CpG context and content in evolutionary signatures of brain DNA methylation
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE32647 | GEO | 2011/10/05
SECONDARY ACCESSION(S): PRJNA146955
REPOSITORIES: GEO
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Project description:We assayed CpG methylation in cerebral cortex of neurologically and psychiatrically normal human postmortem specimens, as well as mouse forebrain specimens. Cross-species human-mouse DNA methylation conservation analysis shows that DNA methylation is not correlated with sequence conservation. Instead, greater DNA methylation conservation is correlated with increasing CpG density. We identified key genomic features that can be targeted for identification of epigenetic loci that may be developmentally and evolutionarily conserved and wherein aberrations in DNA methylation patterns can confer risk for disease. Characterization of evolutionary signatures of DNA methylation in the brain
2011-10-04 | E-GEOD-32647 | biostudies-arrayexpress
Project description:BACKGROUND: In previous studies using candidate gene approaches, low sperm count (oligospermia) has been associated with altered sperm mRNA content and DNA methylation in both imprinted and non-imprinted genes. We performed a genome-wide analysis of sperm DNA methylation and mRNA content to test for associations with sperm function. METHODS AND RESULTS: Sperm DNA and mRNA were isolated from 21 men with a range of semen parameters presenting to a tertiary male reproductive health clinic. DNA methylation was measured with the Illumina Infinium array at 27,000 CpG loci. Unsupervised clustering of methylation data differentiated the 21 sperm samples by their motility values. Recursively partitioned mixture modeling (RPMM) of methylation data resulted in four distinct methylation profiles that were significantly associated with sperm motility (P=0.01). Linear models of microarray analysis (LIMMA) was performed based on motility and identified 9,189 CpG loci with significantly altered methylation (Q<0.05) in the low motility samples, with many loci located in genes associated with subfertility and epigenetic regulation. In the low motility samples, the majority of disrupted CpG loci (80%) were hypomethylated. Of the aberrantly methylated CpGs, 194 were associated with imprinted genes almost equally distributed into hypermethylated (predominantly paternally expressed) and hypomethylated (predominantly maternally expressed) groups. Sperm mRNA was measured with the Human Gene 1.0 ST Affymetrix GeneChip Array. LIMMA analysis based on motility identified 20 candidate transcripts as differentially expressed in low motility sperm, including HDAC1 (NCBI 3065), SIRT3 (NCBI 23410), and DNMT3A (NCBI 1788). Altered expression of these epigenetic regulatory genes was associated with RPMM DNA methylation class. CONCLUSIONS: Using integrative genome-wide approaches to study epigenetic and gene expression patterns in human sperm we identified CpG methylation profiles and mRNA alterations associated with low sperm motility, and that low motility sperm may have aberrant genome-wide hypomethylation due to excess HDAC1 activity. See "summary" above
2011-06-02 | E-GEOD-26881 | biostudies-arrayexpress
Project description:BACKGROUND: In previous studies using candidate gene approaches, low sperm count (oligospermia) has been associated with altered sperm mRNA content and DNA methylation in both imprinted and non-imprinted genes. We performed a genome-wide analysis of sperm DNA methylation and mRNA content to test for associations with sperm function. METHODS AND RESULTS: Sperm DNA and mRNA were isolated from 21 men with a range of semen parameters presenting to a tertiary male reproductive health clinic. DNA methylation was measured with the Illumina Infinium array at 27,000 CpG loci. Unsupervised clustering of methylation data differentiated the 21 sperm samples by their motility values. Recursively partitioned mixture modeling (RPMM) of methylation data resulted in four distinct methylation profiles that were significantly associated with sperm motility (P=0.01). Linear models of microarray analysis (LIMMA) was performed based on motility and identified 9,189 CpG loci with significantly altered methylation (Q<0.05) in the low motility samples, with many loci located in genes associated with subfertility and epigenetic regulation. In the low motility samples, the majority of disrupted CpG loci (80%) were hypomethylated. Of the aberrantly methylated CpGs, 194 were associated with imprinted genes almost equally distributed into hypermethylated (predominantly paternally expressed) and hypomethylated (predominantly maternally expressed) groups. Sperm mRNA was measured with the Human Gene 1.0 ST Affymetrix GeneChip Array. LIMMA analysis based on motility identified 20 candidate transcripts as differentially expressed in low motility sperm, including HDAC1 (NCBI 3065), SIRT3 (NCBI 23410), and DNMT3A (NCBI 1788). Altered expression of these epigenetic regulatory genes was associated with RPMM DNA methylation class. CONCLUSIONS: Using integrative genome-wide approaches to study epigenetic and gene expression patterns in human sperm we identified CpG methylation profiles and mRNA alterations associated with low sperm motility, and that low motility sperm may have aberrant genome-wide hypomethylation due to excess HDAC1 activity.
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Project description:DNA methylation plays an important role in development and disease. The primary sites of DNA methylation in vertebrates are cytosines in the CpG dinucleotide context, which account for roughly three quarters of the total DNA methylation content in human and mouse cells. While the genomic distribution, inter-individual stability and functional role of CpG methylation are reasonably well understood, little is known about DNA methylation targeting CpA, CpC and CpT dinucleotides. Here we report a comprehensive analysis of non-CG methylation in 72 genome-scale DNA methylation maps across human pluripotent and differentiated cell types. We confirm non-CG methylation to be predominant in pluripotent cell types and observe an expected decrease upon differentiation and near complete absence in various differentiated cells. Our data highlight that non-CG methylation is highly variable and shows little conservation between different pluripotent cell lines. While we show a strong correlation of non-CG methylation and DNMT3 expression levels we find a statistical independence of non-CG methylation from pluripotency associated gene expression. Finally, non-CG methylation appears to be spatially correlated with CpG methylation. In summary these results contribute further to our understanding of DNA methylation in human cells and help clarify previous observations using a large representative sample set.
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Project description:DNA methylation profiling of cancer and control samples. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across 1,505 CpG sites CpGs distributed across 807 genes in blood DNA specimens. DNA samples were extracted from blood specimens, bisulfite treated and subsequently used for GoldenGate Methylation Cancer Panel I Array (Illumina) according to manufacturer’s protocol together with normalization methylated, hemimethylated and unmethylated DNA controls (Qiagen).
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