Julian Tonti-Filippini

Human DNA methylomes at base resolution show widespread epigenomic differences

DNA cytosine methylation is a central epigenetic modification that has essential roles in cellular processes including genome regulation, development and disease. Here we present the first genome-wide, single-base-resolution maps of methylated cytosines in a mammalian genome, from both human embryonic stem cells and fetal fibroblasts, along with comparative analysis of messenger RNA and small RNA components of the transcriptome, several histone modifications, and sites of DNA–protein interaction for several key regulatory factors. Widespread differences were identified in the composition and patterning of cytosine methylation between the two genomes. Nearly one-quarter of all methylation identified in embryonic stem cells was in a non-CG context, suggesting that embryonic stem cells may use different methylation mechanisms to affect gene regulation. Methylation in non-CG contexts showed enrichment in gene bodies and depletion in protein binding sites and enhancers. Non-CG methylation disappeared upon induced differentiation of the embryonic stem cells, and was restored in induced pluripotent stem cells. We identified hundreds of differentially methylated regions proximal to genes involved in pluripotency and differentiation, and widespread reduced methylation levels in fibroblasts associated with lower transcriptional activity. These reference epigenomes provide a foundation for future studies exploring this key epigenetic modification in human disease and development.

Highly Integrated Single-Base Resolution Maps of the Epigenome in Arabidopsis

Deciphering the multiple layers of epigenetic regulation that control transcription is critical to understanding how plants develop and respond to their environment. Using sequencing-by-synthesis technology we directly sequenced the cytosine methylome (methylC-seq), transcriptome (mRNA-seq), and small RNA transcriptome (smRNA-seq) to generate highly integrated epigenome maps for wild-type Arabidopsis thaliana and mutants defective in DNA methyltransferase or demethylase activity. At single-base resolution we discovered extensive, previously undetected DNA methylation, identified the context and level of methylation at each site, and observed local sequence effects upon methylation state. Deep sequencing of smRNAs revealed a direct relationship between the location of smRNAs and DNA methylation, perturbation of smRNA biogenesis upon loss of CpG DNA methylation, and a tendency for smRNAs to direct strand-specific DNA methylation in regions of RNA-DNA homology. Finally, strand-specific mRNA-seq revealed altered transcript abundance of hundreds of genes, transposons, and unannotated intergenic transcripts upon modification of the DNA methylation state.

Global Epigenomic Reconfiguration During Mammalian Brain Development

Introduction Several lines of evidence point to a key role for dynamic epigenetic changes during brain development, maturation, and learning. DNA methylation (mC) is a stable covalent modification that persists in post-mitotic cells throughout their lifetime, defining their cellular identity. However, the methylation status at each of the ~1 billion cytosines in the genome is potentially an information-rich and flexible substrate for epigenetic modification that can be altered by cellular activity. Indeed, changes in DNA methylation have been implicated in learning and memory, as well as in age-related cognitive decline. However, little is known about the cell type–specific patterning of DNA methylation and its dynamics during mammalian brain development. The DNA methylation landscape of human and mouse neurons is dynamically reconfigured through development. Base-resolution analysis allowed identification of methylation in the CG and CH context (H = A, C, or T). Unlike other differentiated cell types, neurons accumulate substantial mCH during the early years of life, coinciding with the period of synaptogenesis and brain maturation. Methods We performed genome-wide single-base resolution profiling of the composition, patterning, cell specificity, and dynamics of DNA methylation in the frontal cortex of humans and mice throughout their lifespan (MethylC-Seq). Furthermore, we generated base-resolution maps of 5-hydroxymethylcytosine (hmC) in mammalian brains by TAB-Seq at key developmental stages, accompanied by RNA-Seq transcriptional profiling. Results Extensive methylome reconfiguration occurs during development from fetal to young adult. In this period, coincident with synaptogenesis, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. We uncovered surprisingly complex features of brain cell DNA methylation at multiple scales, first by identifying intragenic methylation patterns in neurons and glia that distinguish genes with cell type–specific activity. Second, we report a novel mCH signature that identifies genes escaping X-chromosome inactivation in neurons. Third, we find >100,000 developmentally dynamic and cell type–specific differentially CG-methylated regions that are enriched at putative regulatory regions of the genome. Finally, whole-genome detection of 5-hydroxymethylcytosine (hmC) at single-base resolution revealed that this mark is present in fetal brain cells at locations that lose CG methylation and become activated during development. CG-demethylation at these hmC-poised loci depends on Tet2 activity. Discussion Whole-genome single-base resolution methylcytosine and hydroxymethylcytosine maps revealed profound changes during frontal cortex development in humans and mice. These results extend our knowledge of the unique role of DNA methylation in brain development and function, and offer a new framework for testing the role of the epigenome in healthy function and in pathological disruptions of neural circuits. Overall, brain cell DNA methylation has unique features that are precisely conserved, yet dynamic and cell-type specific. Epigenetic Brainscape Epigenetic modifications and their potential changes during development are of high interest, but few studies have characterized such differences. Lister et al. (1237905, published online 4 July; see the Perspective by Gabel and Greenberg) report whole-genome base-resolution analysis of DNA cytosine modifications and transcriptome analysis in the frontal cortex of human and mouse brains at multiple developmental stages. The high-resolution mapping of DNA cytosine methylation (5mC) and one of its oxidation derivatives (5hmC) at key developmental stages provides a comprehensive resource covering the temporal dynamics of these epigenetic modifications in neurons compared to glia. The data suggest that methylation marks are dynamic during brain development in both humans and mice. A genome-wide map shows that DNA methylation in neurons and glial cells changes during development in humans and mice. [Also see Perspective by Gabel and Greenberg] DNA methylation is implicated in mammalian brain development and plasticity underlying learning and memory. We report the genome-wide composition, patterning, cell specificity, and dynamics of DNA methylation at single-base resolution in human and mouse frontal cortex throughout their lifespan. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis. During this period, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. Moreover, we found an mCH signature that identifies genes escaping X-chromosome inactivation. Last, whole-genome single-base resolution 5-hydroxymethylcytosine (hmC) maps revealed that hmC marks fetal brain cell genomes at putative regulatory regions that are CG-demethylated and activated in the adult brain and that CG demethylation at these hmC-poised loci depends on Tet2 activity.

