Systematic classification of non-coding RNAs by epigenomic similarity

BACKGROUND: Even though only 1.5% of the human genome is translated into proteins, recent reports indicate that most of it is transcribed into non-coding RNAs (ncRNAs), which are becoming the subject of increased scientific interest. We hypothesized that examining how different classes of ncRNAs co-localized with annotated epigenomic elements could help understand the functions, regulatory mechanisms, and relationships among ncRNA families. RESULTS: We examined 15 different ncRNA classes for statistically significant genomic co-localizations with cell type-specific chromatin segmentation states, transcription factor binding sites (TFBSs), and histone modification marks using GenomeRunner (http://www.genomerunner.org). P-values were obtained using a Chi-square test and corrected for multiple testing using the Benjamini-Hochberg procedure. We clustered and visualized the ncRNA classes by the strength of their statistical enrichments and depletions. We found piwi-interacting RNAs (piRNAs) to be depleted in regions containing activating histone modification marks, such as H3K4 mono-, di- and trimethylation, H3K27 acetylation, as well as certain TFBSs. piRNAs were further depleted in active promoters, weak transcription, and transcription elongation regions, and enriched in repressed and heterochromatic regions. Conversely, transfer RNAs (tRNAs) were depleted in heterochromatin regions and strongly enriched in regions containing activating H3K4 di- and trimethylation marks, H2az histone variant, and a variety of TFBSs. Interestingly, regions containing CTCF insulator protein binding sites were associated with tRNAs. tRNAs were also enriched in the active, weak and poised promoters and, surprisingly, in regions with repetitive/copy number variations. CONCLUSIONS: Searching for statistically significant associations between ncRNA classes and epigenomic elements permits detection of potential functional and/or regulatory relationships among ncRNA classes, and suggests cell type-specific biological roles of ncRNAs

Epigenomic Profiling of Human CD4+ T Cells Supports a Linear Differentiation Model and Highlights Molecular Regulators of Memory Development

SummaryThe impact of epigenetics on the differentiation of memory T (Tmem) cells is poorly defined. We generated deep epigenomes comprising genome-wide profiles of DNA methylation, histone modifications, DNA accessibility, and coding and non-coding RNA expression in naive, central-, effector-, and terminally differentiated CD45RA+ CD4+ Tmem cells from blood and CD69+ Tmem cells from bone marrow (BM-Tmem). We observed a progressive and proliferation-associated global loss of DNA methylation in heterochromatic parts of the genome during Tmem cell differentiation. Furthermore, distinct gradually changing signatures in the epigenome and the transcriptome supported a linear model of memory development in circulating T cells, while tissue-resident BM-Tmem branched off with a unique epigenetic profile. Integrative analyses identified candidate master regulators of Tmem cell differentiation, including the transcription factor FOXP1. This study highlights the importance of epigenomic changes for Tmem cell biology and demonstrates the value of epigenetic data for the identification of lineage regulators

Comprehensive analysis of the chromatin landscape in Drosophila melanogaster.

Chromatin is composed of DNA and a variety of modified histones and non-histone proteins, which have an impact on cell differentiation, gene regulation and other key cellular processes. Here we present a genome-wide chromatin landscape for Drosophila melanogaster based on eighteen histone modifications, summarized by nine prevalent combinatorial patterns. Integrative analysis with other data (non-histone chromatin proteins, DNase I hypersensitivity, GRO-Seq reads produced by engaged polymerase, short/long RNA products) reveals discrete characteristics of chromosomes, genes, regulatory elements and other functional domains. We find that active genes display distinct chromatin signatures that are correlated with disparate gene lengths, exon patterns, regulatory functions and genomic contexts. We also demonstrate a diversity of signatures among Polycomb targets that include a subset with paused polymerase. This systematic profiling and integrative analysis of chromatin signatures provides insights into how genomic elements are regulated, and will serve as a resource for future experimental investigations of genome structure and function

Integrative methods for analyzing big data in precision medicine

We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of “Big Data” in biology and medicine. These data offer many opportunities to advance precision medicine. We outline key challenges in precision medicine and present recent advances in data integration-based methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, biomarkers discovery, and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face

Genome-wide analysis of DNA methylation topology to understand cell fate

DNA methylation is an epignetic modification associated with gene regulation. It has extensively been studied in the context of small regulatory regions. Yet, not so much is known about large domains characterized by fuzzy methylation patterns, termed Partially Methylated Domains (PMDs). The present thesis comprises PMD analyses in various contexts and provides several new aspects to study DNA methylation. First, a comprehensive analysis of PMDs across a large cohort of WGBS samples was performed, to identify structural and functional features associated with PMDs. A newly developed approach, ChromH3M, was proposed for the analysis and integration of a large spectrum of WGBS data sets. Second, PMDs were found to be indicators of the cellular proliferation history and segmented loss of DNA methylation in PMDs supports the sequential linear differentiation model of memory T-cells. Third, assessment of genome-wide methylation changes in PMDs of Multiple Sclerosis-discordant monozygotic co-twins did not show significant differences, but local changes (DMRs) were identified. Taken together, the outcomes of the presented studies shed light on a so far neglected aspect of DNA methylation, that is PMDs, in different contexts; lineage specialization, differentiation, replication, disease, chromatin organization and gene expression.Die DNA-Methylierung ist eine epigenetische Modi1kation, die funktionell mit der Genregulation verbunden ist. Sie wurde bereits ausführlich im Kontext kleiner regulatorischer Regionen untersucht. Es ist jedoch noch nicht sehr viel bekannt über große Domänen, welche erstmals in WGBS-Daten beschrieben wurden. Sie werden als partiell methylierte Regionen (PMDs) bezeichnet und sind durch das Vorhandensein variabler Methylierungsmuster charakterisiert. Die vorliegende Arbeit umfasst PMD-Analysen in unterschiedlichen Kontexten und liefert verschiedene neue Aspekte zur Untersuchung der DNA-Methylierung. Zuerst wurde eine umfassende Analyse von PMDs in einer großen Kohorte von WGBS-Proben durchgeführt, um strukturelle und funktionelle Merkmale zu identi 1zieren, die mit PMDs assoziert sind. Ein neu entwickelter Ansatz, ChromH3M, wurde für die Analyse und Integration einer großen Kohorte vonWGBS Datensätzen angewandt. Zweitens wurde festgestellt, dass PMDs Indikatoren für die Zellproliferationshistorie sind, und der zu beobachtende graduelle Verlust der globalen DNAMethylierung bei der Differenzierung von T-Gedächtniszellen unterstützt die Hypothese der sequenziellen linearen Differenzierung. Drittens zeigte die Bewertung der genomweiten Methylierungsänderungen in PMDs von Multiple Sklerose-diskordanten monozygoten Zwillingen keine signi1kanten Unterschiede, jedoch wurden lokale Änderungen (DMRs) identi1ziert. Insgesamt geben die Ergebnisse der vorgestellten Studien Aufschluss über einen bislang eher vernachlässigten Aspekt der DNA-Methylierung, d.h. PMDs, in verschiedenen Zusammenhängen: der Festlegung der Zell-entwicklungsbahnen, der Zelldifferenzierung, der Replikation, die Krankheit, der Organisation des Chromatins, sowie der Regulation der Genexpression

Integrated annotation and analysis of genomic features reveal new types of functional elements and large-scale epigenetic phenomena in the developing zebrafish

Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals