Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA171224 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR526927.fastq.gz | Fastqsanger.gz | |||
| SRR526928.fastq.gz | Fastqsanger.gz | |||
| SRR526929.fastq.gz | Fastqsanger.gz | |||
| SRR526930.fastq.gz | Fastqsanger.gz | |||
| SRR526931.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 18 |
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Project description:Purpose: We characterized genome-wide DNA methylation profiles (methylome) in purified peripheral blood monocytes (PBMs) from 18 healthy postmenopausal Caucasian females aged 50-56 years. Methods: DNA methylome of Human Peripheral Blood Monocytes were generated by methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq), using Illumina GAIIx. The sequence reads that passed quality filters were analyzed using MEDIPS package. Targeted methylation validation analysis was performed by using MassARRAY EpiTYPER assays. Genome-wide gene expression profiles have been obtained for 7 of the 18 subjects by using Affymetrix 1.0 Human Exon ST arrays following the manufacturer's recommended protocols. Results: Using MeDIP-seq,a total of approximately 283 million reads were uniquely aligned to human genome (Build NCBI37, HG19), resulting in average ~16 million uniquely aligned high quality reads per sample. Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. We found that approximately 24% CpG islands (CGIs) were highly methylated in PBMs. Further characterization of CGIs with respect to their relative locations to RefSeq genes revealed that the highly methylated CGIs were largely enriched (~89%) in CGIs located in gene bodies and intergenic regions. By integration of the methylome data with genome-wide PBM gene expression data, we found negative correlation between promoter methylation levels and gene transcription levels when comparing groups of genes with different expression levels, and this relationship was consistently observed across promoters with high to low CpG densities. Furthermore, we observed a modest but significant excess (permutation p<0.0001) of genes showing negative correlation between inter-individual promoter methylation and transcription levels, particularly for genes associated with CpG-rich promoters. Across the 18 individual PBM methylomes, we also identified genomic regions that were constitutively highly methylated in PBMs as well as regions showing large inter-individual variability. Conclusions: This study represents a comprehensive analysis of the PBM methylome and our data provides a valuable resource for future epigenomic and multi-omic studies exploring biological and disease-related regulatory mechanisms in PBMs. DNA methylome of human peripheral blood monocytes were generated by MeDIP-seq, using Illumina GAIIx.
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