ModHMM: A Modular Supra-Bayesian Genome Segmentation Method

Genome segmentation methods are powerful tools to obtain cell type or tissue-specific genome-wide annotations and are frequently used to discover regulatory elements. However, traditional segmentation methods show low predictive accuracy and their data-driven annotations have some undesirable properties. As an alternative, we developed ModHMM, a highly modular genome segmentation method. Inspired by the supra-Bayesian approach, it incorporates predictions from a set of classifiers. This allows to compute genome segmentations by utilizing state-of-the-art methodology. We demonstrate the method on ENCODE data and show that it outperforms traditional segmentation methods not only in terms of predictive performance, but also in qualitative aspects. Therefore, ModHMM is a valuable alternative to study the epigenetic and regulatory landscape across and within cell types or tissues

Prediction of regulatory elements in mammalian genomes using chromatin signatures

<p>Abstract</p> <p>Background</p> <p>Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, providing a pragmatic way for systematic mapping of these regulatory elements in the genome. With rapid accumulation of chromatin modification profiles in the genome of various organisms and cell types, this chromatin based approach promises to uncover many new regulatory elements, but computational methods to effectively extract information from these datasets are still limited.</p> <p>Results</p> <p>We present here a supervised learning method to predict promoters and enhancers based on their unique chromatin modification signatures. We trained Hidden Markov models (HMMs) on the histone modification data for known promoters and enhancers, and then used the trained HMMs to identify promoter or enhancer like sequences in the human genome. Using a simulated annealing (SA) procedure, we searched for the most informative combination and the optimal window size of histone marks.</p> <p>Conclusion</p> <p>Compared with the previous methods, the HMM method can capture the complex patterns of histone modifications particularly from the weak signals. Cross validation and scanning the ENCODE regions showed that our method outperforms the previous profile-based method in mapping promoters and enhancers. We also showed that including more histone marks can further boost the performance of our method. This observation suggests that the HMM is robust and is capable of integrating information from multiple histone marks. To further demonstrate the usefulness of our method, we applied it to analyzing genome wide ChIP-Seq data in three mouse cell lines and correctly predicted active and inactive promoters with positive predictive values of more than 80%. The software is available at <url>http://http:/nash.ucsd.edu/chromatin.tar.gz</url>.</p

Hyperosmotic priming of arabidopsis seedlings establishes a long-term somatic memory accompanied by specific changes of the epigenome

&lt;p&gt;Background: In arid and semi-arid environments, drought and soil salinity usually occur at the beginning and end of a plant's life cycle, offering a natural opportunity for the priming of young plants to enhance stress tolerance in mature plants. Chromatin marks, such as histone modifications, provide a potential molecular mechanism for priming plants to environmental stresses, but whether transient exposure of seedlings to hyperosmotic stress leads to chromatin changes that are maintained throughout vegetative growth remains unclear.&lt;/p&gt; &lt;p&gt;Results: We have established an effective protocol for hyperosmotic priming in the model plant Arabidopsis, which includes a transient mild salt treatment of seedlings followed by an extensive period of growth in control conditions. Primed plants are identical to non-primed plants in growth and development, yet they display reduced salt uptake and enhanced drought tolerance after a second stress exposure. ChIP-seq analysis of four histone modifications revealed that the priming treatment altered the epigenomic landscape; the changes were small but they were specific for the treated tissue, varied in number and direction depending on the modification, and preferentially targeted transcription factors. Notably, priming leads to shortening and fractionation of H3K27me3 islands. This effect fades over time, but is still apparent after a ten day growth period in control conditions. Several genes with priming-induced differences in H3K27me3 showed altered transcriptional responsiveness to the second stress treatment.&lt;/p&gt; &lt;p&gt;Conclusion: Experience of transient hyperosmotic stress by young plants is stored in a long-term somatic memory comprising differences of chromatin status, transcriptional responsiveness and whole plant physiology.&lt;/p&gt

Genome-Wide Analysis of Histone Modification Enrichments Induced by Marek's Disease Virus in Inbred Chicken Lines

Covalent histone modifications constitute a complex network of transcriptional regulation involved in diverse biological processes ranging from stem cell differentiation to immune response. The advent of modern sequencing technologies enables one to query the locations of histone modifications across the genome in an efficient manner. However, inherent biases in the technology and diverse enrichment patterns complicate data analysis. Marek's disease (MD) is an acute, lymphoma-inducing disease of chickens with disease outcomes affected by multiple host and environmental factors. Inbred chicken lines 63 and 72 share the same major histocompatibility complex haplotype, but have contrasting responses to MD. This dissertation presents novel methods for analysis of genome-wide histone modification data and application of new and existing methods to the investigation of epigenetic effects of MD on these lines. First, we present WaveSeq, a novel algorithm for detection of significant enrichments in ChIP-Seq data. WaveSeq implements a distribution-free approach by combining the continuous wavelet transform with Monte Carlo sampling techniques for effective peak detection. WaveSeq outperformed existing tools particularly for diffuse histone modification peaks demonstrating that restrictive distributional assumptions are not necessary for accurate ChIP-Seq peak detection. Second, we investigated latent MD in thymus tissues by profiling H3K4me3 and H3K27me3 in infected and control birds from lines 63 and 72. Several genes associated with MD, e.g. MX1 and CTLA&ndash;4, along with those linked with human cancers, showed line-specific and condition-specific enrichments. One of the first studies of histone modifications in chickens, our work demonstrated that MD induced widespread epigenetic variations. Finally, we analyzed the temporal evolution of histone modifications at distinct phases of MD progression in the bursa of Fabricius. Genes involved in several important pathways, e.g. apoptosis and MAPK signaling, and various immune-related miRNAs showed differential histone modifications in the promoter region. Our results indicated heightened inflammation in the susceptible line during early cytolytic MD, while resistant birds showed recuperative symptoms during early MD and epigenetic silencing during latent infection. Thus, although further elucidation of underlying mechanisms is necessary, this work provided the first definitive evidence of the epigenetic effects of MD

