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Amos Tanay and colleagues characterize DNA methylation polymorphism within cell populations and track immortalized fibroblasts in culture for over 300 generations to show that formation of differentially methylated regions occurs through a stochastic process and nearly deterministic epigenetic remodeling. DNA methylation has been comprehensively profiled in normal and cancer cells, but the dynamics that form, maintain and reprogram differentially methylated regions remain enigmatic. Here, we show that methylation patterns within populations of cells from individual somatic tissues are heterogeneous and polymorphic. Using in vitro evolution of immortalized fibroblasts for over 300 generations, we track the dynamics of polymorphic methylation at regions developing significant differential methylation on average. The data indicate that changes in population-averaged methylation occur through a stochastic process that generates a stream of local and uncorrelated methylation aberrations. Despite the stochastic nature of the process, nearly deterministic epigenetic remodeling emerges on average at loci that lose or gain resistance to methylation accumulation. Changes in the susceptibility to methylation accumulation are correlated with changes in histone modification and CTCF occupancy. Characterizing epigenomic polymorphism within cell populations is therefore critical to understanding methylation dynamics in normal and cancer cells.

Using a new method to estimate DNA methylation turnover rate, embryonic stem cells are shown to lack clonal transmission of methylation but still maintain a stable epigenetic state, whereas somatic cells transmit methylation clonally but lose epigenetic state coherence owing to the persistence of accumulated methylation errors. Stable epigenetic memory in stem cells Epigenetic mechanisms such as DNA methylation facilitate the stable maintenance of gene regulatory programs. Here, Amos Tanay and colleagues develop a method to estimate DNA methylation turnover rate, and show that embryonic stem cells maintain a stable epigenetic state without clonal transmission of methylation. In contrast, somatic cells transmit considerable epigenetic information to progenies, but this makes the somatic epigenome more vulnerable to noise. Stable maintenance of gene regulatory programs is essential for normal function in multicellular organisms. Epigenetic mechanisms, and DNA methylation in particular, are hypothesized to facilitate such maintenance by creating cellular memory 1 , 2 , 3 , 4 that can be written during embryonic development 5 , 6 and then guide cell-type-specific gene expression 7 . Here we develop new methods for quantitative inference of DNA methylation turnover rates, and show that human embryonic stem cells preserve their epigenetic state by balancing antagonistic processes that add and remove methylation marks rather than by copying epigenetic information from mother to daughter cells. In contrast, somatic cells transmit considerable epigenetic information to progenies. Paradoxically, the persistence of the somatic epigenome makes it more vulnerable to noise, since random epimutations can accumulate to massively perturb the epigenomic ground state. The rate of epigenetic perturbation depends on the genomic context, and, in particular, DNA methylation loss is coupled to late DNA replication dynamics. Epigenetic perturbation is not observed in the pluripotent state, because the rapid turnover-based equilibrium continuously reinforces the canonical state. This dynamic epigenetic equilibrium also explains how the epigenome can be reprogrammed quickly 8 and to near perfection 9 after induced pluripotency.

A high-resolution 4C-seq protocol involving two restriction digests and a revised analysis pipeline allows robust detection of physical interactions between regulatory DNA elements. Regulatory DNA elements can control the expression of distant genes via physical interactions. Here we present a cost-effective methodology and computational analysis pipeline for robust characterization of the physical organization around selected promoters and other functional elements using chromosome conformation capture combined with high-throughput sequencing (4C-seq). Our approach can be multiplexed and routinely integrated with other functional genomics assays to facilitate physical characterization of gene regulation.

Multiple discrete regions at 8q24 were recently shown to contain alleles that predispose to many cancers including prostate, breast, and colon. These regions are far from any annotated gene and their biological activities have been unknown. Here we profiled a 5-megabase chromatin segment encompassing all the risk regions for RNA expression, histone modifications, and locations occupied by RNA polymerase II and androgen receptor (AR). This led to the identification of several transcriptional enhancers, which were verified using reporter assays. Two enhancers in one risk region were occupied by AR and responded to androgen treatment; one contained a single nucleotide polymorphism (rs11986220) that resides within a FoxA1 binding site, with the prostate cancer risk allele facilitating both stronger FoxA1 binding and stronger androgen responsiveness. The study reported here exemplifies an approach that may be applied to any risk-associated allele in non-protein coding regions as it emerges from genome-wide association studies to better understand the genetic predisposition of complex diseases.

Normal cell growth is governed by a complicated biological system, featuring multiple levels of control, often deregulated in cancers. The role of microRNAs (miRNAs) in the control of gene expression is now increasingly appreciated, yet their involvement in controlling cell proliferation is still not well understood. Here we investigated the mammalian cell proliferation control network consisting of transcriptional regulators, E2F and p53, their targets and a family of 15 miRNAs. Indicative of their significance, expression of these miRNAs is downregulated in senescent cells and in breast cancers harboring wild‐type p53. These miRNAs are repressed by p53 in an E2F1‐mediated manner. Furthermore, we show that these miRNAs silence antiproliferative genes, which themselves are E2F1 targets. Thus, miRNAs and transcriptional regulators appear to cooperate in the framework of a multi‐gene transcriptional and post‐transcriptional feed‐forward loop. Finally, we show that, similarly to p53 inactivation, overexpression of representative miRNAs promotes proliferation and delays senescence, manifesting the detrimental phenotypic consequence of perturbations in this circuit. Taken together, these findings position miRNAs as novel key players in the mammalian cellular proliferation network. Synopsis Precise regulation of gene expression is crucial for maintaining homeostasis in healthy tissues and for the execution of cellular programs such as proliferation, differentiation and cell death. In the last decade, microRNAs (miRNAs) have been uncovered as an expanding family of gene expression regulators. These short non‐coding RNAs regulate gene expression at the post‐transcriptional level by promoting translational inhibition or mRNA degradation (Bartel, 2004 ). Similar to protein‐coding genes, the expression of miRNAs is also regulated by transcription factors (TFs), and induction or repression of miRNAs has been demonstrated to play a role in physiological processes such as immune response (Thai et al , 2007 ) and apoptosis (Chang et al , 2007 ; Raver‐Shapira et al , 2007 ). Accordingly, deregulation of miRNAs is associated with diverse types of diseases, including a variety of cancers (Esquela‐Kerscher and Slack, 2006 ; Volinia et al , 2006 ). In an earlier computational study, we predicted the presence of several types of regulatory network motifs that involve TFs and miRNAs (Shalgi et al , 2007 ), and may provide a mechanism for fine‐tuned coordination between transcriptional and post‐transcriptional regulation of gene expression. Here, we describe and experimentally demonstrate one such regulatory motif, termed feed‐forward loop (FFL), which involves the TF E2F1, a set of miRNAs, and their common targets (Figure 8 ). In this FFL, E2F1, a key regulator of cell‐cycle progression, transcriptionally activates a family of 15 miRNAs that are organized in three paralogous polycistrons on three different chromosomes. These miRNAs silence a group of antiproliferative regulators including the pocket proteins pRb and p130 and the CDK inhibitors p21 and p57. Importantly, these genes are themselves transcriptional targets of E2F1. Thus, a TF activates a set of genes as well as a set of miRNAs, which in turn post‐transcriptionally regulate that set of genes. Increasing the complexity of this regulatory FFL, many of the shared targets of E2F1 and the miRNAs function as regulators of the cell cycle; some negatively regulate E2F itself. For example, the pocket proteins pRB and p130 are the major components that regulate the activity of E2F family members throughout the phases of the cell cycle through direct protein–protein interaction. The TF p53 is regarded as one of the key proteins that prevent malignant transformation (Ryan et al , 2001 ), and deactivating mutations of this tumor suppressor are highly common in a wide variety of tumors (Hussain and Harris, 1999 ). A hallmark activity of p53 is the inhibition of proliferation and the induction of cellular senescence on diverse types of stress signals with oncogenic potential, including DNA damage, telomere shortening and oncogene activation. There are several known mechanisms by which p53 negatively regulates proliferation, the key one being the transcriptional activation of the CDK inhibitor p21, which indirectly inhibits the activity of E2F family members. Another recently discovered mechanism for inhibiting proliferation by p53 is the induction of miRNAs from the miR‐34 family, which also modulate the E2F pathway (He et al , 2007 ; Tarasov et al , 2007 ; Tazawa et al , 2007 ; Kumamoto et al , 2008 ). Additionally, direct and indirect transcriptional repression by p53 is considered important for its ability to inhibit proliferation (Ho and Benchimol, 2003 ). Using miRNA microarrays, we discovered that p53 activation during cellular senescence in primary human fibroblasts leads to a decrease in the expression of the above‐mentioned family of miRNAs, including members of the miR‐17‐92, miR‐106b/93/25 and miR‐106a‐92 polycistronic miRNA clusters. A similar decrease in miRNA expression was observed in human breast cancer specimens that harbor wild‐type p53 as compared with those that harbor mutant forms of p53. We further investigated the mechanism by which p53 represses the expression of this group of miRNAs, and found that activation of p53 leads to a dramatic reduction of E2F1 mRNA, protein and activity levels, which in turn leads to a decrease in the E2F1‐dependent transcriptional activation of these miRNAs. To study the consequence of deregulation of this FFL and importance of its inhibition by p53, we ectopically expressed representative members from the set of p53‐repressed miRNAs, namely the miR‐106b/93/25 polycistron, in primary human fibroblasts. Consequently, these cells acquired an enhanced proliferative phenotype manifested by increased growth rate, increased colony formation efficiency and delayed entry into replicative senescence. These results position the repression of this set of miRNAs as a novel mechanism by which p53 inhibits proliferation and controls cell fate. Here we identified a group of 15 co‐regulated paralogous miRNAs which are transcriptionally activated by E2F1. This group includes the miR‐17‐92, miR‐106a‐92 and miR‐106b/93/25 polycistronic miRNAs. These miRNAs silence anti‐proliferative genes, which themselves are E2F1 targets and function as negative regulators of proliferation. Thus, E2F1 and this group of microRNAs cooperate in a feed‐forward loop that involves transcriptional and post‐transcriptional modes of regulation. The key tumor suppressor p53 disrupts this feed‐forward loop by inactivating E2F1 in senescent cells and in human cancers. This inhibition serves as another arm of p53's tight control of proliferation.

UMI-4C is a rapid, simplified barcoding approach to targeted chromatin conformation capture that produces high-complexity libraries from low sample input, is easily multiplexed and gives a quantitative, statistically defined readout. We developed a targeted chromosome conformation capture (4C) approach that uses unique molecular identifiers (UMIs) to derive high-complexity quantitative chromosome contact profiles with controlled signal-to-noise ratios. UMI-4C detects chromosomal interactions with improved sensitivity and specificity, and it can easily be multiplexed to allow robust comparison of contact distributions between loci and conditions. This approach may open the way to the incorporation of contact distributions into quantitative models of gene regulation.

Multiple discrete regions at 8q24 were recently shown to contain alleles that predispose to many cancers including prostate, breast, and colon. These regions are far from any annotated gene and their biological activities have been unknown. Here we profiled a 5-megabase chromatin segment encompassing all the risk regions for RNA expression, histone modifications, and locations occupied by RNA polymerase II and androgen receptor (AR). This led to the identification of several transcriptional enhancers, which were verified using reporter assays. Two enhancers in one risk region were occupied by AR and responded to androgen treatment; one contained a single nucleotide polymorphism (rs11986220) that resides within a FoxA1 binding site, with the prostate cancer risk allele facilitating both stronger FoxA1 binding and stronger androgen responsiveness. The study reported here exemplifies an approach that may be applied to any risk-associated allele in non-protein coding regions as it emerges from genome-wide association studies to better understand the genetic predisposition of complex diseases.