Search

Genetic amplification, mutation, and translocation are known to play a causal role in the upregulation of an oncogene in cancer cells. Here, we report an emerging role of microRNA, the epigenetic deregulation of which may also lead to this oncogenic activation. SOX4, an oncogene belonging to the SRY-related high mobility group box family, was found to be overexpressed (P < 0.005) in endometrial tumors (n = 74) compared with uninvolved controls (n = 20). This gene is computationally predicted to be the target of a microRNA, miR-129-2. When compared with the matched endometria, the expression of miR-129-2 was lost in 27 of 31 primary endometrial tumors that also showed a concomitant gain of SOX4 expression (P < 0.001). This inverse relationship is associated with hypermethylation of the miR-129-2 CpG island, which was observed in endometrial cancer cell lines (n = 6) and 68% of 117 endometrioid endometrial tumors analyzed. Reactivation of miR-129-2 in cancer cells by pharmacologic induction of histone acetylation and DNA demethylation resulted in decreased SOX4 expression. In addition, restoration of miR-129-2 by cell transfection led to decreased SOX4 expression and reduced proliferation of cancer cells. Further analysis found a significant correlation of hypermethylated miR-129-2 with microsatellite instability and MLH1 methylation status (P < 0.001) and poor overall survival (P < 0.039) in patients. Therefore, these results imply that the aberrant expression of SOX4 is, in part, caused by epigenetic repression of miR-129-2 in endometrial cancer. Unlike the notion that promoter hypomethylation may upregulate an oncogene, we present a new paradigm in which hypermethylation-mediated silencing of a microRNA derepresses its oncogenic target in cancer cells. [Cancer Res 2009;69(23):9038–46]

Supplementary Table 2 from Xenoestrogen-Induced Epigenetic Repression of microRNA-9-3 in Breast Epithelial Cells

Supplementary Figures 1-6, Tables 1-15, Methods from Epigenetic Silencing Mediated through Activated PI3K/AKT Signaling in Breast Cancer

Supplementary Figures 1-6 from Epigenetic Repression of microRNA-129-2 Leads to Overexpression of SOX4 Oncogene in Endometrial Cancer

Supplementary Table 1 from Xenoestrogen-Induced Epigenetic Repression of microRNA-9-3 in Breast Epithelial Cells

The interplay between histone modifications and promoter hypermethylation provides a causative explanation for epigenetic gene silencing in cancer. Less is known about the upstream initiators that direct this process. Here, we report that the Cystatin M (CST6) tumor suppressor gene is concurrently down-regulated with other loci in breast epithelial cells cocultured with cancer-associated fibroblasts (CAF). Promoter hypermethylation of CST6 is associated with aberrant AKT1 activation in epithelial cells, as well as the disabled INNP4B regulator resulting from the suppression by CAFs. Repressive chromatin, marked by trimethyl-H3K27 and dimethyl-H3K9, and de novo DNA methylation is established at the promoter. The findings suggest that microenvironmental stimuli are triggers in this epigenetic cascade, leading to the long-term silencing of CST6 in breast tumors. Our present findings implicate a causal mechanism defining how tumor stromal fibroblasts support neoplastic progression by manipulating the epigenome of mammary epithelial cells. The result also highlights the importance of direct cell-cell contact between epithelial cells and the surrounding fibroblasts that confer this epigenetic perturbation. Because this two-way interaction is anticipated, the described coculture system can be used to determine the effect of epithelial factors on fibroblasts in future studies. [Cancer Res 2008;68(24):10257–66]

Supplementary Methods, Figures 1-5, Tables 1-5 from Breast Cancer–Associated Fibroblasts Confer AKT1-Mediated Epigenetic Silencing of Cystatin M in Epithelial Cells

Transmissible plasmids spread genes encoding antibiotic resistance and other traits to new bacterial species. Here we report that laboratory populations of Escherichia coli with a newly acquired IncQ plasmid often evolve ‘satellite plasmids’ with deletions of accessory genes and genes required for plasmid replication. Satellite plasmids are molecular parasites: their presence reduces the copy number of the full-length plasmid on which they rely for their continued replication. Cells with satellite plasmids gain an immediate fitness advantage from reducing burdensome expression of accessory genes. Yet, they maintain copies of these genes and the complete plasmid, which potentially enables them to benefit from and transmit the traits they encode in the future. Evolution of satellite plasmids is transient. Cells that entirely lose accessory gene function or plasmid mobility dominate in the long run. Satellite plasmids also evolve in Snodgrassella alvi colonizing the honey bee gut, suggesting that this mechanism may broadly contribute to the importance of IncQ plasmids as agents of bacterial gene transfer in nature., Newly acquired plasmids are frequently lost due to fitness costs. Here, Zhang et al. show that the evolution of satellite plasmids with gene deletions can reduce fitness costs by driving down the copy number of full plasmids and thus favor maintenance of the full plasmid and its novel accessory genes.