Experimental Analysis of the Arabidopsis Mitochondrial Proteome Highlights Signaling and Regulatory Components, Provides Assessment of Targeting Prediction Programs, and Indicates Plant-Specific Mitochondrial Proteins

A novel insight into Arabidopsis mitochondrial function was revealed from a large experimental proteome derived by liquid chromatography–tandem mass spectrometry. Within the experimental set of 416 identified proteins, a significant number of low-abundance proteins involved in DNA synthesis, transcriptional regulation, protein complex assembly, and cellular signaling were discovered. Nearly 20% of the experimentally identified proteins are of unknown function, suggesting a wealth of undiscovered mitochondrial functions in plants. Only approximately half of the experimental set is predicted to be mitochondrial by targeting prediction programs, allowing an assessment of the benefits and limitations of these programs in determining plant mitochondrial proteomes. Maps of putative orthology networks between yeast, human, and Arabidopsis mitochondrial proteomes and the Rickettsia prowazekii proteome provide detailed insights into the divergence of the plant mitochondrial proteome from those of other eukaryotes. These show a clear set of putative cross-species orthologs in the core metabolic functions of mitochondria, whereas considerable diversity exists in many signaling and regulatory functions.

SUBA: the Arabidopsis Subcellular Database

Knowledge of protein localisation contributes towards our understanding of protein function and of biological inter-relationships. A variety of experimental methods are currently being used to produce localisation data that need to be made accessible in an integrated manner. Chimeric fluorescent fusion proteins have been used to define subcellular localisations with at least 1100 related experiments completed in Arabidopsis. More recently, many studies have employed mass spectrometry to undertake proteomic surveys of subcellular components in Arabidopsis yielding localisation information for approximately 2600 proteins. Further protein localisation information may be obtained from other literature references to analysis of locations (AmiGO: approximately 900 proteins), location information from Swiss-Prot annotations (approximately 2000 proteins); and location inferred from gene descriptions (approximately 2700 proteins). Additionally, an increasing volume of available software provides location prediction information for proteins based on amino acid sequence. We have undertaken to bring these various data sources together to build SUBA, a SUBcellular location database for Arabidopsis proteins. The localisation data in SUBA encompasses 10 distinct subcellular locations, >6743 non-redundant proteins and represents the proteins encoded in the transcripts responsible for 51% of Arabidopsis expressed sequence tags. The SUBA database provides a powerful means by which to assess protein subcellular localisation in Arabidopsis (http://www.suba.bcs.uwa.edu.au).

