Epigenetic mechanisms integrate genetic and environmental causes of disease. Comprehensive genome-wide analyses of epigenetic modifications have not demonstrated robust association with common diseases. Using Illumina HumanMethylation450 arrays on 354 ACPA positive rheumatoid arthritis (RA) cases and 337 controls, we identified two clusters within the MHC region whose differential methylation potentially mediates genetic risk for RA. To reduce confounding hampering previous epigenome-wide studies, we corrected for cellular heterogeneity by estimating and adjusting for cell-type proportions and used mediation analysis to filter out associations likely consequential to disease. Four CpGs also showed association between genotype and variance of methylation in addition to mean. The associations for both clusters replicated at least one CpG (p<0.01), with the rest showing suggestive association, in monocytes in an independent 12 cases and 12 controls. Thus, DNA methylation is a potential mediator of genetic risk.
In spite of our increased understanding of how genomes are dysregulated in cancer and a plethora of molecular diagnostic tools, the front line and ‘gold standard’ detection of cancer remains the pathologist’s detection of gross changes in cellular and tissue structure, most strikingly nuclear dis-organization. In fact, for over 140 years it has been noted that nuclear morphology is often disrupted in cancer. Even today, nuclear morphology measures include nuclear size, shape, DNA content (ploidy) and ‘chromatin organization’. Given the importance of nuclear shape to diagnoses of cancer phenotypes, it is surprising and frustrating that we currently lack a detailed understanding to explain these changes and how they might arise and relate to molecular events in the cell. It is an implicit hypothesis that perturbation of chromatin and epigenetic signatures may lead to alterations in nuclear structure (or vice versa) and that these perturbations lie at the heart of cancer genesis. In this review, we attempt to synthesize research leading to our current understanding on how chromatin interactions at the nuclear lamina, epigenetic modulation and gene regulation may intersect in cancer and offer a perspective on critical experiments that would help clarify how nuclear architecture may contribute to the cancerous phenotype. We also discuss the historical understanding of nuclear structure in normal cells and as a diagnostic in cancer.
Chromatin; Chromosome; Nuclear lamina; Histone; DNA methylation; Lamina Associated Domain; Epigenetics; Fluorescence in situ hybridization (FISH); Hi-C; DamID; ChIP; Cancer; Development
In honeybee societies, distinct caste phenotypes are created from the same genotype, suggesting a role for epigenetics in deriving these behaviorally different phenotypes. We found no differences in DNA methylation between irreversible worker/queen castes, but substantial differences between nurses and forager subcastes. Reverting foragers back to nurses reestablished methylation levels for a majority of genes and provided the first evidence in any organism of reversible epigenetic changes associated with behavior.
Background Gestational age at birth strongly predicts neonatal, adolescent and adult morbidity and mortality through mostly unknown mechanisms. Identification of specific genes that are undergoing regulatory change prior to birth, such as through changes in DNA methylation, would increase our understanding of developmental changes occurring during the third trimester and consequences of pre-term birth (PTB).
Methods We performed a genome-wide analysis of DNA methylation (using microarrays, specifically CHARM 2.0) in 141 newborns collected in Baltimore, MD, using novel statistical methodology to identify genomic regions associated with gestational age at birth. Bisulphite pyrosequencing was used to validate significant differentially methylated regions (DMRs), and real-time PCR was performed to assess functional significance of differential methylation in a subset of newborns.
Results We identified three DMRs at genome-wide significance levels adjacent to the NFIX, RAPGEF2 and MSRB3 genes. All three regions were validated by pyrosequencing, and RAGPEF2 also showed an inverse correlation between DNA methylation levels and gene expression levels. Although the three DMRs appear very dynamic with gestational age in our newborn sample, adult DNA methylation levels at these regions are stable and of equal or greater magnitude than the oldest neonate, directionally consistent with the gestational age results.
Conclusions We have identified three differentially methylated regions associated with gestational age at birth. All three nearby genes play important roles in the development of several organs, including skeletal muscle, brain and haematopoietic system. Therefore, they may provide initial insight into the basis of PTB's negative health outcomes. The genome-wide custom DNA methylation array technology and novel statistical methods employed in this study could constitute a model for epidemiologic studies of epigenetic variation.
Epigenetic epidemiology; differentially methylated regions; pre-term birth; gestational age; genome-wide DNA methylation
Background During the past 5 years, high-throughput technologies have been successfully used by epidemiology studies, but almost all have focused on sequence variation through genome-wide association studies (GWAS). Today, the study of other genomic events is becoming more common in large-scale epidemiological studies. Many of these, unlike the single-nucleotide polymorphism studied in GWAS, are continuous measures. In this context, the exercise of searching for regions of interest for disease is akin to the problems described in the statistical ‘bump hunting’ literature.
Methods New statistical challenges arise when the measurements are continuous rather than categorical, when they are measured with uncertainty, and when both biological signal, and measurement errors are characterized by spatial correlation along the genome. Perhaps the most challenging complication is that continuous genomic data from large studies are measured throughout long periods, making them susceptible to ‘batch effects’. An example that combines all three characteristics is genome-wide DNA methylation measurements. Here, we present a data analysis pipeline that effectively models measurement error, removes batch effects, detects regions of interest and attaches statistical uncertainty to identified regions.
Results We illustrate the usefulness of our approach by detecting genomic regions of DNA methylation associated with a continuous trait in a well-characterized population of newborns. Additionally, we show that addressing unexplained heterogeneity like batch effects reduces the number of false-positive regions.
Conclusions Our framework offers a comprehensive yet flexible approach for identifying genomic regions of biological interest in large epidemiological studies using quantitative high-throughput methods.
Epigenetic epidemiology; DNA methylation; genome-wide analysis; bump hunting; batch effects
It has recently been proposed that variation in DNA methylation at specific genomic locations may play an important role in the development of complex diseases such as cancer. Here, we develop 1- and 2-group multiple testing procedures for identifying and quantifying regions of DNA methylation variability. Our method is the first genome-wide statistical significance calculation for increased or differential variability, as opposed to the traditional approach of testing for mean changes. We apply these procedures to genome-wide methylation data obtained from biological and technical replicates and provide the first statistical proof that variably methylated regions exist and are due to interindividual variation. We also show that differentially variable regions in colon tumor and normal tissue show enrichment of genes regulating gene expression, cell morphogenesis, and development, supporting a biological role for DNA methylation variability in cancer.
Bump finding; Functional data analysis; Multiple testing; Preprocessing; Variably methylation regions (VMRs)
Comprehensive high-throughput arrays for relative methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen and three brain regions: cortex, hippocampus and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33–59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14–40%, for the cortex vs. hippocampus DMRs, 12–29%, and for the cortex vs. hypothalamus DMRs, 5–35%, with a correlation of r2 = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.
epigenetics; DNA methylation; methylation array; genome-wide; rat; brain
The organization of higher order chromatin is an emerging epigenetic mechanism for understanding development and disease. We and others have previously observed dynamic changes during differentiation and oncogenesis in large heterochromatin domains such as Large Organized Chromatin K (lysine) modifications (LOCKs), of histone H3 lysine-9 dimethylation (H3K9me2) or other repressive histone posttranslational modifications. The microstructure of these regions has not previously been explored.
We analyzed the genome-wide distribution of H3K9me2 in two human pluripotent stem cell lines and three differentiated cells lines. We identified > 2,500 small regions with very low H3K9me2 signals in the body of LOCKs, which were termed as euchromatin islands (EIs). EIs are 6.5-fold enriched for DNase I Hypersensitive Sites and 8-fold enriched for the binding of CTCF, the major organizer of higher-order chromatin. Furthermore, EIs are 2–6 fold enriched for differentially DNA-methylated regions associated with tissue types (T-DMRs), reprogramming (R-DMRs) and cancer (C-DMRs). Gene ontology (GO) analysis suggests that EI-associated genes are functionally related to organ system development, cell adhesion and cell differentiation.
We identify the existence of EIs as a finer layer of epigenomic architecture within large heterochromatin domains. Their enrichment for CTCF sites and DNAse hypersensitive sites, as well as association with DMRs, suggest that EIs play an important role in normal epigenomic architecture and its disruption in disease.
Epigenetics; H3K9me2; Euchromatin islands; CTCF; DNA methylation
We compared bona-fide human induced pluripotent stem cells (iPSC) derived from umbilical cord blood (CB) and neonatal keratinocytes (K). As a consequence of both incomplete erasure of tissue-specific methylation and aberrant de novo methylation, CB-iPSC and K-iPSC are distinct in genome-wide DNA methylation profiles and differentiation potential. Extended passage of some iPSC clones in culture didn't improve their epigenetic resemblance to ESC, implying that some human iPSC retain a residual “epigenetic memory” of their tissue of origin.
DNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in their infancy. Methylation sensitive restriction enzymes and microarrays provide a potential high-throughput, low-cost platform to allow methylation profiling. However, accurate absolute methylation estimates have been elusive due to systematic errors and unwanted variability. Previous microarray preprocessing procedures, mostly developed for expression arrays, fail to adequately normalize methylation-related data since they rely on key assumptions that are violated in the case of DNA methylation. We develop a normalization strategy tailored to DNA methylation data and an empirical Bayes percentage methylation estimator that together yield accurate absolute methylation estimates that can be compared across samples. We illustrate the method on data generated to detect methylation differences between tissues and between normal and tumor colon samples.
DNA methylation; Epigenetics; Microarray
Tumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which also distinguish normal tissue types from each other, suggesting that these cDMRs might be generalized across cancer types. Here we show stochastic methylation variation of the same cDMRs, distinguishing cancer from normal, in colon, lung, breast, thyroid, and Wilms tumors, with intermediate variation in adenomas. Whole genome bisulfite sequencing shows these variable cDMRs are related to loss of sharply delimited methylation boundaries at CpG islands. Furthermore, we find hypomethylation of discrete blocks encompassing half the genome, with extreme gene expression variability. Genes associated with the cDMRs and large blocks are involved in mitosis and matrix remodeling, respectively. These data suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer and could contribute to tumor heterogeneity.
Epithelial to mesenchymal transition (EMT) is an extreme example of cell plasticity, important for normal development, injury repair, and malignant progression. Widespread epigenetic reprogramming occurs during stem cell differentiation and malignant transformation, but EMT-related epigenetic reprogramming is poorly understood. Here we investigated epigenetic modifications during TGF-β-mediated EMT. While DNA methylation was unchanged during EMT, we found global reduction of the heterochromatin mark H3-lys9 dimethylation (H3K9Me2), increase of the euchromatin mark H3-lys4 trimethylation (H3K4Me3), and increase of the transcriptional mark H3-lys36 trimethylation (H3K36Me3). These changes were largely dependent on lysine-specific deaminase-1 (Lsd1), and Lsd1 loss-of-function experiments showed marked effects on EMT-driven cell migration and chemoresistance. Genome-scale mapping revealed that chromatin changes were largely specific to large organized heterochromatin K9-modifications (LOCKs), suggesting that EMT is characterized by reprogramming of specific chromatin domains across the genome.
The epigenome consists of non–sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here, we have performed an unbiased genome-scale analysis of ~4 million CpG sites in 74 individuals with comprehensive array-based relative methylation (CHARM) analysis. We found 227 regions that showed extreme interindividual variability [variably methylated regions (VMRs)] across the genome, which are enriched for developmental genes based on Gene Ontology analysis. Furthermore, half of these VMRs were stable within individuals over an average of 11 years, and these VMRs defined a personalized epigenomic signature. Four of these VMRs showed covariation with body mass index consistently at two study visits and were located in or near genes previously implicated in regulating body weight or diabetes. This work suggests an epigenetic strategy for identifying patients at risk of common disease.
The DNA of most vertebrates is depleted in CpG dinucleotide: a C followed by a G in the 5′ to 3′ direction. CpGs are the target for DNA methylation, a chemical modification of cytosine (C) heritable during cell division and the most well-characterized epigenetic mechanism. The remaining CpGs tend to cluster in regions referred to as CpG islands (CGI). Knowing CGI locations is important because they mark functionally relevant epigenetic loci in development and disease. For various mammals, including human, a readily available and widely used list of CGI is available from the UCSC Genome Browser. This list was derived using algorithms that search for regions satisfying a definition of CGI proposed by Gardiner-Garden and Frommer more than 20 years ago. Recent findings, enabled by advances in technology that permit direct measurement of epigenetic endpoints at a whole-genome scale, motivate the need to adapt the current CGI definition. In this paper, we propose a procedure, guided by hidden Markov models, that permits an extensible approach to detecting CGI. The main advantage of our approach over others is that it summarizes the evidence for CGI status as probability scores. This provides flexibility in the definition of a CGI and facilitates the creation of CGI lists for other species. The utility of this approach is demonstrated by generating the first CGI lists for invertebrates, and the fact that we can create CGI lists that substantially increases overlap with recently discovered epigenetic marks. A CGI list and the probability scores, as a function of genome location, for each species are available at http://www.rafalab.org.
