Depletion of Mettl3 in cholinergic neurons causes adult-onset neuromuscular degeneration

Motor neuron (MN) demise is a hallmark of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Post-transcriptional gene regulation can control RNA's fate, and defects in RNA processing are critical determinants of MN degeneration. N6-methyladenosine (m6A) is a post-transcriptional RNA modification that controls diverse aspects of RNA metabolism. To assess the m6A requirement in MNs, we depleted the m6A methyltransferase-like 3 (METTL3) in cells and mice. METTL3 depletion in embryonic stem cell-derived MNs has profound and selective effects on survival and neurite outgrowth. Mice with cholinergic neuron-specific METTL3 depletion display a progressive decline in motor behavior, accompanied by MN loss and muscle denervation, culminating in paralysis and death. Reader proteins convey m6A effects, and their silencing phenocopies METTL3 depletion. Among the m6A targets, we identified transactive response DNA-binding protein 43 (TDP-43) and discovered that its expression is under epitranscriptomic control. Thus, impaired m6A signaling disrupts MN homeostasis and triggers neurodegeneration conceivably through TDP-43 deregulation.

Comprehensive transcriptome analysis reveals altered mRNA splicing and post-transcriptional changes in the aged mouse brain

A comprehensive understanding of molecular changes during brain aging is essential to mitigate cognitive decline and delay neurodegenerative diseases. The interpretation of mRNA alterations during brain aging is influenced by the health and age of the animal cohorts studied. Here, we carefully consider these factors and provide an in-depth investigation of mRNA splicing and dynamics in the aging mouse brain, combining short- and long-read sequencing technologies with extensive bioinformatic analyses. Our findings encompass a spectrum of age-related changes, including differences in isoform usage, decreased mRNA dynamics and a module showing increased expression of neuronal genes. Notably, our results indicate a reduced abundance of mRNA isoforms leading to nonsense-mediated RNA decay and suggest a regulatory role for RNA-binding proteins, indicating that their regulation may be altered leading to the reshaping of the aged brain transcriptome. Collectively, our study highlights the importance of studying mRNA splicing events during brain aging.

Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing

N6-methyladenosine (m6A) is the most abundant internal eukaryotic mRNA modification, and is involved in the regulation of various biological processes. Direct Nanopore sequencing of native RNA (dRNA-seq) emerged as a leading approach for its identification. Several software were published for m6A detection and there is a strong need for independent studies benchmarking their performance on data from different species, and against various reference datasets. Moreover, a computational workflow is needed to streamline the execution of tools whose installation and execution remains complicated. We developed NanOlympicsMod, a Nextflow pipeline exploiting containerized technology for comparing 14 tools for m6A detection on dRNA-seq data. NanOlympicsMod was tested on dRNA-seq data generated from in vitro (un)modified synthetic oligos. The m6A hits returned by each tool were compared to the m6A position known by design of the oligos. In addition, NanOlympicsMod was used on dRNA-seq datasets from wild-type and m6A-depleted yeast, mouse and human, and each tool's hits were compared to reference m6A sets generated by leading orthogonal methods. The performance of the tools markedly differed across datasets, and methods adopting different approaches showed different preferences in terms of precision and recall. Changing the stringency cut-offs allowed for tuning the precision-recall trade-off towards user preferences. Finally, we determined that precision and recall of tools are markedly influenced by sequencing depth, and that additional sequencing would likely reveal additional m6A sites. Thanks to the possibility of including novel tools, NanOlympicsMod will streamline the benchmarking of m6A detection tools on dRNA-seq data, improving future RNA modification characterization.

Identification, semantic annotation and comparison of combinations of functional elements in multiple biological conditions

MOTIVATION

Approaches such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) represent the standard for the identification of binding sites of DNA-associated proteins, including transcription factors and histone marks. Public repositories of omics data contain a huge number of experimental ChIP-seq data, but their reuse and integrative analysis across multiple conditions remain a daunting task.

RESULTS

We present the Combinatorial and Semantic Analysis of Functional Elements (CombSAFE), an efficient computational method able to integrate and take advantage of the valuable and numerous, but heterogeneous, ChIP-seq data publicly available in big data repositories. Leveraging natural language processing techniques, it integrates omics data samples with semantic annotations from selected biomedical ontologies; then, using hidden Markov models, it identifies combinations of static and dynamic functional elements throughout the genome for the corresponding samples. CombSAFE allows analyzing the whole genome, by clustering patterns of regions with similar functional elements and through enrichment analyses to discover ontological terms significantly associated with them. Moreover, it allows comparing functional states of a specific genomic region to analyze their different behavior throughout the various semantic annotations. Such findings can provide novel insights by identifying unexpected combinations of functional elements in different biological conditions.

AVAILABILITY AND IMPLEMENTATION

The Python implementation of the CombSAFE pipeline is freely available for non-commercial use at: https://github.com/DEIB-GECO/CombSAFE.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Computational methods for RNA modification detection from nanopore direct RNA sequencing data

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms.