Combining Experimental and Predicted Datasets for Determination of the Subcellular Location of Proteins in Arabidopsis

Substantial experimental datasets defining the subcellular location of Arabidopsis (Arabidopsis thaliana) proteins have been reported in the literature in the form of organelle proteomes built from mass spectrometry data (approximately 2,500 proteins). Subcellular location for specific proteins has also been published based on imaging of chimeric fluorescent fusion proteins in intact cells (approximately 900 proteins). Further, the more diverse history of biochemical determination of subcellular location is stored in the entries of the Swiss-Prot database for the products of many Arabidopsis genes (approximately 1,800 proteins). Combined with the range of bioinformatic targeting prediction tools and comparative genomic analysis, these experimental datasets provide a powerful basis for defining the final location of proteins within the wide variety of subcellular structures present inside Arabidopsis cells. We have analyzed these published experimental and prediction data to answer a range of substantial questions facing researchers about the veracity of these approaches to determining protein location and their interrelatedness. We have merged these data to form the subcellular location database for Arabidopsis proteins (SUBA), providing an integrated understanding of protein location, encompassing the plastid, mitochondrion, peroxisome, nucleus, plasma membrane, endoplasmic reticulum, vacuole, Golgi, cytoskeleton structures, and cytosol (www.suba.bcs.uwa.edu.au). This includes data on more than 4,400 nonredundant Arabidopsis protein sequences. We also provide researchers with an online resource that may be used to query protein sets or protein families and determine whether predicted or experimental location data exist; to analyze the nature of contamination between published proteome sets; and/or for building theoretical subcellular proteomes in Arabidopsis using the latest experimental data.

Characterization of the Preprotein and Amino Acid Transporter Gene Family in Arabidopsis

Seventeen loci encode proteins of the preprotein and amino acid transporter family in Arabidopsis (Arabidopsis thaliana). Some of these genes have arisen from recent duplications and are not in annotated duplicated regions of the Arabidopsis genome. In comparison to a number of other eukaryotic organisms, this family of proteins has greatly expanded in plants, with 24 loci in rice (Oryza sativa). Most of the Arabidopsis and rice genes are orthologous, indicating expansion of this family before monocot and dicot divergence. In vitro protein uptake assays, in vivo green fluorescent protein tagging, and immunological analyses of selected proteins determined either mitochondrial or plastidic localization for 10 and six proteins, respectively. The protein encoded by At5g24650 is targeted to both mitochondria and chloroplasts and, to our knowledge, is the first membrane protein reported to be targeted to mitochondria and chloroplasts. Three genes encoded translocase of the inner mitochondrial membrane (TIM)17-like proteins, three TIM23-like proteins, and three outer envelope protein16-like proteins in Arabidopsis. The identity of Arabidopsis TIM22-like proteins is most likely a protein encoded by At3g10110/At1g18320, based on phylogenetic analysis, subcellular localization, and complementation of a yeast (Saccharomyces cerevisiae) mutant and coexpression analysis. The lack of a preprotein and amino acid transporter domain in some proteins, localization in mitochondria, plastids, or both, variation in gene structure, and the differences in expression profiles indicate that the function of this family has diverged in plants beyond roles in protein translocation.

What can we do with 1000 plastid genomes

The plastid genome of plants is the smallest and most gene-rich of the three genomes in each cell and the one generally present in the highest copy number. As a result, obtaining plastid DNA sequence is a particularly cost-effective way of discovering genetic information about a plant. Until recently, the sequence information gathered in this way was generally limited to small portions of the genome amplified by polymerase chain reaction, but recent advances in sequencing technology have stimulated a substantial rate of increase in the sequencing of complete plastid genomes. Within the last year, the number of complete plastid genomes accessible in public sequence repositories has exceeded 1000. This sudden flood of data raises numerous challenges in data analysis and interpretation, but also offers the keys to potential insights across large swathes of plant biology. We examine what has been learnt so far, what more could be learnt if we look at the data in the right way, and what we might gain from the tens of thousands more genome sequences that will surely arrive in the next few years. The most exciting new discoveries are likely to be made at the interdisciplinary interfaces between molecular biology and ecology.

STAR: an integrated solution to management and visualization of sequencing data

MOTIVATION Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data. RESULTS STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data. AVAILABILITY AND IMPLEMENTATION STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser.