Trans-chromosomal methylation

The epigenome plays a vital role in helping to maintain and regulate cell functions in all organisms. Alleles with differing epigenetic marks in the same nucleus do not function in isolation but can interact in trans to modify the epigenetic state of one or both alleles. This is particularly evident when two divergent epigenomes come together in a hybrid resulting in thousands of alterations to the methylome. These changes mainly involve the methylation patterns at one allele being changed to resemble the methylation patterns of the other allele, in processes we have termed trans-chromosomal methylation (TCM) and trans-chromosomal demethylation (TCdM). These processes are primarily modulated by siRNAs and the RNA directed DNA methylation pathway. Drawing from other examples of trans-allelic interactions, we describe the process of TCM and TCdM and the effect such changes can have on genome activity. Trans-allelic epigenetic interactions may be a common occurrence in many biological systems.     

Trans-chromosomal methylation

The epigenome plays a vital role in helping to maintain and regulate cell functions in all organisms. Alleles with differing epigenetic marks in the same nucleus do not function in isolation but can interact in trans to modify the epigenetic state of one or both alleles. This is particularly evident when two divergent epigenomes come together in a hybrid resulting in thousands of alterations to the methylome. These changes mainly involve the methylation patterns at one allele being changed to resemble the methylation patterns of the other allele, in processes we have termed trans-chromosomal methylation (TCM) and trans-chromosomal demethylation (TCdM). These processes are primarily modulated by siRNAs and the RNA directed DNA methylation pathway. Drawing from other examples of trans-allelic interactions, we describe the process of TCM and TCdM and the effect such changes can have on genome activity. Trans-allelic epigenetic interactions may be a common occurrence in many biological systems.     

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

Background

Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers.

Results

To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2''-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival.

Conclusions

This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.     

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

ChIP-seq is a powerful method for obtaining genome-wide maps of protein-DNA interactions and epigenetic modifications. CHANCE (CHip-seq ANalytics and Confidence Estimation) is a standalone package for ChIP-seq quality control and protocol optimization. Our user-friendly graphical software quickly estimates the strength and quality of immunoprecipitations, identifies biases, compares the user's data with ENCODE's large collection of published datasets, performs multi-sample normalization, checks against quantitative PCR-validated control regions, and produces informative graphical reports. CHANCE is available at https://github.com/songlab/chance.     

Guiding DNA methylation

How DNA methyltransferases, with their limited target specificity, establish cell-type-specific epigenetic patterns is poorly understood. Schübeler and colleagues (Lienert et al., 2011) now show that methylation-determining regions (MDRs) within promoter regions are sufficient to recapitulate endogenous patterns and dynamics of DNA methylation.     

Human non-CG methylation

Non-CG methylation is well characterized in plants, where it appears to play a role in gene silencing and genomic imprinting. Although strong evidence for the presence of non-CG methylation in animals has been available for some time, both its origin and function remain elusive. In this review we discuss available evidence on non-CG methylation in animals in light of evidence suggesting that the human stem cell methylome contains significant levels of methylation outside the CG site.     

RNA-directed DNA methylation

DNA methylation is an important epigenetic mechanism for silencing transposons and other repetitive elements, and for stable repression of specific transgenes and endogenous genes. Plants can utilize small interfering RNAs (siRNAs) to guide de novo DNA methyltransferases for the establishment of sequence-specific DNA methylation. Genetic and biochemical approaches have identified many components involved in RNA-directed DNA methylation (RdDM). These components function in one or more of the following three aspects: biogenesis of siRNAs, production of scaffold RNAs, and the assembly of an effector complex that involves the complementary pairing between the guide siRNAs and nascent scaffold RNAs and that recruits the DNA methyltransferases. Recent studies not only unveiled new molecular players and novel interactions, but also suggested spatial and temporal segregation of the RdDM process within the nucleus.     

Cytochrome c methylation

In this review, protein methylation is outlined in general terms, highlighting the major amino acids that are methylated and some of the proteins in which they are found. The majority of the review examines the methylation of cytochrome c at Lys-77 of lower eukaryotes as a possible model for methylation studies. Early work involving the purification and characterization of the methyltransferase responsible for this methylation indicated cytochrome c was methylated posttranslationally, yet prior to import into the mitochondria. Methylation in vitro occurred only at the in vivo methylation site and only on cytochrome c. Later studies using in vitro translated apocytochrome c revealed that methylated, as compared with unmethylated, apocytochrome c was imported preferentially into yeast, but not rat liver, mitochondria. Efforts to discover the reasons for this preference have shown that methylation of apocytochrome c dramatically lowers its isoelectric point (against a predicted increase) and decrease its Stokes radius. A possible mechanism for these differences involving the disruption of hydrogen bonds is presented here with space-filling models. Finally, the in vivo significance of this modification is also discussed.