Germline methylation patterns inferred from local nucleotide frequency of repetitive sequences in the human genome

Given the genomic abundance and susceptibility to DNA methylation, interspersed repetitive sequences in the human genome can be exploited as valuable resources in genome-wide methylation studies. To learn about the relationships between DNA methylation and repeat sequences, we performed a global measurement of CpG dinucleotide frequencies for interspersed repetitive sequences and inferred germline methylation patterns in the human genome. Although extensive CpG depletion was observed for most repeat sequences, those in the proximity to CpG islands have been relatively removed from germline methylation being the potential source of germline activation. We also investigated the CpG depletion patterns of Alu pairs to see whether they might play an active role in germline methylation. Two kinds of Alu pairs, direct or inverted pairs classified according to the orientation, showed contrast CpG depletion patterns with respect to separating distance of Alus, i.e., as two Alu elements are more closely spaced in a pair, a higher extent of CpG depletion was observed in inverted orientation and vice versa for directly repetitive Alu pairs. This suggests that specific organization of repetitive sequences, such as inverted Alu pairs, might play a role in triggering DNA methylation consistent with a homology-dependent methylation hypothesis.     

Loss of epigenetic silencing in tumors preferentially affects primate-specific retroelements

Close to 50% of the human genome harbors repetitive sequences originally derived from mobile DNA elements, and in normal cells, this sequence compartment is tightly regulated by epigenetic silencing mechanisms involving chromatin-mediated repression. In cancer cells, repetitive DNA elements suffer abnormal demethylation, with potential loss of silencing. We used a genome-wide microarray approach to measure DNA methylation changes in cancers of the head and neck and to compare these changes to alterations found in adjacent non-tumor tissues. We observed specific alterations at thousands of small clusters of CpG dinucleotides associated with DNA repeats. Among the 257,599 repetitive elements probed, 5% to 8% showed disease-related DNA methylation alterations. In dysplasia, a large number of local events of loss of methylation appear in apparently stochastic fashion. Loss of DNA methylation is most pronounced for certain members of the SVA, HERV, LINE-1P, AluY, and MaLR families. The methylation levels of retrotransposons are discretely stratified, with younger elements being highly methylated in healthy tissues, while in tumors, these young elements suffer the most dramatic loss of methylation. Wilcoxon test statistics reveals that a subset of primate LINE-1 elements is demethylated preferentially in tumors, as compared to non-tumoral adjacent tissue. Sequence analysis of these strongly demethylated elements reveals genomic loci harboring full length, as opposed to truncated elements, while possible enrichment for functional LINE-1 ORFs is weaker. Our analysis suggests that, in non-tumor adjacent tissues, there is generalized and highly variable disruption of epigenetic control across the repetitive DNA compartment, while in tumor cells, a specific subset of LINE-1 retrotransposons that arose during primate evolution suffers the most dramatic DNA methylation alterations.     

Locus-specific chromatin profiling of evolutionarily young transposable elements

Despite a vast expansion in the availability of epigenomic data, our knowledge of the chromatin landscape at interspersed repeats remains highly limited by difficulties in mapping short-read sequencing data to these regions. In particular, little is known about the locus-specific regulation of evolutionarily young transposable elements (TEs), which have been implicated in genome stability, gene regulation and innate immunity in a variety of developmental and disease contexts. Here we propose an approach for generating locus-specific protein–DNA binding profiles at interspersed repeats, which leverages information on the spatial proximity between repetitive and non-repetitive genomic regions. We demonstrate that the combination of HiChIP and a newly developed mapping tool (PAtChER) yields accurate protein enrichment profiles at individual repetitive loci. Using this approach, we reveal previously unappreciated variation in the epigenetic profiles of young TE loci in mouse and human cells. Insights gained using our method will be invaluable for dissecting the molecular determinants of TE regulation and their impact on the genome.     

The profile of repeat-associated histone lysine methylation states in the mouse epigenome

Histone lysine methylation has been shown to index silenced chromatin regions at, for example, pericentric heterochromatin or of the inactive X chromosome. Here, we examined the distribution of repressive histone lysine methylation states over the entire family of DNA repeats in the mouse genome. Using chromatin immunoprecipitation in a cluster analysis representing repetitive elements, our data demonstrate the selective enrichment of distinct H3-K9, H3-K27 and H4-K20 methylation marks across tandem repeats (e.g. major and minor satellites), DNA transposons, retrotransposons, long interspersed nucleotide elements and short interspersed nucleotide elements. Tandem repeats, but not the other repetitive elements, give rise to double-stranded (ds) RNAs that are further elevated in embryonic stem (ES) cells lacking the H3-K9-specific Suv39h histone methyltransferases. Importantly, although H3-K9 tri- and H4-K20 trimethylation appear stable at the satellite repeats, many of the other repeat-associated repressive marks vary in chromatin of differentiated ES cells or of embryonic trophoblasts and fibroblasts. Our data define a profile of repressive histone lysine methylation states for the repetitive complement of four distinct mouse epigenomes and suggest tandem repeats and dsRNA as primary triggers for more stable chromatin imprints.     

Multiple cellular mechanisms prevent chromosomal rearrangements involving repetitive DNA

Repetitive DNA is present in the eukaryotic genome in the form of segmental duplications, tandem and interspersed repeats, and satellites. Repetitive sequences can be beneficial by serving specific cellular functions (e.g. centromeric and telomeric DNA) and by providing a rapid means for adaptive evolution. However, such elements are also substrates for deleterious chromosomal rearrangements that affect fitness and promote human disease. Recent studies analyzing the role of nuclear organization in DNA repair and factors that suppress non-allelic homologous recombination (NAHR) have provided insights into how genome stability is maintained in eukaryotes. In this review, we outline the types of repetitive sequences seen in eukaryotic genomes and how recombination mechanisms are regulated at the DNA sequence, cell organization, chromatin structure, and cell cycle control levels to prevent chromosomal rearrangements involving these sequences.     

Methylation analysis by DNA immunoprecipitation

DNA methylation regulates gene expression primarily through modification of chromatin structure. Global methylation studies have revealed biologically relevant patterns of DNA methylation in the human genome affecting sequences such as gene promoters, gene bodies, and repetitive elements. Disruption of normal methylation patterns and subsequent gene expression changes have been observed in several diseases especially in human cancers. Immunoprecipitation (IP)‐based methods to evaluate methylation status of DNA have been instrumental in such genome‐wide methylation studies. This review describes techniques commonly used to identify and quantify methylated DNA with emphasis on IP based platforms. In an effort to consolidate the wealth of information and highlight critical aspects of methylated DNA analysis, sample considerations, experimental and bioinformatic approaches for analyzing genome‐wide methylation profiles, and the benefit of integrating DNA methylation data with complementary dimensions of genomic data are discussed. J. Cell. Physiol. 222: 522–531, 2010. © 2009 Wiley‐Liss, Inc.