Methylation profiling by array of human cell line HCT116 after treatment with demethylating drugs azacytidine or decitabine.
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER:
PROVIDER: E-MTAB-210 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Array-based analysis of genome-wide DNA methylation changes induced by the demethylating drugs azacytidine and decitabine on HCT116 and HL60 cells for 24 hours
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Project description:The Human leukocyte antigen (HLA) -region, especially HLA class I and II genes, plays a major role in the predisposition to autoimmune disorders. Particularly three HLA haplotypes, DRB1*03-DQA1*05-DQB1*02 (DR3-DQ2), DRB1*04:01-DQA1*03-DQB1*03:02 (DR4-DQ8) and DRB1*15-DQA1*01-DQB1*06:02 (DR2-DQ6), have an important role in many autoimmune diseases: for example, in type 1 diabetes (T1D) the DR2-DQ6 is associated with a strongly decreased T1D risk and the DR3-DQ2 and DR4-DQ8 are associated with a moderately increased T1D risk. To clarify the mechanisms behind this association, we examined genome-wide DNA methylation in CD4+ T cells and CD19+ B cells of healthy subjects homozygous either for DR3-DQ2 (n = 19), DR4-DQ8 (n = 17) or DR2-DQ6 (n = 14), and compared methylation between the genotypes. For the study, CD4+ T cells and CD19+ B cells were isolated consecutively from PBMC samples using magnetic bead separation. DNA was extracted from the cell lysates with AllPrep DNA/RNA/miRNA Universal Kit (Qiagen, Germany). Then the individual DNA samples were pooled into 11 pooled samples with 4–5 samples per pooled sample. The original 50 samples were designated pools based on age and sex to ensure that the age and sex distributions would be as similar as possible between the pooled samples. The mean age (±SD) in the three HLA-groups (DR2-DQ6, DR3-DQ2 and DR4-DQ8) were 15.0 (±8.3), 11.1 (±5.6) and 11.8 (±7.9) and their male to female ratios were 8/6, 9/10 and 11/6. Similar pooled samples were created for both the CD4+ T cell and the CD19+ B cell samples. Then DNA methylation was examined in the pooled CD4+ T cell and CD19+ B cell samples using Illumina Infinium HumanMethylation EPIC beadchip.
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Project description:Epigenetic methyl-CpG silencing of the ribosomal RNA (rRNA) genes is thought to down-regulate rRNA synthesis in mammals. In contrast, we now show that CpG methylation in fact positively influences rRNA synthesis and processing. Human HCT116 cells, inactivated for DNMT1 and DNMT3b or treated with aza-dC, lack CpG methylation and reactivate a large fraction of normally silent rRNA genes. Unexpectedly, these cells display reduced rRNA synthesis and processing, and accumulate unprocessed 45S rRNA. Reactivation of the rRNA genes is associated with their cryptic transcription by RNA polymerase II. Ectopic expression of cryptic rRNA gene transcripts recapitulates the defects associated with loss of CpG methylation. The data demonstrate that rRNA gene silencing prevents cryptic RNA polymerase II transcription of these genes. Lack of silencing leads to the partial disruption of rRNA synthesis and rRNA processing, providing an unexpected explanation for the cytotoxic effects of loss of CpG methylation. Agilent custom microarray analyses of transcripts from sense and antisense strands of the human rRNA genes present in total nuclear RNA from HCT116-DNMT1-/-;DNMT3b-/- (DKO) and HCT116 (PS) cells. The DKO/PS RNA ratio was normalized within the 5â region of the 45S ribosomal RNA, since this sense coding region was found by quantitative Northern and S1-mapping analyses to equally present in the RNA pools from both cells (as compared to total RNA levels and 18S and 28S levels). The distribution for sense RNAs from the coding region is strongly influenced by the predominant RPI 45S rRNA transcript and hence peaks at 0, the DKO and PS 45S rRNA signals having been normalized. 60-mer probes were designed to tile Human rDNA (GenBank accession U13369) on both strands using ArrayOligoSelector (Wardle et al., 2006). A total of 1,146 different non-overlapping probes (573 for each DNA strand) were designed to cover the 43 kb of human rDNA and each printed in triplicate on the array. The experiment was performed using a dye-swap duplicate analysis. The microarrays were scanned on a G2565CA DNA microarray scanner (Agilent Technologies) and the quantification performed using the Feature Extraction software (Agilent technologies). The data were analyzed using the LIMMA software package in R (Smyth and Speed, 2003).
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