CpG island; Epigenetics; Hidden Markov model; Sequence analysis
Traditionally, the pathology of human disease has been focused on microscopic examination of affected tissues, chemical and biochemical analysis of biopsy samples, other available samples of convenience, such as blood, and noninvasive or invasive imaging of varying complexity, in order to classify disease and illuminate its mechanistic basis. The molecular age has complemented this armamentarium with gene expression arrays and selective analysis of individual genes. However, we are entering a new era of epigenomic profiling, i.e., genome-scale analysis of cell-heritable nonsequence genetic change, such as DNA methylation. The epigenome offers access to stable measurements of cellular state and to biobanked material for large-scale epidemiological studies. Some of these genome-scale technologies are beginning to be applied to create the new field of epigenetic epidemiology.
Epigenetics; Epidemiology; DNA methylation
Epigenomics provides the functional context of genome sequence, analogous to the functional anatomy of the human body provided by Vesalius a half millennium ago. Much of what appear to be inconclusive genetic data for common disease could therefore become meaningful in an epigenomic context.
Epigenetic modifications must underlie lineage-specific differentiation as terminally differentiated cells express tissue-specific genes, but their DNA sequence is unchanged. Hematopoiesis provides a well-defined model to study epigenetic modifications during cell-fate decisions, as multipotent progenitors (MPPs) differentiate into progressively restricted myeloid or lymphoid progenitors. While DNA methylation is critical for myeloid versus lymphoid differentiation, as demonstrated by the myeloerythroid bias in Dnmt1 hypomorphs1, a comprehensive DNA methylation map of hematopoietic progenitors, or of any multipotent/oligopotent lineage, does not exist. Here we examined 4.6 million CpG sites throughout the genome for MPPs, common lymphoid progenitors (CLPs), common myeloid progenitors (CMPs), granulocyte/macrophage progenitors (GMPs), and thymocyte progenitors (DN1, DN2, DN3). Dramatic epigenetic plasticity accompanied both lymphoid and myeloid restriction. Myeloid commitment involved less global DNA methylation than lymphoid commitment, supported functionally by myeloid skewing of progenitors following treatment with a DNA methyltransferase inhibitor. Differential DNA methylation correlated with gene expression more strongly at CpG island shores than CpG islands. Many examples of genes and pathways not previously known to be involved in choice between lymphoid/myeloid differentiation have been identified, such as Arl4c and Jdp2. Several transcription factors, including Meis1, were methylated and silenced during differentiation, suggesting a role in maintaining an undifferentiated state. Additionally, epigenetic modification of modifiers of the epigenome appears to be important in hematopoietic differentiation. Our results directly demonstrate that modulation of DNA methylation occurs during lineage-specific differentiation and defines a comprehensive map of the methylation and transcriptional changes that accompany myeloid versus lymphoid fate decisions.
The DNA of most vertebrates is depleted in CpG dinucleotides, the target for DNA methylation. The remaining CpGs tend to cluster in regions referred to as CpG islands (CGI). CGI have been useful as marking functionally relevant epigenetic loci for genome studies. For example, CGI are enriched in the promoters of vertebrate genes and thought to play an important role in regulation. Currently, CGI are defined algorithmically as an observed-to-expected ratio (O/E) of CpG greater than 0.6, G+C content greater than 0.5, and usually but not necessarily greater than a certain length. Here we find that the current definition leaves out important CpG clusters associated with epigenetic marks, relevant to development and disease, and does not apply at all to nonvertabrate genomes. We propose an alternative Hidden Markov model-based approach that solves these problems. We fit our model to genomes from 30 species, and the results support a new epigenomic view toward the development of DNA methylation in species diversity and evolution. The O/E of CpG in islands and nonislands segregated closely phylogenetically and showed substantial loss in both groups in animals of greater complexity, while maintaining a nearly constant difference in CpG O/E between islands and nonisland compartments. Lists of CGI for some species are available at http://www.rafalab.org.
