Genome wide analysis of acute myeloid leukemia reveal leukemia specific methylome and subtype specific hypomethylation of repeats

Methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq) has the potential to identify changes in DNA methylation important in cancer development. In order to understand the role of epigenetic modulation in the development of acute myeloid leukemia (AML) we have applied MeDIP-seq to the DNA of 12 AML patients and 4 normal bone marrows. This analysis revealed leukemia-associated differentially methylated regions that included gene promoters, gene bodies, CpG islands and CpG island shores. Two genes (SPHKAP and DPP6) with significantly methylated promoters were of interest and further analysis of their expression showed them to be repressed in AML. We also demonstrated considerable cytogenetic subtype specificity in the methylomes affecting different genomic features. Significantly distinct patterns of hypomethylation of certain interspersed repeat elements were associated with cytogenetic subtypes. The methylation patterns of members of the SINE family tightly clustered all leukemic patients with an enrichment of Alu repeats with a high CpG density (P<0.0001). We were able to demonstrate significant inverse correlation between intragenic interspersed repeat sequence methylation and gene expression with SINEs showing the strongest inverse correlation (R(2) = 0.7). We conclude that the alterations in DNA methylation that accompany the development of AML affect not only the promoters, but also the non-promoter genomic features, with significant demethylation of certain interspersed repeat DNA elements being associated with AML cytogenetic subtypes. MeDIP-seq data were validated using bisulfite pyrosequencing and the Infinium array.     

A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip? for Methylome Profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.     

Identifying differentially methylated genes using mixed effect and generalized least square models

Background  

DNA methylation plays an important role in the process of tumorigenesis. Identifying differentially methylated genes or CpG islands (CGIs) associated with genes between two tumor subtypes is thus an important biological question. The methylation status of all CGIs in the whole genome can be assayed with differential methylation hybridization (DMH) microarrays. However, patient samples or cell lines are heterogeneous, so their methylation pattern may be very different. In addition, neighboring probes at each CGI are correlated. How these factors affect the analysis of DMH data is unknown.     

Folic acid supplementation alters the DNA methylation profile and improves insulin resistance in high-fat-diet-fed mice

Folic acid (FA) supplementation may protect from obesity and insulin resistance, the effects and mechanism of FA on chronic high-fat-diet-induced obesity-related metabolic disorders are not well elucidated. We adopted a genome-wide approach to directly examine whether FA supplementation affects the DNA methylation profile of mouse adipose tissue and identify the functional consequences of these changes. Mice were fed a high-fat diet (HFD), normal diet (ND) or an HFD supplemented with folic acid (20 μg/ml in drinking water) for 10 weeks, epididymal fat was harvested, and genome-wide DNA methylation analyses were performed using methylated DNA immunoprecipitation sequencing (MeDIP-seq). Mice exposed to the HFD expanded their adipose mass, which was accompanied by a significant increase in circulating glucose and insulin levels. FA supplementation reduced the fat mass and serum glucose levels and improved insulin resistance in HFD-fed mice. MeDIP-seq revealed distribution of differentially methylated regions (DMRs) throughout the adipocyte genome, with more hypermethylated regions in HFD mice. Methylome profiling identified DMRs associated with 3787 annotated genes from HFD mice in response to FA supplementation. Pathway analyses showed novel DNA methylation changes in adipose genes associated with insulin secretion, pancreatic secretion and type 2 diabetes. The differential DNA methylation corresponded to changes in the adipose tissue gene expression of Adcy3 and Rapgef4 in mice exposed to a diet containing FA. FA supplementation improved insulin resistance, decreased the fat mass, and induced DNA methylation and gene expression changes in genes associated with obesity and insulin secretion in obese mice fed a HFD.     

Factors to preserve CpG-rich sequences in methylated CpG islands

Background

Mammalian CpG islands (CGIs) normally escape DNA methylation in all adult tissues and developmental stages. However, in our previous study we unexpectedly identified many methylated CGIs in human peripheral blood leukocytes. Methylated CpG dinucleotides convert to TpG dinucleotides through deaminization of their cytosine bases more frequently than hypomethylated CpG dinucleotides. Therefore, we wondered how methylated CGIs in germline or non-germline cells maintain their CpG-rich sequences. It is known that events such as germline hypomethylation, CpG selection, biased gene conversion (BGC), and frequent CpG fixation can contribute to the maintenance of CpG-rich sequences in methylated CGIs in germline or non-germline cells. However, it has not been investigated which of the processes maintain CpG-rich sequences of methylated CGIs in each genomic position.

