
Meena Kumari ◽  
Nicolae Radu Zabet ◽  
Leonard C Schalkwyk
Keyword(s):  
Dna Methylation ◽  
Sex Differences ◽  
Whole Blood ◽  
Cpg Islands ◽  
Disease Etiology ◽  
Cpg Sites ◽  
Males And Females ◽  
Methylation Patterns ◽  
First Time ◽  
Epic Array

Sex differences are known to play a role in disease etiology, progression and outcome. Previous studies have revealed autosomal epigenetic differences between males and females in some tissues, including differences in DNA methylation patterns. Here, we report for the first time an analysis of autosomal sex differences in DNAme using the Illumina EPIC array in human whole blood (n=1171). We identified 554 sex-associated differentially methylated CpG sites (saDMPs) with the majority found to be hypermethylated in females (70%). These saDMP's are enriched in CpG islands and CpG shores and located preferentially at 5'UTRs, 3'UTRs and enhancers. Additionally, we identified 311 significant sex associated differentially methylated regions (saDMRs). Transcription factor binding site enrichment revealed enrichment of transcription factors related to critical developmental processes and sex determination such as SRY and SOX9. Our study reports a reliable catalogue of sex associated CpG sites and elucidates several characteristics of these sites.

Sign in / Sign up

Export Citation Format

Share Document