Induced pluripotent stem (iPS) cells are derived by epigenetic reprogramming, but their DNA methylation patterns have not yet been analyzed on a genome-wide scale. Here, we find substantial hypermethylation and hypomethylation of cytosine-phosphate-guanine (CpG) island shores in nine human iPS cell lines as compared to their parental fibroblasts. The differentially methylated regions (DMRs) in the reprogrammed cells (denoted R-DMRs) were significantly enriched in tissue-specific (T-DMRs; 2.6-fold, P < 10−4) and cancer-specific DMRs (C-DMRs; 3.6-fold, P < 10−4). Notably, even though the iPS cells are derived from fibroblasts, their R-DMRs can distinguish between normal brain, liver and spleen cells and between colon cancer and normal colon cells. Thus, many DMRs are broadly involved in tissue differentiation, epigenetic reprogramming and cancer. We observed colocalization of hypomethylated R-DMRs with hypermethylated C-DMRs and bivalent chromatin marks, and colocalization of hypermethylated R-DMRs with hypomethylated C-DMRs and the absence of bivalent marks, suggesting two mechanisms for epigenetic reprogramming in iPS cells and cancer.
Tumour suppressor genes (TSGs) inhibiting normal cellular growth are frequently silenced epigenetically in cancer1. DNA methylation is commonly associated with TSG silencing1, yet mutations in the DNA methylation initiation and recognition machinery in carcinogenesis are unknown2. An intriguing possible mechanism for gene regulation involves widespread non-coding RNAs such as microRNA, Piwi-interacting RNA and antisense RNAs3-5. Widespread sense-antisense transcripts have been systematically identified in mammalian cells6, and global transcriptome analysis shows that up to 70% of transcripts have antisense partners and that perturbation of antisense RNA can alter the expression of the sense gene7. For example, it has been shown that an antisense transcript not naturally occurring but induced by genetic mutation leads to gene silencing and DNA methylation, causing thalassaemia in a patient8. Here we show that many TSGs have nearby antisense RNAs, and we focus on the role of one RNA in silencing p15, a cyclin-dependent kinase inhibitor implicated in leukaemia. We found an inverse relation between p15 antisense (p15AS) and p15 sense expression in leukaemia. A p15AS expression construct induced p15 silencing in cis and in trans through heterochromatin formation but not DNA methylation; the silencing persisted after p15AS was turned off, although methylation and heterochromatin inhibitors reversed this process. The p15AS-induced silencing was Dicer-independent. Expression of exogenous p15AS in mouse embryonic stem cells caused p15 silencing and increased growth, through heterochromatin formation, as well as DNA methylation after differentiation of the embryonic stem cells. Thus, natural antisense RNA may be a trigger for heterochromatin formation and DNA methylation in TSG silencing in tumorigenesis.
In a previous genomic analysis, using somatic methyltransferase (DNMT) knockout cells, we showed that hypomethylation decreased the expression of as many genes as were observed to increase, suggesting a previously unknown mechanism for epigenetic regulation. To address this idea, the expression of the BAG family genes was used as a model. These genes were used because their expression was decreased in DNMT1−/−, DNMT3B−/−, and double knockout cells and increased in DNMT1-overexpressing and DNMT3B-overexpressing cells. Chromatin immunoprecipitation analysis of the BAG-1 promoter in DNMT1-overexpressing or DNMT3B-overexpressing cells showed a permissive dimethyl-H3-K4/dimethyl-H3-K9 chromatin status associated with DNA-binding of CTCFL/BORIS, as well as increased BAG-1 expression. In contrast, a nonpermissive dimethyl-H3-K4/dimethyl-H3-K9 chromatin status was associated with CTCF DNA-binding and decreased BAG-1 expression in the single and double DNMT knockout cells. BORIS short hairpin RNA knockdown decreased both promoter DNA-binding, as well as BAG-1 expression, and changed the dimethyl-H3-K4/dimethyl-H3-K9 ratio to that characteristic of a nonpermissive chromatin state. These results suggest that DNMT1 and DNMT3B regulate BAG-1 expression via insulator protein DNA-binding and chromatin dynamics by regulating histone dimethylation.