Summary Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell—the neighborhood of genetic changes that are most likely to drive adaptation in a given environment—can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell’s adaptome.

Clonal populations of cells continuously evolve new genetic diversity, but it takes a significant amount of time for the progeny of a single cell with a new beneficial mutation to outstrip both its ancestor and competitors to fully dominate a population. If these driver mutations can be discovered earlier—while they are still extremely rare—and profiled in large numbers, it may be possible to anticipate the future evolution of similar cell populations. For example, one could diagnose the likely course of incipient diseases, such as cancer and bacterial infections, and better judge which treatments will be effective, by tracking rare drug-resistant variants. To test this approach, we replayed the first 500 generations of a >70,000-generationEscherichia coliexperiment and examined the trajectories of new mutations in eight genes known to be under positive selection in this environment in six populations. By employing a deep sequencing procedure using unique molecular identifiers and target enrichment we were able to track 301 beneficial mutations at frequencies as low as 0.01% and infer the fitness effects of 240 of these. Distinct molecular signatures of selection on protein structure and function were evident for the three genes in which beneficial mutations were most common (nadR, pykF,andtopA). We detected mutations hundreds of generations before they became dominant and tracked beneficial alleles in genes that were not mutated in the long-term experiment until thousands of generations had passed. This type of targeted adaptome sequencing approach could function as an early warning system to inform interventions that aim to prevent undesirable evolution.

Experimental studies of evolution using microbes have a long tradition, and these studies have increased greatly in number and scope in recent decades. Most such experiments have been short in duration, typically running for weeks or months. A venerable exception, the long-term evolution experiment (LTEE) with Escherichia coli has continued for 30 years and 70,000 bacterial generations. The LTEE has become one of the cornerstones of the field of experimental evolution, in general, and the BEACON Center for the Study of Evolution in Action, in particular. Science laboratories and experiments usually have finite lifespans, but we hope that the LTEE can continue far into the future. There are practical issues associated with maintaining such a long-term experiment. One issue, which we address here, is whether key measurements made at one time and place are reproducible, within reasonable limits, at other times and places. This issue comes to the forefront when one considers moving an experiment like the LTEE from one lab to another. To that end, the Barrick lab at The University of Texas at Austin, measured the fitness values of samples from the 12 LTEE populations at 2,000, 10,000, and 50,000 generations and compared the new data to data previously obtained at Michigan State University. On balance, the datasets agree very well. More generally, this finding shows the value of simplicity in experimental design, such as using a chemically defined growth medium and appropriately storing samples from microbiological experiments. Even so, one must be vigilant in checking assumptions and procedures given the potential for uncontrolled factors (e.g., water quality) to affect outcomes. This vigilance is perhaps especially important for a trait like fitness, which integrates all aspects of organismal performance and may therefore be sensitive to any number of subtle environmental influences.

Lineage tracking delivers essential quantitative insight into dynamic, probabilistic cellular processes, such as somatic tumor evolution and differentiation. Methods for high diversity lineage quantitation rely on sequencing a population of DNA barcodes. However, manipulation of specific individual lineages is not possible with this approach. To address this challenge, we developed a functionalized lineage tracing tool, Control of Lineages by Barcode Enabled Recombinant Transcription (COLBERT), that enables high diversity lineage tracing and lineage-specific manipulation of gene expression. This modular platform utilizes expressed barcode gRNAs to both track cell lineages and direct lineage-specific gene expression.

Unwanted evolution of designed DNA sequences limits metabolic and genome engineering efforts. Engineered functions that are burdensome to host cells and slow their replication are rapidly inactivated by mutations, and unplanned mutations with unpredictable effects often accumulate alongside designed changes in large-scale genome editing projects. We developed a directed evolution strategy, Periodic Reselection for Evolutionarily Reliable Variants (PResERV), to discover mutations that prolong the function of a burdensome DNA sequence in an engineered organism. Here, we used PResERV to isolate E. coli cells that replicate ColE1 plasmids with higher fidelity. We found mutations in DNA polymerases I and IV and in RNase E that reduce plasmid mutation rates by 6-to 30-fold. The PResERV method implicitly selects to maintain the growth rate of host cells, and high plasmid copy numbers and gene expression levels are maintained in some of the evolved E. coli strains, indicating that it is possible to improve the genetic stability of cellular chassis without encountering trade-offs in other desirable performance characteristics. Utilizing these new antimutator E. coli and applying PResERV to other organisms in the future promises to prevent evolutionary failures and unpredictability to provide a more stable genetic foundation for synthetic biology.