New insight into the catalytic -dependent and -independent roles of METTL3 in sustaining aberrant translation in chronic myeloid leukemia

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm caused by the presence of tyrosine kinase BCR-ABL1 fusion protein, which deregulate transcription and mRNA translation. Tyrosine kinase inhibitors (TKIs) are the first-choice treatment. However, resistance to TKIs remains a challenge to cure CML patients. Here, we reveal that the m⁶A methyltransferase complex METTL3/METTL14 is upregulated in CML patients and that is required for proliferation of primary CML cells and CML cell lines sensitive and resistant to the TKI imatinib. We demonstrate that depletion of METTL3 strongly impairs global translation efficiency. In particular, our data show that METTL3 is crucial for the expression of genes involved in ribosome biogenesis and translation. Specifically, we found that METTL3 directly regulates the level of PES1 protein identified as an oncogene in several tumors. We propose a model in which nuclear METTL3/METTL14 methyltransferase complex modified nascent transcripts whose translation is enhanced by cytoplasmic localization of METTL3, independently from its catalytic activity. In conclusion, our results point to METTL3 as a novel relevant oncogene in CML and as a promising therapeutic target for TKI resistant CML.

Dynamics of transcriptional and post-transcriptional regulation

Despite gene expression programs being notoriously complex, RNA abundance is usually assumed as a proxy for transcriptional activity. Recently developed approaches, able to disentangle transcriptional and post-transcriptional regulatory processes, have revealed a more complex scenario. It is now possible to work out how synthesis, processing and degradation kinetic rates collectively determine the abundance of each gene's RNA. It has become clear that the same transcriptional output can correspond to different combinations of the kinetic rates. This underscores the fact that markedly different modes of gene expression regulation exist, each with profound effects on a gene's ability to modulate its own expression. This review describes the development of the experimental and computational approaches, including RNA metabolic labeling and mathematical modeling, that have been disclosing the mechanisms underlying complex transcriptional programs. Current limitations and future perspectives in the field are also discussed.

Translation is required for miRNA-dependent decay of endogenous transcripts

Post-transcriptional repression of gene expression by miRNAs occurs through transcript destabilization or translation inhibition. mRNA decay is known to account for most miRNA-dependent repression. However, because transcript decay occurs co-translationally, whether target translation is a requirement for miRNA-dependent transcript destabilization remains unknown. To decouple these two molecular processes, we used cytosolic long noncoding RNAs (lncRNAs) as models for endogenous transcripts that are not translated. We show that, despite interacting with the miRNA-loaded RNA-induced silencing complex, the steady-state abundance and decay rates of these transcripts are minimally affected by miRNA loss. To further validate the apparent requirement of translation for miRNA-dependent decay, we fused two lncRNA candidates to the 3'-end of a protein-coding gene reporter and found this results in their miRNA-dependent destabilization. Further analysis revealed that the few natural lncRNAs whose levels are regulated by miRNAs in mESCs tend to associate with translating ribosomes, and possibly represent misannotated micropeptides, further substantiating the necessity of target translation for miRNA-dependent transcript decay. In summary, our analyses suggest that translation is required for miRNA-dependent transcript destabilization, and demonstrate that the levels of coding and noncoding transcripts are differently affected by miRNAs.

Identification of Genes Post-Transcriptionally Regulated from RNA-seq: The Case Study of Liver Hepatocellular Carcinoma

The field of transcriptional regulation generally assumes that changes in transcripts levels reflect changes in transcriptional status of the corresponding gene. While this assumption might hold true for a large population of transcripts, a considerable and still unrecognized fraction of the variation might involve other steps of the RNA lifecycle, that is the processing of the premature RNA, and degradation of the mature RNA. Discrimination between these layers requires complementary experimental techniques, such as RNA metabolic labeling or block of transcription experiments. Nonetheless, the analysis of the premature and mature RNA, derived from intronic and exonic read counts in RNA-seq data, allows distinguishing between transcriptionally and post-transcriptionally regulated genes, although not recognizing the specific step involved in the post-transcriptional response, that is processing, degradation, or a combination of the two. We illustrate how the INSPEcT R/Bioconductor package could be used to infer post-transcriptional regulation in TCGA RNA-seq samples for Hepatocellular Carcinoma.

Genome-wide dynamics of RNA synthesis, processing, and degradation without RNA metabolic labeling

The quantification of the kinetic rates of RNA synthesis, processing, and degradation are largely based on the integrative analysis of total and nascent transcription, the latter being quantified through RNA metabolic labeling. We developed INSPEcT−, a computational method based on the mathematical modeling of premature and mature RNA expression that is able to quantify kinetic rates from steady-state or time course total RNA-seq data without requiring any information on nascent transcripts. Our approach outperforms available solutions, closely recapitulates the kinetic rates obtained through RNA metabolic labeling, improves the ability to detect changes in transcript half-lives, reduces the cost and complexity of the experiments, and can be adopted to study experimental conditions in which nascent transcription cannot be readily profiled. Finally, we applied INSPEcT− to the characterization of post-transcriptional regulation landscapes in dozens of physiological and disease conditions. This approach was included in the INSPEcT Bioconductor package, which can now unveil RNA dynamics from steady-state or time course data, with or without the profiling of nascent RNA.

INSPEcT-GUI Reveals the Impact of the Kinetic Rates of RNA Synthesis, Processing, and Degradation, on Premature and Mature RNA Species

The abundance of RNA species and their response to perturbations are set by the kinetics rates of RNA synthesis, processing, and degradation. However, the visualization, interpretation, and manipulation of these data require familiarity with mathematical modeling and command line tools. INSPEcT-GUI is an R-Shiny interface that allows researchers without specific training to effortlessly explore how the fine kinetic regulation of the RNA life cycle can shape gene expression programs. In particular, it allows to: (i) interactively visualize gene-level RNA dynamics; (ii) refine the model fit of experimental data; (iii) test alternative regulatory models; (iv) explore, independently from the availability of data, how the combined action of the RNA kinetic rates impacts on premature and mature RNA. INSPEcT-GUI is freely available within the R/Bioconductor package INSPEcT at http://bioconductor.org/packages/INSPEcT/. An HTML vignette including documentation on the tool startup and usage, executable examples, and a video demonstration, are available at: http://bioconductor.org/packages/release/bioc/vignettes/INSPEcT/inst/doc/INSPEcT_GUI.html.

Direct RNA Sequencing for the Study of Synthesis, Processing, and Degradation of Modified Transcripts

It has been known for a few decades that transcripts can be marked by dozens of different modifications. Yet, we are just at the beginning of charting these marks and understanding their functional impact. High-quality methods were developed for the profiling of some of these marks, and approaches to finely study their impact on specific phases of the RNA life-cycle are available, including RNA metabolic labeling. Thanks to these improvements, the most abundant marks, including N6-methyladenosine, are emerging as important determinants of the fate of marked RNAs. However, we still lack approaches to directly study how the set of marks for a given RNA molecule shape its fate. In this perspective, we first review current leading approaches in the field. Then, we propose an experimental and computational setup, based on direct RNA sequencing and mathematical modeling, to decipher the functional consequences of RNA modifications on the fate of individual RNA molecules and isoforms.

A dual role of dLsd1 in oogenesis: regulating developmental genes and repressing transposons

The histone demethylase LSD1 is a key chromatin regulator that is often deregulated in cancer. Its ortholog, dLsd1 plays a crucial role in Drosophila oogenesis; however, our knowledge of dLsd1 function is insufficient to explain its role in the ovary. Here, we have performed genome-wide analysis of dLsd1 binding in the ovary, and we document that dLsd1 is preferentially associated to the transcription start site of developmental genes. We uncovered an unanticipated interplay between dLsd1 and the GATA transcription factor Serpent and we report an unexpected role for Serpent in oogenesis. Besides, our transcriptomic data show that reducing dLsd1 levels results in ectopic transposable elements (TE) expression correlated with changes in H3K4me2 and H3K9me2 at TE loci. In addition, our results suggest that dLsd1 is required for Piwi dependent TE silencing. Hence, we propose that dLsd1 plays crucial roles in establishing specific gene expression programs and in repressing transposons during oogenesis.

Ontology-driven integrative analysis of omics data through Onassis

Public repositories of large-scale omics datasets represent a valuable resource for researchers. In fact, data re-analysis can either answer novel questions or provide critical data able to complement in-house experiments. However, despite the development of standards for the compilation of metadata, the identification and organization of samples still constitutes a major bottleneck hampering data reuse. We introduce Onassis, an R package within the Bioconductor environment providing key functionalities of Natural Language Processing (NLP) tools. Leveraging biomedical ontologies, Onassis greatly simplifies the association of samples from large-scale repositories to their representation in terms of ontology-based annotations. Moreover, through the use of semantic similarity measures, Onassis hierarchically organizes the datasets of interest, thus supporting the semantically aware analysis of the corresponding omics data. In conclusion, Onassis leverages NLP techniques, biomedical ontologies, and the R statistical framework, to identify, relate, and analyze datasets from public repositories. The tool was tested on various large-scale datasets, including compendia of gene expression, histone marks, and DNA methylation, illustrating how it can facilitate the integrative analysis of various omics data.

An early Myc-dependent transcriptional program orchestrates cell growth during B-cell activation

Upon activation, lymphocytes exit quiescence and undergo substantial increases in cell size, accompanied by activation of energy-producing and anabolic pathways, widespread chromatin decompaction, and elevated transcriptional activity. These changes depend upon prior induction of the Myc transcription factor, but how Myc controls them remains unclear. We addressed this issue by profiling the response to LPS stimulation in wild-type and c-myc-deleted primary mouse B-cells. Myc is rapidly induced, becomes detectable on virtually all active promoters and enhancers, but has no direct impact on global transcriptional activity. Instead, Myc contributes to the swift up- and down-regulation of several hundred genes, including many known regulators of the aforementioned cellular processes. Myc-activated promoters are enriched for E-box consensus motifs, bind Myc at the highest levels, and show enhanced RNA Polymerase II recruitment, the opposite being true at down-regulated loci. Remarkably, the Myc-dependent signature identified in activated B-cells is also enriched in Myc-driven B-cell lymphomas: hence, besides modulation of new cancer-specific programs, the oncogenic action of Myc may largely rely on sustained deregulation of its normal physiological targets.

m6A RNA modification and its writer/reader VIRMA/YTHDF3 in testicular germ cell tumors: a role in seminoma phenotype maintenance

BACKGROUND

Covalent RNA modifications, such as N-6-methyladenosine (m⁶A), have been associated with various biological processes, but their role in cancer remains largely unexplored. m⁶A dynamics depends on specific enzymes whose deregulation may also impact in tumorigenesis. Herein, we assessed the differential abundance of m⁶A, its writer VIRMA and its reader YTHDF3, in testicular germ cell tumors (TGCTs), looking for clinicopathological correlates.

METHODS

In silico analysis of TCGA data disclosed altered expression of VIRMA (52%) and YTHDF3 (48%), prompting subsequent validation. Formalin-fixed paraffin-embedded tissues from 122 TGCTs (2005-2016) were selected. RNA extraction, cDNA synthesis and real-time qPCR (Taqman assays) for VIRMA and YTHDF3 were performed, as well as immunohistochemistry for VIRMA, YTHDF3 and m⁶A, for staining intensity assessment. Associations between categorical variables were assessed using Chi square and Fisher's exact test. Distribution of continuous variables between groups was compared using the nonparametric Mann-Whitney and Kruskal-Wallis tests. Biomarker performance was assessed through receiver operating characteristics (ROC) curve construction and a cut-off was established by Youden's index method. Statistical significance was set at p < 0.05.

RESULTS

In our cohort, VIRMA and YTHDF3 mRNA expression levels differed among TGCT subtypes, with Seminomas (SEs) depicting higher levels than Non-Seminomatous tumors (NSTs) (p < 0.01 for both). A positive correlation was found between VIRMA and YTHDF3 expression levels. VIRMA discriminated SEs from NSTs with AUC = 0.85 (Sensitivity 77.3%, Specificity 81.1%, PPV 71.6%, NPV 85.3%, Accuracy 79.7%). Immunohistochemistry paralleled transcript findings, as patients with strong m⁶A immunostaining intensity depicted significantly higher VIRMA mRNA expression levels and stronger VIRMA immunoexpression intensity (p < 0.001 and p < 0.01, respectively).

CONCLUSION

Abundance of m⁶A and expression of VIRMA/YTHDF3 were different among TGCT subtypes, with higher levels in SEs, suggesting a contribution to SE phenotype maintenance. VIRMA and YTHDF3 might cooperate in m⁶A establishment in TGCTs, and their transcript levels accurately discriminate between SEs and NSTs, constituting novel candidate biomarkers for patient management.

m6A-Dependent RNA Dynamics in T Cell Differentiation

N6-methyladenosine (m6A) is the most abundant RNA modification. It has been involved in the regulation of RNA metabolism, including degradation and translation, in both physiological and disease conditions. A recent study showed that m6A-mediated degradation of key transcripts also plays a role in the control of T cells homeostasis and IL-7 induced differentiation. We re-analyzed the omics data from that study and, through the integrative analysis of total and nascent RNA-seq data, we were able to comprehensively quantify T cells RNA dynamics and how these are affected by m6A depletion. In addition to the expected impact on RNA degradation, we revealed a broader effect of m6A on RNA dynamics, which included the alteration of RNA synthesis and processing. Altogether, the combined action of m6A on all major steps of the RNA life-cycle closely re-capitulated the observed changes in the abundance of premature and mature RNA species. Ultimately, our re-analysis extended the findings of the initial study, focused on RNA stability, and proposed a yet unappreciated role for m6A in RNA synthesis and processing dynamics.

DNA methylation dynamics during embryonic development and postnatal maturation of the mouse auditory sensory epithelium

The inner ear is a complex structure responsible for hearing and balance, and organ pathology is associated with deafness and balance disorders. To evaluate the role of epigenomic dynamics, we performed whole genome bisulfite sequencing at key time points during the development and maturation of the mouse inner ear sensory epithelium (SE). Our single-nucleotide resolution maps revealed variations in both general characteristics and dynamics of DNA methylation over time. This allowed us to predict the location of non-coding regulatory regions and to identify several novel candidate regulatory factors, such as Bach2, that connect stage-specific regulatory elements to molecular features that drive the development and maturation of the SE. Constructing in silico regulatory networks around sites of differential methylation enabled us to link key inner ear regulators, such as Atoh1 and Stat3, to pathways responsible for cell lineage determination and maturation, such as the Notch pathway. We also discovered that a putative enhancer, defined as a low methylated region (LMR), can upregulate the GJB6 gene and a neighboring non-coding RNA. The study of inner ear SE methylomes revealed novel regulatory regions in the hearing organ, which may improve diagnostic capabilities, and has the potential to guide the development of therapeutics for hearing loss by providing multiple intervention points for manipulation of the auditory system.

Positioning Europe for the EPITRANSCRIPTOMICS challenge

The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20 years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery that development, ageing, and stem-cell dependent regeneration but also several diseases including cancer are largely controlled by the epigenetic state of cells. Consequently, this research has already led to the first FDA approved drugs that exploit the gained knowledge to combat disease. In recent years, the ~150 modifications found in RNA have come to the focus of intense research. Here we provide a perspective on necessary and expected developments in the fast expanding area of RNA modifications, termed epitranscriptomics.

Identification of Differentially Methylated Regions in the Genome of Arabidopsis thaliana

DNA methylation profiling in the epigenome of Arabidopsis thaliana (Arabidopsis) has provided great insights in the role of this epigenetic mark for the regulation of transcription in plants, and is often based on high-throughput sequencing. The analysis of these data involves a series of steps including quality checks, filtering, alignment, identification of methyl-cytosines, and the identification of differentially methylated regions. This chapter outlines the computational methodology required to profile genome-wide differential methylation patterns based on publicly available Arabidopsis base-resolution bisulfite sequencing data. The methylPipe Bioconductor package is adopted for the identification of the differentially methylated regions, and all the steps from the raw data to the required input are described in detail.

Ontology-based annotations and semantic relations in large-scale (epi)genomics data

Public repositories of large-scale biological data currently contain hundreds of thousands of experiments, including high-throughput sequencing and microarray data. The potential of using these resources to assemble data sets combining samples previously not associated is vastly unexplored. This requires the ability to associate samples with clear annotations and to relate experiments matched with different annotation terms. In this study, we illustrate the semantic annotation of Gene Expression Omnibus samples metadata using concepts from biomedical ontologies, focusing on the association of thousands of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) samples with a given target, tissue and disease state. Next, we demonstrate the feasibility of quantitatively measuring the semantic similarity between different samples, with the aim of combining experiments associated with the same or similar semantic annotations, thus allowing the generation of large data sets without the need of additional experiments. We compared tools based on Unified Medical Language System with tools that use topic-specific ontologies, showing that the second approach outperforms the first both in the annotation process and in the computation of semantic similarity measures. Finally, we demonstrated the potential of this approach by identifying semantically homogeneous groups of ChIP-seq samples targeting the Myc transcription factor, and expanding this data set with semantically coherent epigenetic samples. The semantic information of these data sets proved to be coherent with the ChIP-seq signal and with the current knowledge about this transcription factor.

Mycobacterium tuberculosis exploits the formation of new blood vessels for its dissemination

The mechanisms by which the airborne pathogen Mycobacterium tuberculosis spreads within the lung and leaves its primary niche to colonize other organs, thus inducing extrapulmonary forms of tuberculosis (TB) in humans, remains poorly understood. Herein, we used a transcriptomic approach to investigate the host cell gene expression profile in M. tuberculosis-infected human macrophages (ΜΦ). We identified 33 genes, encoding proteins involved in angiogenesis, for which the expression was significantly modified during infection, and we show that the potent angiogenic factor VEGF is secreted by M. tuberculosis-infected ΜΦ, in an RD1-dependent manner. In vivo these factors promote the formation of blood vessels in murine models of the disease. Inhibiting angiogenesis, via VEGF inactivation, abolished mycobacterial spread from the infection site. In accordance with our in vitro and in vivo results, we show that the level of VEGF in TB patients is elevated and that endothelial progenitor cells are mobilized from the bone marrow. These results strongly strengthen the most recent data suggesting that mycobacteria take advantage of the formation of new blood vessels to disseminate.

Integrated Systems for NGS Data Management and Analysis: Open Issues and Available Solutions

Next-generation sequencing (NGS) technologies have deeply changed our understanding of cellular processes by delivering an astonishing amount of data at affordable prices; nowadays, many biology laboratories have already accumulated a large number of sequenced samples. However, managing and analyzing these data poses new challenges, which may easily be underestimated by research groups devoid of IT and quantitative skills. In this perspective, we identify five issues that should be carefully addressed by research groups approaching NGS technologies. In particular, the five key issues to be considered concern: (1) adopting a laboratory management system (LIMS) and safeguard the resulting raw data structure in downstream analyses; (2) monitoring the flow of the data and standardizing input and output directories and file names, even when multiple analysis protocols are used on the same data; (3) ensuring complete traceability of the analysis performed; (4) enabling non-experienced users to run analyses through a graphical user interface (GUI) acting as a front-end for the pipelines; (5) relying on standard metadata to annotate the datasets, and when possible using controlled vocabularies, ideally derived from biomedical ontologies. Finally, we discuss the currently available tools in the light of these issues, and we introduce HTS-flow, a new workflow management system conceived to address the concerns we raised. HTS-flow is able to retrieve information from a LIMS database, manages data analyses through a simple GUI, outputs data in standard locations and allows the complete traceability of datasets, accompanying metadata and analysis scripts.

LowMACA: exploiting protein family analysis for the identification of rare driver mutations in cancer

Background

The increasing availability of resequencing data has led to a better understanding of the most important genes in cancer development. Nevertheless, the mutational landscape of many tumor types is heterogeneous and encompasses a long tail of potential driver genes that are systematically excluded by currently available methods due to the low frequency of their mutations. We developed LowMACA (Low frequency Mutations Analysis via Consensus Alignment), a method that combines the mutations of various proteins sharing the same functional domains to identify conserved residues that harbor clustered mutations in multiple sequence alignments. LowMACA is designed to visualize and statistically assess potential driver genes through the identification of their mutational hotspots.

Results

We analyzed the Ras superfamily exploiting the known driver mutations of the trio K-N-HRAS, identifying new putative driver mutations and genes belonging to less known members of the Rho, Rab and Rheb subfamilies. Furthermore, we applied the same concept to a list of known and candidate driver genes, and observed that low confidence genes show similar patterns of mutation compared to high confidence genes of the same protein family.

Conclusions

LowMACA is a software for the identification of gain-of-function mutations in putative oncogenic families, increasing the amount of information on functional domains and their possible role in cancer. In this context LowMACA emphasizes the role of genes mutated at low frequency otherwise undetectable by classical single gene analysis.

LowMACA is an R package available at http://www.bioconductor.org/packages/release/bioc/html/LowMACA.html. It is also available as a GUI standalone downloadable at: https://cgsb.genomics.iit.it/wiki/projects/LowMACA

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0935-7) contains supplementary material, which is available to authorized users.

Degradation dynamics of microRNAs revealed by a novel pulse-chase approach

The regulation of miRNAs is critical to the definition of cell identity and behavior in normal physiology and disease. To date, the dynamics of miRNA degradation and the mechanisms involved in remain largely obscure, in particular, in higher organisms. Here, we developed a pulse-chase approach based on metabolic RNA labeling to calculate miRNA decay rates at genome-wide scale in mammalian cells. Our analysis revealed heterogeneous miRNA half-lives, with many species behaving as stable molecules (T_1/2 > 24 h), while others, including passenger miRNAs and a number (25/129) of guide miRNAs, are quickly turned over (T_1/2 = 4–14 h). Decay rates were coupled with other features, including genomic organization, transcription rates, structural heterogeneity (isomiRs), and target abundance, measured through quantitative experimental approaches. This comprehensive analysis highlighted functional mechanisms that mediate miRNA degradation, as well as the importance of decay dynamics in the regulation of the miRNA pool under both steady-state conditions and during cell transitions.