The CTCF paralog BORIS (brother of the regulator of imprinted sites) is an insulator DNA-binding protein thought to play a role in chromatin organization and gene expression. Under normal physiologic conditions, BORIS is predominantly expressed during embryonic male germ cell development; however, it is also expressed in tumors and tumor cell lines and, as such, has been classified as a cancer-germline or cancer-testis gene. It has been suggested that BORIS may be a pro-proliferative factor, whereas CTCF favors antiproliferation. BORIS and CTCF share similar zinc finger DNA-binding domains and seem to bind to identical target sequences. Thus, one critical question is the mechanism governing the DNA-binding specificity of these two proteins when both are present in tumor cells. Chromatin immunoprecipitation (ChIP) in HCT116 cells and their hypermethylated variant showed that BORIS binds to methylated DNA sequences, whereas CTCF binds to unmethylated DNA. Electromobility shift assays, using both whole-cell extracts and in vitro translated CTCF and BORIS protein, and methylation-specific ChIP PCR showed that BORIS is a methylation-independent DNA-binding protein. Finally, experiments in murine hybrid cells containing either the maternal or paternal human chromosome 11 showed that BORIS preferentially binds to the methylated paternal H19 differentially methylated region, suggesting a mechanism in which the affinity of CTCF for the unmethylated maternal allele directs the DNA binding of BORIS toward the paternal allele.
Alterations in DNA methylation (DNAm) in cancer have been known for 25 years, including hypomethylation of oncogenes and hypermethylation of tumor suppressor genes1. However, most studies of cancer methylation have assumed that functionally important DNAm will occur in promoters, and that most DNAm changes in cancer occur in CpG islands2,3. Here we show that most methylation alterations in colon cancer occur not in promoters, and also not in CpG islands but in sequences up to 2 kb distant which we term “CpG island shores.” CpG island shore methylation was strongly related to gene expression, and it was highly conserved in mouse, discriminating tissue types regardless of species of origin. There was a surprising overlap (45-65%) of the location of colon cancer-related methylation changes with those that distinguished normal tissues, with hypermethylation enriched closer to the associated CpG islands, and hypomethylation enriched further from the associated CpG island and resembling non-colon normal tissues. Thus, methylation changes in cancer are at sites that vary normally in tissue differentiation, and they are consistent with the epigenetic progenitor model of cancer4, that epigenetic alterations affecting tissue-specific differentiation are the predominant mechanism by which epigenetic changes cause cancer.
Higher eukaryotes must adapt a totipotent genome to specialized cell types with a stable but limited repertoire of functions. One potential mechanism for lineage restriction is changes in chromatin, and differentiation-related chromatin changes have been observed for individual genes1–2. We have taken a genome-wide view of histone H3 lysine-9 dimethylation (H3K9Me2). We find that differentiated tissues exhibit surprisingly large K9-modified regions (up to 4.9 Mb), that are highly conserved between human and mouse, and differentiation-specific, covering only ~4% of the genome in undifferentiated mouse embryonic stem (ES) cells, compared to 31% in differentiated ES cells, ~46% in liver and ~10% in brain. They require histone methyltransferase G9a, and are inversely related to expression of genes within them, and we term them Large Organized Chromatin K9-modifications (LOCKs). LOCKs are substantially lost in cancer cell lines, and they may provide a cell type-heritable mechanism for phenotypic plasticity in development and disease.
Loss of genomic imprinting (LOI) of the insulin-like growth factor-2 gene (IGF2) is an epigenetic change involving abnormal activation of the normally silent maternally inherited allele. LOI of IGF2 gene is found in tumor tissue, normal adjoining mucosa and peripheral blood lymphocytes (PBL) of some patients with colorectal cancer (CRC), suggesting that this alteration precedes and is a risk factor for CRC. However, whether LOI of IGF2 is transitory or remains a permanent epigenetic alteration is unknown.
Four-hundred patients, mean age 60.7 years (range 15–95), 287 (80%) Caucasian were studied. This included 210 (51.4%) patients with no colorectal neoplasia, and 190 (48.6) with colorectal neoplasia. LOI of IGF2 was present in all age strata examined, and no statistically significant association across age strata (p trend > 0.05) was noted. Forty-nine patients had repeat analysis of blood imprinting status at a mean follow up time of 38.2 ± 12.9 months. All but three patients had the same imprinting status at follow up (94% agreement, kappa 0.79, p < 0.001). Genomic imprinting was stable for patients with and without colorectal neoplasia.
Standard RT-PCR assays for imprinting analysis of IGF2 were performed on PBL from ApaI informative individuals recruited at baseline and repeated 1 to 3 years later. Prevalence of LOI of IGF2 was also evaluated according to age strata.
LOI of the IGF2 gene in PBL appears to be a stable epigenetic phenomenon in most patients. Furthermore, LOI of IGF2 was not associated with age, suggesting an inherited or congenital epigenetic event. These findings support the concept that LOI of IGF2 may be a useful risk factor for CRC predisposition.
IGF2; genomic imprinting; colorectal cancer; temporal stability; loss of imprinting