Organisms evolve and adapt via changes in their genomes that improve survival and reproduction in the context of their environment. Few experiments have examined how these genomic signatures of adaptation, which may favor mutations in certain genes or molecular pathways, vary across a set of similar environments that have both shared and distinctive characteristics. We sequenced complete genomes from 30 Escherichia coli lineages that evolved for 2,000 generations in one of five environments that differed only in the temperatures they experienced. Particular “signature” genes acquired mutations in these bacteria in response to selection imposed by specific temperature treatments. Thus, it is sometimes possible to predict aspects of the environment recently experienced by microbial populations from changes in their genome sequences.

Isolated populations derived from a common ancestor are expected to diverge genetically and phenotypically as they adapt to different local environments. To examine this process, 30 populations of Escherichia coli were evolved for 2,000 generations, with six in each of five different thermal regimes: constant 20 °C, 32 °C, 37 °C, 42 °C, and daily alternations between 32 °C and 42 °C. Here, we sequenced the genomes of one endpoint clone from each population to test whether the history of adaptation in different thermal regimes was evident at the genomic level. The evolved strains had accumulated ∼5.3 mutations, on average, and exhibited distinct signatures of adaptation to the different environments. On average, two strains that evolved under the same regime exhibited ∼17% overlap in which genes were mutated, whereas pairs that evolved under different conditions shared only ∼4%. For example, all six strains evolved at 32 °C had mutations in nadR, whereas none of the other 24 strains did. However, a population evolved at 37 °C for an additional 18,000 generations eventually accumulated mutations in the signature genes strongly associated with adaptation to the other temperature regimes. Two mutations that arose in one temperature treatment tended to be beneficial when tested in the others, although less so than in the regime in which they evolved. These findings demonstrate that genomic signatures of adaptation can be highly specific, even with respect to subtle environmental differences, but that this imprint may become obscured over longer timescales as populations continue to change and adapt to the shared features of their environments.

Evolutionary innovations often arise from complex genetic and ecological interactions, which can make it challenging to understand retrospectively how a novel trait arose. In a long-term experiment, Escherichia coli gained the ability to use abundant citrate (Cit(+)) in the growth medium after ∼31,500 generations of evolution. Exploiting this previously untapped resource was highly beneficial: later Cit(+) variants achieve a much higher population density in this environment. All Cit(+) individuals share a mutation that activates aerobic expression of the citT citrate transporter, but this mutation confers only an extremely weak Cit(+) phenotype on its own. To determine which of the other >70 mutations in early Cit(+) clones were needed to take full advantage of citrate, we developed a recursive genomewide recombination and sequencing method (REGRES) and performed genetic backcrosses to purge mutations not required for Cit(+) from an evolved strain. We discovered a mutation that increased expression of the dctA C4-dicarboxylate transporter greatly enhanced the Cit(+) phenotype after it evolved. Surprisingly, strains containing just the citT and dctA mutations fully use citrate, indicating that earlier mutations thought to have potentiated the initial evolution of Cit(+) are not required for expression of the refined version of this trait. Instead, this metabolic innovation may be contingent on a genetic background, and possibly ecological context, that enabled citT mutants to persist among competitors long enough to obtain dctA or equivalent mutations that conferred an overwhelming advantage. More generally, refinement of an emergent trait from a rudimentary form may be crucial to its evolutionary success.

Adaptation by natural selection depends on the rates, effects and interactions of many mutations, making it difficult to determine what proportion of mutations in an evolving lineage are beneficial. Here we analysed 264 complete genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The populations that retained the ancestral mutation rate support a model in which most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to mutation-accumulation lines evolved under a bottlenecking regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions and deletions are overrepresented in the long-term populations, further supporting the inference that most mutations that reached high frequency were favoured by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.

Aberrant TGFβ signaling pathway may alter the expression of down-stream targets and promotes ovarian carcinogenesis. However, the mechanism of this impairment is not fully understood. Our previous study has identified RunX1T1 as a putative SMAD4 target in an immortalized ovarian surface epithelial cell line, IOSE. In this study, we report that transcription of RunX1T1 was confirmed to be positively regulated by SMAD4 in IOSE cells and epigenetically silenced in a panel of ovarian cancer cell lines by promoter hypermethylation and histone methylation at H3 lysine 9. SMAD4 depletion increased repressive histone modifications of RunX1T1 promoter without affecting promoter methylation in IOSE cells. Epigenetic treatment can restore RunX1T1 expression by reversing its epigenetic status in MCP3 ovarian cancer cells. When transiently treated with a demethylating agent, the expression of RunX1T1 was partially restored in MCP3 cells, but gradual re-silencing through promoter re-methylation was observed after the treatment. Interestingly, SMAD4 knockdown accelerated this re-silencing process, suggesting that normal TGF-beta signaling is essential for the maintenance of RunX1T1 expression. In vivo analysis confirmed that hypermethylation of RunX1T1 was detected in 35.7% (34/95) of ovarian tumors with high clinical stages (P=0.035) and in 83% (5/6) of primary ovarian cancer-initiating cells. Additionally, concurrent methylation of RunX1T1 and another SMAD4 target, FBXO32 which was previously found to be hypermethylated in ovarian cancer was observed in this same sample cohort (P< 0.05). Restoration of RunX1T1 inhibited cancer cell growth. Taken together, dysregulated TGFβ/SMAD4 signaling may lead to epigenetic silencing of a putative tumor suppressor, RunX1T1, during ovarian carcinogenesis.