Results

In this study, we comprehensively examined the contribution of the processes described above to the maintenance of CpG-rich sequences in methylated CGIs in germline and non-germline cells which were classified by genomic positions. Approximately 60–80% of CGIs with high methylation in H1 cell line (H1-HM) in all the genomic positions showed a low average CpG → TpG/CpA substitution rate. In contrast, fewer than half the numbers of CGIs with H1-HM in all the genomic positions showed a low average CpG → TpG/CpA substitution rate and low levels of methylation in sperm cells (SPM-LM). Furthermore, a small fraction of CGIs with a low average CpG → TpG/CpA substitution rate and high levels of methylation in sperm cells (SPM-HM) showed CpG selection.On the other hand, independent of the positions in genes, most CGIs with SPM-HM showed a slightly higher average TpG/CpA → CpG substitution rate compared with those with SPM-LM.

Conclusions

Relatively high numbers (approximately 60–80%) of CGIs with H1-HM in all the genomic positions preserve their CpG-rich sequences by a low CpG → TpG/CpA substitution rate caused mainly by their SPM-LM, and for those with SPM-HM partly by CpG selection and TpG/CpA → CpG fixation. BGC has little contribution to the maintenance of CpG-rich sequences of CGIs with SPM-HM which were classified by genomic positions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1286-x) contains supplementary material, which is available to authorized users.     

Development of a Novel Output Value for Quantitative Assessment in Methylated DNA Immunoprecipitation-CpG Island Microarray Analysis

In DNA methylation microarray analysis, quantitative assessment of intermediate methylation levels in samples with various global methylation levels is still difficult. Here, specifically for methylated DNA immunoprecipitation-CpG island (CGI) microarray analysis, we developed a new output value. The signal log ratio reflected the global methylation levels, but had only moderate linear correlation (r = 0.72) with the fraction of DNA molecules immunoprecipitated. By multiplying the signal log ratio using a coefficient obtained from the probability value that took account of signals in neighbouring probes, its linearity was markedly improved (r = 0.94). The new output value, Me value, reflected the global methylation level, had a strong correlation also with the fraction of methylated CpG sites obtained by bisulphite sequencing (r = 0.88), and had an accuracy of 71.8 and 83.8% in detecting completely methylated and unmethylated CGIs. Analysis of gastric cancer cell lines using the Me value showed that methylation of CGIs in promoters and gene bodies was associated with low and high, respectively, gene expression. The degree of demethylation of promoter CGIs after 5-aza-2''-deoxycytidine treatment had no association with that of induction of gene expression. The Me value was considered to be useful for analysis of intermediate methylation levels of CGIs.     

Modeling genomic data with type attributes, balancing stability and maintainability

Background

The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern.

Results

We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation.

Conclusion

Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods.     

Isolation and enrichment of human genomic CpG islands by methylation-sensitive mirror orientation selection

CpG islands (CGIs) in human genomic DNA are GC-rich fragments whose aberrant methylation is associated with human disease development. In the current study, methylation-sensitive mirror orientation selection (MS-MOS) was developed to efficiently isolate and enrich unmethylated CGIs from human genomic DNA. The unmethylated CGIs prepared by the MS-MOS procedure subsequently were used to construct a CGI library. Then the sequence characteristics of cloned inserts of the library were analyzed by bioinformatics tools, and the methylation status of CGI clones was analyzed by HpaII PCR. The results showed that the MS-MOS method could be used to isolate up to 0.001% of differentially existed unmethylated DNA fragments in two complex genomic DNA. In the CGI library, 34.1% of clones had insert sequences satisfying the minimal criteria for CGIs. Excluding duplicates, 22.0% of the 80,000 clones were unique CGI clones, representing 60% of all the predicted CGIs (about 29,000) in human genomic DNA, and most or all of the CGI clones were unmethylated in human normal cell DNA based on the HpaII PCR analysis results of randomly selected CGI clones. In conclusion, MS-MOS was an efficient way to isolate and enrich human genomic CGIs. The method has powerful potential application in the comprehensive identification of aberrantly methylated CGIs associated with human tumorigenesis to improve understanding of the epigenetic mechanisms involved.