Genome-Wide DNA Methylation Analysis Identifies Novel Hypomethylated Non-Pericentromeric Genes with Potential Clinical Implications in ICF Syndrome - PubMed (original) (raw)
Genome-Wide DNA Methylation Analysis Identifies Novel Hypomethylated Non-Pericentromeric Genes with Potential Clinical Implications in ICF Syndrome
L Simo-Riudalbas et al. PLoS One. 2015.
Abstract
Introduction and results: Immunodeficiency, centromeric instability and facial anomalies syndrome (ICF) is a rare autosomal recessive disease, characterized by severe hypomethylation in pericentromeric regions of chromosomes (1, 16 and 9), marked immunodeficiency and facial anomalies. The majority of ICF patients present mutations in the DNMT3B gene, affecting the DNA methyltransferase activity of the protein. In the present study, we have used the Infinium 450K DNA methylation array to evaluate the methylation level of 450,000 CpGs in lymphoblastoid cell lines and untrasformed fibroblasts derived from ICF patients and healthy donors. Our results demonstrate that ICF-specific DNMT3B variants A603T/STP807ins and V699G/R54X cause global DNA hypomethylation compared to wild-type protein. We identified 181 novel differentially methylated positions (DMPs) including subtelomeric and intrachromosomic regions, outside the classical ICF-related pericentromeric hypomethylated positions. Interestingly, these sites were mainly located in intergenic regions and inside the CpG islands. Among the identified hypomethylated CpG-island associated genes, we confirmed the overexpression of three selected genes, BOLL, SYCP2 and NCRNA00221, in ICF compared to healthy controls, which are supposed to be expressed in germ line and silenced in somatic tissues.
Conclusions: In conclusion, this study contributes in clarifying the direct relationship between DNA methylation defect and gene expression impairment in ICF syndrome, identifying novel direct target genes of DNMT3B. A high percentage of the DMPs are located in the subtelomeric regions, indicating a specific role of DNMT3B in methylating these chromosomal sites. Therefore, we provide further evidence that hypomethylation in specific non-pericentromeric regions of chromosomes might be involved in the molecular pathogenesis of ICF syndrome. The detection of DNA hypomethylation at BOLL, SYCP2 and NCRNA00221 may pave the way for the development of specific clinical biomarkers with the aim to facilitate the identification of ICF patients.
Conflict of interest statement
Competing Interests: The authors have declared that no competing interests exist.
Figures
Fig 1. Genome-wide DNA methylation profiles in ICF patients and control samples.
(A) Histograms shows bimodal distribution pattern of DNA methylation profiles in ICF patients and normal donors. The frequency of CpGs according to DNA methylation levels are depicted in the graph. (B) Table showing number of average poorly methylated (methylation levels beta<0.33) and average highly methylated (methylation levels Beta>0.66). (C) Scatter plot represents comparison of DNA methylation levels of total CpG sites using the Infinium 450K DNA methylation assay. Green triangle selects hypomethylated area for ICF patients compared to controls. (D) Box plot displaying the distribution of Beta-values of total CpG sites of ICF versus healthy control donors. Normality was tested using the Shapiro-Wilk test and significance was evaluated with the Mann-Whitney U test and is indicated by three asterisks *** (p<0.001).
Fig 2. Identification of Differentially methylated CpGs.
(A) Unsupervised hierarchical clustering and heatmap of four cord blood donors (purple), three unrelated healthy donors (blue) and two ICF patients (orange) using 5000 random selected CpGs. DNA Methylation levels scale is shown. Each column represents patients and each row represents the different CpGs. (B) Supervised cluster and heatmap representing the distinctive 181 CpGs corresponding to the comparison between ICF patients (orange) and all control samples (dark blue).
Fig 3. Schematic representation of chromosomes and CpG localization.
Gene names and intergenic CpGs are represented and localized by blue lines.
Fig 4. Genomic distribution and gene features of the 53 differentially methylated CpGs.
(A) Chromosomal sub-localization classified in different groups: subtelomeric, pericentromeric and intrachromosomal. (B) Associated RNA transcription classified in: coding, non-coding and intergenic. (C) CpG context and neighborhood classified in: island, shore, shelf and open sea/others. (D) Functional genomic distribution classified in: promoter (TSS1500, TSS200, 5´UTR), genic (1stexon, body and 3´UTR) and intergenic.
Fig 5. Validation of DNA methylation of four representative genes (BOLL, SYCP2, LDHALD6 and NCRNA00221) levels by bisulfite genomic sequencing analysis.
Left panel depicts DNA methylation values (Beta) from ICF and healthy donors using both methodologies bisulfite genomic sequencing (BSG) and 450K array. Right panel shows bisulfite genomic sequencing analysis of genes in one representative control and ICF patient. CpG dinucleotides are shown in vertical lines. Multiple single clones are represented for each sample. Presence of unmethylated or methylated CpGs is indicated by white or black squares, respectively. Red arrows mark the localization of the differentially methylated CpGs by 450K array. The distance to transcription start site (bp) is also indicated.
Fig 6. Gene expression analysis for the selected 4 CpG island-promoter associated genes BOLL, SYCP2, LDHALD6 and NCRNA00221.
Fold change values of the differentially DNA methylated genes in lymphoblastoid ICF patients and healthy donors were evaluated by qRT-PCR. In parallel, Fold change values were also tested in untransformed fibroblast form an ICF patient and a healthy donor. Values were determined at least in triplicate. Statistic analysis was evaluated using student t test and significance symbols correspond to (* p<0.05; ** p<0.01 and *** p<0.001).
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The research leading to these results has received funding from the Cellex Foundation, Instituto de Sanidad Carlos III (ISCIII) and the Health and Science Departments of the Generalitat de Catalunya. ADL and ABC were supported by the “Sara Borrell” postdoctoral contract (CD12/00738) and (C09/00365) from the ISCIII at the Spanish Ministry of Economy and Competitiveness. MRM is supported by the Epigenomics Flagship Project EPIGEN, MIUR-CNR. ME is an ICREA Research Professor. JS is a “Miguel Servet” researcher and this work was supported by CP13/00055 ISCIII grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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