Trimethylation of histone 3 lysine 27 (H3K27me3) is a critical epigenetic mark for the maintenance of gene silencing. Additional accumulation of DNA methylation in target loci is thought to cooperatively support this epigenetic silencing during tumorigenesis. However, molecular mechanisms underlying the complex interplay between the two marks remain to be explored. Here we show that activation of PI3K/AKT signaling can be a trigger of this epigenetic processing at many downstream target genes. We also find that DNA methylation can be acquired at the same loci in cancer cells, thereby reinforcing permanent repression in those losing the H3K27me3 mark. Because of a link between PI3K/AKT signaling and epigenetic alterations, we conducted epigenetic therapies in conjunction with the signaling-targeted treatment. These combined treatments synergistically relieve gene silencing and suppress cancer cell growth in vitro and in xenografts. The new finding has important implications for improving targeted cancer therapies in the future. Cancer Res; 71(5); 1752–62. ©2011 AACR.

Substantial evidence indicates that exposure to bisphenol A (BPA) during early development may increase breast cancer risk later in life. The changes may persist into puberty and adulthood, suggesting an epigenetic process being imposed in differentiated breast epithelial cells. The molecular mechanisms by which early memory of BPA exposure is imprinted in breast progenitor cells and then passed onto their epithelial progeny are not well understood. The aim of this study was to examine epigenetic changes in breast epithelial cells treated with low-dose BPA. We also investigated the effect of BPA on the ERα signaling pathway and global gene expression profiles. Compared to control cells, nuclear internalization of ERα was observed in epithelial cells preexposed to BPA. We identified 170 genes with similar expression changes in response to BPA. Functional analysis confirms that gene suppression was mediated in part through an ERα-dependent pathway. As a result of exposure to BPA or other estrogen-like chemicals, the expression of lysosomal-associated membrane protein 3 (LAMP3) became epigenetically silenced in breast epithelial cells. Furthermore, increased DNA methylation in the LAMP3 CpG island was this repressive mark preferentially occurred in ERα-positive breast tumors. These results suggest that the in vitro system developed in our laboratory is a valuable tool for exposure studies of BPA and other xenoestrogens in human cells. Individual and geographical differences may contribute to altered patterns of gene expression and DNA methylation in susceptible loci. Combination of our exposure model with epigenetic analysis and other biochemical assays can give insight into the heritable effect of low-dose BPA in human cells.

Resistance to TGF-beta is frequently observed in ovarian cancer, and disrupted TGF-beta/SMAD4 signaling results in the aberrant expression of downstream target genes in the disease. Our previous study showed that ADAM19, a SMAD4 target gene, is downregulated through epigenetic mechanisms in ovarian cancer with aberrant TGF-beta/SMAD4 signaling. In this study, we investigated the mechanism of downregulation of FBXO32, another SMAD4 target gene, and the clinical significance of the loss of FBXO32 expression in ovarian cancer. Expression of FBXO32 was observed in the normal ovarian surface epithelium, but not in ovarian cancer cell lines. FBXO32 methylation was observed in ovarian cancer cell lines displaying constitutive TGF-beta/SMAD4 signaling, and epigenetic drug treatment restored FBXO32 expression in ovarian cancer cell lines regardless of FBXO32 methylation status, suggesting that epigenetic regulation of this gene in ovarian cancer may be a common event. In advanced-stage ovarian tumors, a significant (29.3%; P