Identifying genome-wide transcription units from histone modifications using EPIGENE

With the successful completion of the human genome project and the rapid development of sequencing technologies, transcriptome annotation across multiple human cell types and tissues is now available. Accurate transcriptome annotation is critical for understanding the functional as well as the regulatory roles of genomic regions. Current methods for identifying genome-wide active transcription units (TUs) use RNA sequencing (RNA-seq). However, this approach requires large quantities of mRNAs making the identification of highly unstable regulatory RNAs (like microRNA precursors) difficult. As a result of this complexity in identifying inherently unstable TUs, the transcriptome landscape across all cells and tissues remains incomplete. This problem can be alleviated by chromatin-based approaches due to a well-established correlation between transcription and histone modification. Here, I present EPIGENE, a novel chromatin segmentation method for identifying genome-wide active TUs using transcription-associated histone modifications. Unlike existing chromatin segmentation approaches, EPIGENE uses a constrained, semi-supervised multivariate Hidden Markov Model (HMM) that models the observed combination of histone modifications using a product of independent Bernoulli random variables to identify the chromatin state sequence underlying an active TU. Using EPIGENE, I successfully predicted genome-wide TUs across multiple human cell lines. EPIGENE predicted TUs were enriched for RNA Polymerase II (Pol II) at the transcription start site (TSS) and in gene body indicating that they are indeed transcribed. Comprehensive validation using existing annotations revealed that 93% of EPIGENE TUs can be explained by existing gene annotations and 5% of EPIGENE TUs in HepG2 can be explained by microRNA annotations. EPIGENE predicted TUs more precisely compared to existing chromatin segmentation and RNA-seq based approaches across multiple human cell lines. Using EPIGENE, I also identified 232 novel TUs in K562 and 43 novel cell-specific TUs in K562, HepG2, and IMR90, all of which were supported by Pol II ChIP-seq and nascent RNA-seq evidence

Characterization Of Epigenetic Plasticity And Chromatin Dynamics In Cancer Cell Models

Cancer progression is driven by cumulative changes that promote and maintain the malignant phenotype. Epigenetic alterations are central to malignant transformation and to the development of therapy resistance. Changes in DNA methylation, histone acetylation and methylation, noncoding RNA expression and higher-order chromatin structures are epigenetic features of cancer, which are independent of changes in the DNA sequence. Despite the knowledge that these epigenetic alterations disrupt essential pathways that protect cells from uncontrolled growth, how these modifications collectively coordinate cancer gene expression programs remains poorly understood. In this dissertation, I utilize molecular and informatic approaches to define and characterize the genome-wide epigenetic patterns of two important human cancer cell models. I further explore the dynamic alterations of chromatin structure and its interplay with gene regulation in response to therapeutic agents. In the first part of this dissertation, pancreatic ductal adenocarcinoma (PDAC) cell models were used to characterize genome-wide patterns of chromatin structure. The effects of histone acetyltransferase (HAT) inhibitors on chromatin structure patterns were investigated to understand how these potential therapeutics influence the epigenome and gene regulation. Accordingly, HAT inhibitors globally target histone modifications and also impacted specific gene pathways and regulatory domains such as super-enhancers. Overall, the results from this study uncover potential roles for specific epigenomic domains in PDAC cells and demonstrate epigenomic plasticity to HAT inhibitors. In the second part of this dissertation, I investigate the dynamic changes of chromatin structure in response to estrogen signaling over a time-course using Estrogen Receptor (ER) positive breast cancer cell models. Accordingly, I generated genome-wide chromatin contact maps, ER, CTCF and regulatory histone modification profiles and compared and integrated these profiles to determine the temporal patterns of regulatory chromatin compartments. The results reveal that the majority of alterations occur in regions that correspond to active chromatin states, and that dynamic chromatin is linked to genes associated with specific cancer growth and metabolic signaling pathways. To distinguish ER-regulated processes in tamoxifen-sensitive and in tamoxifen-resistant (TAMR) cell models, we determined the corresponding chromatin and gene expression profiles using ER-positive TAMR cancer cell derivatives. Comparison of the patterns revealed characteristic features of estrogen responsiveness and show a global reprogramming of chromatin structure in breast cancer cells with acquired tamoxifen resistance. Taken together, this dissertation reveals novel insight into dynamic epigenomic alterations that occur with extrinsic stimuli and provides insight into mechanisms underlying the therapeutic responses in cancer cells