Genetic amplification, mutation, and translocation are known to play a causal role in the upregulation of an oncogene in cancer cells. Here, we report an emerging role of microRNA, the epigenetic deregulation of which may also lead to this oncogenic activation. SOX4, an oncogene belonging to the SRY-related high mobility group box family, was found to be overexpressed (P < 0.005) in endometrial tumors (n = 74) compared with uninvolved controls (n = 20). This gene is computationally predicted to be the target of a microRNA, miR-129-2. When compared with the matched endometria, the expression of miR-129-2 was lost in 27 of 31 primary endometrial tumors that also showed a concomitant gain of SOX4 expression (P < 0.001). This inverse relationship is associated with hypermethylation of the miR-129-2 CpG island, which was observed in endometrial cancer cell lines (n = 6) and 68% of 117 endometrioid endometrial tumors analyzed. Reactivation of miR-129-2 in cancer cells by pharmacologic induction of histone acetylation and DNA demethylation resulted in decreased SOX4 expression. In addition, restoration of miR-129-2 by cell transfection led to decreased SOX4 expression and reduced proliferation of cancer cells. Further analysis found a significant correlation of hypermethylated miR-129-2 with microsatellite instability and MLH1 methylation status (P < 0.001) and poor overall survival (P < 0.039) in patients. Therefore, these results imply that the aberrant expression of SOX4 is, in part, caused by epigenetic repression of miR-129-2 in endometrial cancer. Unlike the notion that promoter hypomethylation may upregulate an oncogene, we present a new paradigm in which hypermethylation-mediated silencing of a microRNA derepresses its oncogenic target in cancer cells. [Cancer Res 2009;69(23):9038–46]

Early exposure to xenoestrogens may predispose to breast cancer risk later in adult life. It is likely that long-lived, self-regenerating epithelial progenitor cells are more susceptible to these exposure injuries over time and transmit the injured memory through epigenetic mechanisms to their differentiated progeny. Here, we used progenitor-containing mammospheres as an in vitro exposure model to study this epigenetic effect. Expression profiling identified that, relative to control cells, 9.1% of microRNAs (82 of 898 loci) were altered in epithelial progeny derived from mammospheres exposed to a synthetic estrogen, diethylstilbestrol. Repressive chromatin marks, trimethyl Lys27 of histone H3 (H3K27me3) and dimethyl Lys9 of histone H3 (H3K9me2), were found at a down-regulated locus, miR-9-3, in epithelial cells preexposed to diethylstilbestrol. This was accompanied by recruitment of DNA methyltransferase 1 that caused an aberrant increase in DNA methylation of its promoter CpG island in mammosphere-derived epithelial cells on diethylstilbestrol preexposure. Functional analyses suggest that miR-9-3 plays a role in the p53-related apoptotic pathway. Epigenetic silencing of this gene, therefore, reduces this cellular function and promotes the proliferation of breast cancer cells. Promoter hypermethylation of this microRNA may be a hallmark for early breast cancer development, and restoration of its expression by epigenetic and microRNA-based therapies is another viable option for future treatment of this disease. [Cancer Res 2009;69(14):5936–45]

New mutations leading to structural variation (SV) in genomes — in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements — can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide substitutions and indels (SN), so it is not yet routinely identified in studies that profile population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm using simulated Escherichia coli data and then applied it to 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously analyzed clonal isolates allowed us to evaluate the accuracy of our procedure. Overall, SV accounted for ~25% of the genetic diversity found in these samples. By profiling rare SV, we were able to identify many cases where alternative mutations in key genes transiently competed within a single population. We also found, unexpectedly, that mutations in two genes that rose to prominence at these early time points always went extinct in the long term. Because it is not limited by the base-calling error rate of the sequencing technology, our approach for identifying rare SV in whole-population samples may have a lower detection limit than similar predictions of SNs in these data sets. We anticipate that this functionality of breseq will be useful for providing a more complete picture of genome dynamics during evolution experiments with haploid microorganisms.

Background Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events. Results We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold). Conclusions Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-1039) contains supplementary material, which is available to authorized users.

Large-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelve Escherichia coli populations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement events were detected, including 82 deletions, 19 inversions, and 9 duplications, with lineages having between 5 and 20 events. In three populations, successive rearrangements impacted particular regions. In five populations, rearrangements affected over a third of the chromosome. Most rearrangements involved recombination between insertion sequence (IS) elements, illustrating their importance in mediating genome plasticity. Two lines of evidence suggest that at least some of these rearrangements conferred higher fitness. First, parallel changes were observed across the independent populations, with ~65% of the rearrangements affecting the same loci in at least two populations. For example, the ribose-utilization operon and the manB-cpsG region were deleted in 12 and 10 populations, respectively, suggesting positive selection, and this inference was previously confirmed for the former case. Second, optical maps from clones sampled over time from one population showed that most rearrangements occurred early in the experiment, when fitness was increasing most rapidly. However, some rearrangements likely occur at high frequency and may have simply hitchhiked to fixation. In any case, large-scale rearrangements clearly influenced genomic evolution in these populations., IMPORTANCE Bacterial chromosomes are dynamic structures shaped by long histories of evolution. Among genomic changes, large-scale DNA rearrangements can have important effects on the presence, order, and expression of genes. Whole-genome sequencing that relies on short DNA reads cannot identify all large-scale rearrangements. Therefore, deciphering changes in the overall organization of genomes requires alternative methods, such as optical mapping. We analyzed the longest-running microbial evolution experiment (more than 25 years of evolution in the laboratory) by optical mapping, genome sequencing, and PCR analyses. We found multiple large genome rearrangements in all 12 independently evolving populations. In most cases, it is unclear whether these changes were beneficial themselves or, alternatively, hitchhiked to fixation with other beneficial mutations. In any case, many genome rearrangements accumulated over decades of evolution, providing these populations with genetic plasticity reminiscent of that observed in some pathogenic bacteria.

Next-generation DNA sequencing (NGS) can be used to reconstruct eco-evolutionary population dynamics and to identify the genetic basis of adaptation in laboratory evolution experiments. Here, we describe how to run the open-source breseq computational pipeline to identify and annotate genetic differences found in whole-genome and whole-population NGS data from haploid microbes where a high-quality reference genome is available. These methods can also be used to analyze mutants isolated in genetic screens and to detect unintended mutations that may occur during strain construction and genome editing.

Deregulation of the transforming growth factor-β (TGFβ) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. TGFβ stimulated SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGFβ-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced, SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer and link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers.

The current concept of epigenetic repression is based on one repressor unit corresponding to one silent gene. This notion, however, cannot adequately explain concurrent silencing of multiple loci observed in large chromosome regions. The long-range epigenetic silencing (LRES) can be a frequent occurrence throughout the human genome. To comprehensively characterize the influence of estrogen signaling on LRES, we analyzed transcriptome, methylome, and estrogen receptor alpha (ESR1)-binding datasets from normal breast epithelia and breast cancer cells. This “omics” approach uncovered 11 large repressive zones (range, 0.35∼5.98 megabases), including a 14-gene cluster located on 16p11.2. In normal cells, estrogen signaling induced transient formation of multiple DNA loops in the 16p11.2 region by bringing 14 distant loci to focal ESR1-docking sites for coordinate repression. However, the plasticity of this free DNA movement was reduced in breast cancer cells. Together with the acquisition of DNA methylation and repressive chromatin modifications at the 16p11.2 loci, an inflexible DNA scaffold may be a novel determinant used by breast cancer cells to reinforce estrogen-mediated repression.

Differential Methylation Hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good read-outs for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. The step-by-step laboratory DMH protocol is described. In addition, we provide descriptions regarding DMH data analysis, including image quantification, background correction, and statistical procedures for both exploratory analysis and more formal inferences. Issues regarding quality control are addressed as well.

Differential methylation hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a revised DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good readouts for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. In addition to the step-by-step laboratory DMH protocol, we also provide a detailed description regarding DMH data analysis. The suggested microarray platform contains 244,000 probes and it can be a daunting barrier for researchers with no prior experience in analyzing DNA methylation data. We have created a data analysis pipeline available in a user friendly, publicly available interface, the Broad Institute's GenePattern software, which can be accessed at http://bisr.osumc.edu :8080/gp. This permits scientists to use our existing data analysis modules on their own data. As we continue to update our analysis algorithm and approaches to integrate high-throughput methylation data with other large-scale data types, we will make these new computation protocols available through the GenePattern platform.

The interplay between histone modifications and promoter hypermethylation provides a causative explanation for epigenetic gene silencing in cancer. Less is known about the upstream initiators that direct this process. Here, we report that the Cystatin M (CST6) tumor suppressor gene is concurrently down-regulated with other loci in breast epithelial cells cocultured with cancer-associated fibroblasts (CAF). Promoter hypermethylation of CST6 is associated with aberrant AKT1 activation in epithelial cells, as well as the disabled INNP4B regulator resulting from the suppression by CAFs. Repressive chromatin, marked by trimethyl-H3K27 and dimethyl-H3K9, and de novo DNA methylation is established at the promoter. The findings suggest that microenvironmental stimuli are triggers in this epigenetic cascade, leading to the long-term silencing of CST6 in breast tumors. Our present findings implicate a causal mechanism defining how tumor stromal fibroblasts support neoplastic progression by manipulating the epigenome of mammary epithelial cells. The result also highlights the importance of direct cell-cell contact between epithelial cells and the surrounding fibroblasts that confer this epigenetic perturbation. Because this two-way interaction is anticipated, the described coculture system can be used to determine the effect of epithelial factors on fibroblasts in future studies. [Cancer Res 2008;68(24):10257–66]

Differential methylation hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a revised DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good readouts for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. In addition to the step-by-step laboratory DMH protocol, we also provide a detailed description regarding DMH data analysis. The suggested microarray platform contains 244,000 probes and it can be a daunting barrier for researchers with no prior experience in analyzing DNA methylation data. We have created a data analysis pipeline available in a user friendly, publicly available interface, the Broad Institute's GenePattern software, which can be accessed at http://bisr.osumc.edu :8080/gp. This permits scientists to use our existing data analysis modules on their own data. As we continue to update our analysis algorithm and approaches to integrate high-throughput methylation data with other large-scale data types, we will make these new computation protocols available through the GenePattern platform.

Kinship relations within populations of unionicolid water mites are not well known, owing to their complex life cycles and the fact that interactions between active and resting stages for some species are transitory. A number of species of unionicolid water mites are, however, obligate symbionts of freshwater mussels and spend most of their life cycle in association with these hosts. Among these species of mites, parents and offspring are more likely to co-occur and thus provide opportunities to address questions related to the structure of the mating system. The present study employs random amplified polymorphic DNA (RAPD) analysis to address kinship within populations of Unionicola foili living in symbiotic association with the host mussel Utterbackia imbecillis. DNA was amplified from adult mites and a representative number of eggs or larvae (n = 20-30) that were removed from mussels collected on three separate occasions (July, November, and March) over a 12-month period. Parsimony analyses of the molecular data for adults and progeny collected from mussels during July, November, and March revealed distinct groupings, that for the most part, corresponded to mites collected from each of the sampling periods. Many of the genetic markers obtained for male and female U. foili were not evident among the larvae or eggs, suggesting that adults obtained from a host mussel at the time of collection were not the parents of a majority of the progeny. However, female mites and eggs collected from mussels during March and November shared more markers than did females and progeny examined during July. Furthermore, many offspring in the July sampling period were found to have one or more parents absent from the sampled population. Overall, RAPD profiling appears to have limited usage in determining kinship within populations of U. foili, due to its recruitment patterns, and the relatively large number of adults and progeny per mussel. It may, however, prove to be a useful method for assessing genetic relatedness among unionicolid mussel-mites that have substantially lower population densities.

Kinship relations within populations of unionicolid water mites are not well known, owing to their complex life cycles and the fact that interactions between active and resting stages for some species are transitory. A number of species of unionicolid water mites are, however, obligate symbionts of freshwater mussels and spend most of their life cycle in association with these hosts. Among these species of mites, parents and offspring are more likely to co-occur and thus provide opportunities to address questions related to the structure of the mating system. The present study employs random amplified polymorphic DNA (RAPD) analysis to address kinship within populations of Unionicola foili living in symbiotic association with the host mussel Utterbackia imbecillis. DNA was amplified from adult mites and a representative number of eggs or larvae (n = 20-30) that were removed from mussels collected on three separate occasions (July, November, and March) over a 12-month period. Parsimony analyses of the molecular data for adults and progeny collected from mussels during July, November, and March revealed distinct groupings, that for the most part, corresponded to mites collected from each of the sampling periods. Many of the genetic markers obtained for male and female U. foili were not evident among the larvae or eggs, suggesting that adults obtained from a host mussel at the time of collection were not the parents of a majority of the progeny. However, female mites and eggs collected from mussels during March and November shared more markers than did females and progeny examined during July. Furthermore, many offspring in the July sampling period were found to have one or more parents absent from the sampled population. Overall, RAPD profiling appears to have limited usage in determining kinship within populations of U. foili, due to its recruitment patterns, and the relatively large number of adults and progeny per mussel. It may, however, prove to be a useful method for assessing genetic relatedness among unionicolid mussel-mites that have substantially lower population densities.

Dysregulation of TGF-β signaling plays a crucial role in ovarian carcinogenesis and maintaining cancer stem cell properties. We have previously identified the TGF-β responsive targets in immortalized ovarian surface epithelial cells (IOSE) by expression microarray and found that ABCA1, a family members of ATP-binding cassette is up-regulated following TGF-β treatment (Qin et al, BMC Syst Biol 2009). Thus, we hypothesize that ABCA1 may be involved in ovarian cancer and its initiation. First, we compared the expression level of ABCA1 in IOSE and a panel of ovarian cancer cell lines and found that ABCA1 was up-regulated in HeyC2, SKOV3, MCP3, and MCP2 ovarian cancer cell lines but down-regulated in A2780 and CP70 ovarian cancer cells. The down-regulation in A2780 and CP70 cells was associated with promoter hypermethylation as demonstrated by bisulphite sequencing and demethylation treatment. To investigate if ABCA1 is involved in ovarian cancer initiating cells (OCIC), we compared the methylation level of ABCA1 in ovarian tumor samples and their corresponding spheroids which is previously found to be enriched with OCIC. Lower methylation of ABCA1 could be detected in 2/6 OCIC samples as compared to their original tumors. We further analyzed the expression and methylation level of ABCA1 in CP70 spheroid (CP70sp) derived from suspension culture of CP70 ovarian cancer cells. Comparing to CP70, up-regulation of stem cell markers Nanog (3.8 fold) and Oct4 (12 fold) was detected in CP70sp cells suggesting that CP70sp may contain OCIC. Interestingly, up-regulation of ABCA1 (5.2 fold) concomitant with promoter hypomethylation was detected in CP70sp cells. Additionally, active demethylation may be involved in the hypomethylation of ABCA1 as expression of the methylcytosine dioxygenase, TET1 was up-regulated in the CP70sp cells (5.3 fold). Furthermore, ABCA1 was involved in drug resistance of ovarian cancer which is a feature of cancer initiating cells, as lenti-viral knockdown of ABCA1 in a platinum resistant MCP2 ovarian cancer cells resensitized the cells to cisplatin (IC50: shABCA1 vs shGFP: 0.267 ug/ml vs 0.402 ug/ml). We further analyzed the methylation level of ABCA1 in 97 ovarian cancer, 46 benign, and 4 normal samples using real-time quantitative MSP assay and found that higher methylation level of ABCA1 was detected in cancer than benign (P=0.051) and normal tissues (P Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 83. doi:10.1158/1538-7445.AM2011-83

Refractory to TGF-β is frequently observed in ovarian cancer, and disrupted TGF-β/SMAD4 signaling results in aberrant expression of downstream target genes in the disease. We hypothesized that aberrant expression of TGF-β/SMAD4 targets are mediated through epigenetic mechanism and also contribute to resistance to TGF-β meditated growth inhibition. Our previous report using chromatin immunoprecipitation microarray (ChIP-chip) identified FBXO32 as one of SMAD4 targets in immortalized ovarian surface epithelial cell (IOSE) (Qin et al., BMC Syst Biol, 17: 73, 2009). In the present study, we investigated the mechanism conferring FBXO32 down-regulation, its clinical significance, and its function in ovarian cancer. Our result showed that expression of FBXO32 was observed in normal ovarian surface epithelium but not in ovarian cancer cell lines (HeyC2, SKOV3, CP70, A2708, MCP2, MCP3) using real time RT-PCR. Promoter methylation of FBXO32 was seen in ovarian cancer cell lines, HeyC2 and SKOV3, that display constitutive TGF-β/SMAD4 signaling. Moreover, our finding that epigenetic drug treatment restored FBXO32 expression in ovarian cancer cell lines regardless of FBXO32 methylation status, suggested that epigenetic regulation of FBXO32 in ovarian cancer may be a common event. Re-expression of FBXO32 markedly impeded proliferation of a platinum-resistant ovarian cancer cell lines, HeyC2 and CP70 (colony number: HeyC2: 19.33 ± 3.06 vs 1 ± 0, P< 0.005; CP70: 46.5 ± 6.36 vs 1.5 ± 0.7, P< 0.001) by using colony formation assay, due to increased apoptosis of the cells (CP70; apoptotic cell%, control: 2.55 ± 0.17; FBXO32: 10.72 ± 1.07, P Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3072.

Transforming growth factor-beta (TGF-beta)/SMAD signaling is a key growth regulatory pathway often dysregulated in ovarian cancer and other malignancies. Although loss of TGF-beta-mediated growth inhibition has been shown to contribute to aberrant cell behavior, the epigenetic consequence(s) of impaired TGF-beta/SMAD signaling on target genes is not well established. In this study, we show that TGF-beta1 causes growth inhibition of normal ovarian surface epithelial cells, induction of nuclear translocation SMAD4, and up-regulation of ADAM19 (a disintegrin and metalloprotease domain 19), a newly identified TGF-beta1 target gene. Conversely, induction and nuclear translocation of SMAD4 were negligible in ovarian cancer cells refractory to TGF-beta1 stimulation, and ADAM19 expression was greatly reduced. Furthermore, in the TGF-beta1 refractory cells, an inactive chromatin environment, marked by repressive histone modifications (trimethyl-H3K27 and dimethyl-H3K9) and histone deacetylase, was associated with the ADAM19 promoter region. However, the CpG island found within the promoter and first exon of ADAM19 remained generally unmethylated. Although disrupted growth factor signaling has been linked to epigenetic gene silencing in cancer, this is the first evidence demonstrating that impaired TGF-beta1 signaling can result in the formation of a repressive chromatin state and epigenetic suppression of ADAM19. Given the emerging role of ADAMs family proteins in growth factor regulation in normal cells, we suggest that epigenetic dysregulation of ADAM19 may contribute to the neoplastic process in ovarian cancer.