Abstract A47: Gene regulation by Myc during B cell activation

Myc is required for the response of cells to proliferative stimuli, as shown for example in fibroblasts or B-cells. Cellular activation entails the regulation of specific transcriptional programs concomitant with a general increase in RNA production (also termed “amplification”), which will need to be carefully disentangled for a full understanding of the mitogenic response. Upon activation of quiescent fibroblasts with serum, c-myc is rapidly induced, and is required for the subsequent activation of a set of ca. 300 genes (Myc-Dependent Serum Response, or MDSR genes) in the early-mid G1 phase of the cell cycle (1). This is followed by RNA amplification, concomitant with the G1-S transition (2). Deletion of the c-myc gene prior to serum stimulation led to a loss of all of these responses: these data indicated that Myc primarily acts to selectively regulate specific gene programs, with RNA amplification occurring as a secondary consequence (2). This is in apparent contrast with previous studies on B-cells and tumors, in which Myc was proposed to directly drive transcriptional amplification at all active loci (3, 4). Here, we addressed Myc-dependent responses in primary mouse B-cells, based on conditional deletion of c-myc followed by LPS stimulation. Our data indicate that, as in fibroblasts, a discrete set of Myc-dependent genes can be identified in B-cells: the response of these genes occurs prior to general RNA amplification, and is not entirely attributable to overt promoter/enhancer invasion by Myc. Together with our previous studies (see poster by A. Sabò et al.) (2), these data provide a unifying view of Myc' s action in different cell types, with amplification occurring as an indirect effect, following from the action of specific Myc-target genes on cellular physiology and metabolism. Systematic work is needed to unravel which of the numerous Myc-regulated genes are critical in mediating this chain of events.

References:

1. Perna D, et al. (2012) Genome-wide mapping of Myc binding and gene regulation in serum-stimulated fibroblasts. Oncogene 31, 1695-1709.

2. Sabo A, et al. (2014) Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis. Nature 511, 488-492.

3. Nie Z, et al. (2012) c-Myc is a universal amplifier of expressed genes in lymphocytes and embryonic stem cells. Cell 151, 68-79.

4. Lin CY, et al. (2012) Transcriptional amplification in tumor cells with elevated c-Myc. Cell 151, 56-67.

Citation Format: Alessandra Tesi, Arianna Sabò, Valerio Bianchi, Marco Morelli, Mattia Pelizzola, Bruno Amati. Gene regulation by Myc during B cell activation. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr A47.

Abstract B10: Genome-wide analysis of p53 transcriptional programs in Myc-induced lymphomas

Oncogenic activation of Myc induces cellular transformation and hyper-proliferation, while it activates intrinsic tumor surveillance pathways aimed at restraining the expansion of pre-cancerous cells. All these Myc-induced tumor suppressive mechanisms converge on p53, and loss of p53 activity is the major selected event in lymphomagenesis. Yet, the genetic programs triggered by p53 in tumor suppression have been only partially clarified. Using whole genome mapping of p53 binding and gene expression profiling, we investigated the transcriptional circuitry employed by p53 in suppressing cancer development. We studied the progression of Myc-induced lymphomas in Eµ-myc transgenic mice, as well as the regression of these lymphomas following restoration of p53 function, by either pharmacological or genetic means. We thus identified a set of p53 target genes that are strong candidates for mediating tumor suppression. Currently, we are testing the impact of these new components of the p53 transcriptional program on tumorigenesis with an RNA interference (RNAi)-based functional genetic screen. Altogether our data expand our understanding of the p53 response to Myc-induced oncogenic stress and will hopefully highlight new tumor suppressive mechanisms, paving the way for their therapeutic application.

Citation Format: Claudia Tonelli, Marco J. Morelli, Arianna Sabò, Andrea Piontini, Mattia Pelizzola, Stefano Campaner, Bruno Amati. Genome-wide analysis of p53 transcriptional programs in Myc-induced lymphomas. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr B10.

Abstract A44: Selective transcriptional regulation by Myc in growth control and tumorigenesis

Myc binds DNA with a preference for the E-box consensus CACGTG. In vivo, however, DNA recognition is primarily determined by chromatin context, preceding sequence-specific DNA binding. Myc preferentially associates with active/poised promoters and, to a lesser extent, distal enhancer elements. When expressed at high levels, Myc targets virtually all active promoters and enhancers in the genome, a phenomenon termed “invasion”, which contributed to the concept that Myc acts as a general amplifier of transcriptional activity (1, 2). We recently presented data that support a different scenario (3). While Myc has the potential to interact with all active/poised regulatory elements in the genome, this does not systematically lead to a productive regulatory interaction: instead, promoter/enhancer invasion by Myc most likely reflects the detection of low-affinity interactions (protein-protein or protein-DNA) that allow the transcription factor to target the relevant genomic regions, preceding local scanning of the DNA sequence for high-affinity binding sites (4). Most importantly, when productively engaged by Myc, target genes can be either induced or repressed, as shown in different cell types (3, 5). Our data also show that the global increase in mRNA copies per cell (or amplification), observable either during tumor progression or upon mitogenic stimulation of normal cells, can occur in the absence of overt promoter/enhancer invasion by Myc. RNA amplification is thus indirect, most likely attributable to changes in physiological features that impact on global RNA production and turnover (e.g. cell size, energy metabolism, etc..). Consistent with this view, many Myc-regulated genes have - or may have - central roles in these physiological processes. Putting together all available data, the emerging unifying model supports a central role for Myc in the control of cellular physiology and metabolism, including - albeit indirectly - global RNA production and turnover. An important challenge lying ahead is the full characterization of the Myc-regulated genes and pathways that mediate these biological effects and - by the same token - endow Myc with such pervasive oncogenic potential. 1. Lin CY, et al. (2012) Transcriptional amplification in tumor cells with elevated c-Myc. Cell 151:56-67. 2. Nie Z, et al. (2012) c-Myc is a universal amplifier of expressed genes in lymphocytes and embryonic stem cells. Cell 151:68-79. 3. Sabo A, et al. (2014) Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis. Nature 511:488-492. 4. Sabo A & Amati B (2014) Genome Recognition by MYC. Cold Spring Harb Perspect Med 4. 5. Walz S, et al. (2014) Activation and repression by oncogenic MYC shape tumour-specific gene expression profiles. Nature 511:483-487.

Citation Format: Arianna Sabò, Theresia K. Kress, Mattia Pelizzola, Stefano de Pretis, Marcin Gorski, Alessandra Tesi, Marco J. Morelli, Pranami Bora, Mirko Doni, Alessandro Verrecchia, Claudia Tonelli, Giovanni Fagà, Valerio Bianchi, Alberto Ronchi, Diana Low, Heiko Muller, Ernesto Guccione, Stefano Campaner, Bruno Amati. Selective transcriptional regulation by Myc in growth control and tumorigenesis. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr A44.

methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data

BACKGROUND

Numerous methods are available to profile several epigenetic marks, providing data with different genome coverage and resolution. Large epigenomic datasets are then generated, and often combined with other high-throughput data, including RNA-seq, ChIP-seq for transcription factors (TFs) binding and DNase-seq experiments. Despite the numerous computational tools covering specific steps in the analysis of large-scale epigenomics data, comprehensive software solutions for their integrative analysis are still missing. Multiple tools must be identified and combined to jointly analyze histone marks, TFs binding and other -omics data together with DNA methylation data, complicating the analysis of these data and their integration with publicly available datasets.

RESULTS

To overcome the burden of integrating various data types with multiple tools, we developed two companion R/Bioconductor packages. The former, methylPipe, is tailored to the analysis of high- or low-resolution DNA methylomes in several species, accommodating (hydroxy-)methyl-cytosines in both CpG and non-CpG sequence context. The analysis of multiple whole-genome bisulfite sequencing experiments is supported, while maintaining the ability of integrating targeted genomic data. The latter, compEpiTools, seamlessly incorporates the results obtained with methylPipe and supports their integration with other epigenomics data. It provides a number of methods to score these data in regions of interest, leading to the identification of enhancers, lncRNAs, and RNAPII stalling/elongation dynamics. Moreover, it allows a fast and comprehensive annotation of the resulting genomic regions, and the association of the corresponding genes with non-redundant GeneOntology terms. Finally, the package includes a flexible method based on heatmaps for the integration of various data types, combining annotation tracks with continuous or categorical data tracks.

CONCLUSIONS

methylPipe and compEpiTools provide a comprehensive Bioconductor-compliant solution for the integrative analysis of heterogeneous epigenomics data. These packages are instrumental in providing biologists with minimal R skills a complete toolkit facilitating the analysis of their own data, or in accelerating the analyses performed by more experienced bioinformaticians.

Selective transcriptional regulation by Myc: Experimental design and computational analysis of high-throughput sequencing data

The gene expression programs regulated by the Myc transcription factor were evaluated by integrated genome-wide profiling of Myc binding sites, chromatin marks and RNA expression in several biological models. Our results indicate that Myc directly drives selective transcriptional regulation, which in certain physiological conditions may indirectly lead to RNA amplification. Here, we illustrate in detail the experimental design concerning the high-throughput sequencing data associated with our study (Sabò et al., Nature. (2014) 511:488–492) and the R scripts used for their computational analysis.

INSPEcT: a computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments

MOTIVATION

Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation. Nevertheless, software for the comprehensive quantification of RNA dynamics is still lacking.

RESULTS

INSPEcT is an R package for the integrative analysis of RNA- and 4sU-seq data to study the dynamics of transcriptional regulation. INSPEcT provides gene-level quantification of these rates, and a modeling framework to identify which of these regulatory processes are most likely to explain the observed mRNA and pre-mRNA concentrations. Software performance is tested on a synthetic dataset, instrumental to guide the choice of the modeling parameters and the experimental design.

AVAILABILITY AND IMPLEMENTATION

INSPEcT is submitted to Bioconductor and is currently available as Supplementary Additional File S1.

CONTACT

mattia.pelizzola@iit.it

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Computational and experimental methods to decipher the epigenetic code

A multi-layered set of epigenetic marks, including post-translational modifications of histones and methylation of DNA, is finely tuned to define the epigenetic state of chromatin in any given cell type under specific conditions. Recently, the knowledge about the combinations of epigenetic marks occurring in the genome of different cell types under various conditions is rapidly increasing. Computational methods were developed for the identification of these states, unraveling the combinatorial nature of epigenetic marks and their association to genomic functional elements and transcriptional states. Nevertheless, the precise rules defining the interplay between all these marks remain poorly characterized. In this perspective we review the current state of this research field, illustrating the power and the limitations of current approaches. Finally, we sketch future avenues of research illustrating how the adoption of specific experimental designs coupled with available experimental approaches could be critical for a significant progress in this area.

Systematic mapping of occluded genes by cell fusion reveals prevalence and stability of cis-mediated silencing in somatic cells

Both diffusible factors acting in trans and chromatin components acting in cis are implicated in gene regulation, but the extent to which either process causally determines a cell's transcriptional identity is unclear. We recently used cell fusion to define a class of silent genes termed "cis-silenced" (or "occluded") genes, which remain silent even in the presence of trans-acting transcriptional activators. We further showed that occlusion of lineage-inappropriate genes plays a critical role in maintaining the transcriptional identities of somatic cells. Here, we present, for the first time, a comprehensive map of occluded genes in somatic cells. Specifically, we mapped occluded genes in mouse fibroblasts via fusion to a dozen different rat cell types followed by whole-transcriptome profiling. We found that occluded genes are highly prevalent and stable in somatic cells, representing a sizeable fraction of silent genes. Occluded genes are also highly enriched for important developmental regulators of alternative lineages, consistent with the role of occlusion in safeguarding cell identities. Alongside this map, we also present whole-genome maps of DNA methylation and eight other chromatin marks. These maps uncover a complex relationship between chromatin state and occlusion. Furthermore, we found that DNA methylation functions as the memory of occlusion in a subset of occluded genes, while histone deacetylation contributes to the implementation but not memory of occlusion. Our data suggest that the identities of individual cell types are defined largely by the occlusion status of their genomes. The comprehensive reference maps reported here provide the foundation for future studies aimed at understanding the role of occlusion in development and disease.

Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

The gaseous plant hormone ethylene regulates a multitude of growth and developmental processes. How the numerous growth control pathways are coordinated by the ethylene transcriptional response remains elusive. We characterized the dynamic ethylene transcriptional response by identifying targets of the master regulator of the ethylene signaling pathway, ETHYLENE INSENSITIVE3 (EIN3), using chromatin immunoprecipitation sequencing and transcript sequencing during a timecourse of ethylene treatment. Ethylene-induced transcription occurs in temporal waves regulated by EIN3, suggesting distinct layers of transcriptional control. EIN3 binding was found to modulate a multitude of downstream transcriptional cascades, including a major feedback regulatory circuitry of the ethylene signaling pathway, as well as integrating numerous connections between most of the hormone mediated growth response pathways. These findings provide direct evidence linking each of the major plant growth and development networks in novel ways. DOI:http://dx.doi.org/10.7554/eLife.00675.001.

Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

The gaseous plant hormone ethylene regulates a multitude of growth and developmental processes. How the numerous growth control pathways are coordinated by the ethylene transcriptional response remains elusive. We characterized the dynamic ethylene transcriptional response by identifying targets of the master regulator of the ethylene signaling pathway, ETHYLENE INSENSITIVE3 (EIN3), using chromatin immunoprecipitation sequencing and transcript sequencing during a timecourse of ethylene treatment. Ethylene-induced transcription occurs in temporal waves regulated by EIN3, suggesting distinct layers of transcriptional control. EIN3 binding was found to modulate a multitude of downstream transcriptional cascades, including a major feedback regulatory circuitry of the ethylene signaling pathway, as well as integrating numerous connections between most of the hormone mediated growth response pathways. These findings provide direct evidence linking each of the major plant growth and development networks in novel ways. DOI:http://dx.doi.org/10.7554/eLife.00675.001.

Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

The gaseous plant hormone ethylene regulates a multitude of growth and developmental processes. How the numerous growth control pathways are coordinated by the ethylene transcriptional response remains elusive. We characterized the dynamic ethylene transcriptional response by identifying targets of the master regulator of the ethylene signaling pathway, ETHYLENE INSENSITIVE3 (EIN3), using chromatin immunoprecipitation sequencing and transcript sequencing during a timecourse of ethylene treatment. Ethylene-induced transcription occurs in temporal waves regulated by EIN3, suggesting distinct layers of transcriptional control. EIN3 binding was found to modulate a multitude of downstream transcriptional cascades, including a major feedback regulatory circuitry of the ethylene signaling pathway, as well as integrating numerous connections between most of the hormone mediated growth response pathways. These findings provide direct evidence linking each of the major plant growth and development networks in novel ways.

DOI:http://dx.doi.org/10.7554/eLife.00675.001

All multicellular organisms, including plants, produce hormones—chemical messengers that are released in one part of an organism but act in another. The binding of hormones to receptor proteins on the surface of target cells activates signal transduction cascades, leading ultimately to changes in the transcription and translation of genes.

Ethylene is a gaseous plant hormone that acts at trace levels to stimulate or regulate a variety of processes, including the regulation of plant growth, the ripening of fruit and the shedding of leaves. Plants also produce ethylene in response to wounding, pathogen attack or exposure to environmental stresses, such as extreme temperatures or drought. Although the effects of ethylene on plants are well documented, much less is known about how its functions are controlled and coordinated at the molecular level.

Here, Chang et al. reveal how ethylene alters the transcription of DNA into messenger DNA (mRNA) in the plant model organism, Arabidopsis thaliana. Ethylene is known to exert some of its effects via a protein called EIN3, which is a transcription factor that acts as the master regulator of the ethylene signaling pathway. To identify the targets of EIN3, Chang et al. exposed plants to ethylene and then used a technique called ChIP-Seq to identify those regions of the DNA that EIN3 binds to. At the same time, they used genome-wide mRNA sequencing to determine which genes showed altered transcription.

Over the course of 24 hr, ethylene induced four distinct waves of transcription, suggesting that discrete layers of transcriptional control are present. EIN3 binding also controlled a multitude of downstream transcriptional cascades, including a major negative feedback loop. Surprisingly, many of the genes that showed altered expression in response to EIN3 binding were also influenced by hormones other than ethylene.

In addition to extending our knowledge of the role of EIN3 in coordinating the effects of ethylene, the work of Chang et al. reveals the extensive connectivity between pathways regulated by distinct hormones in plants. The results may also make it easier to identify key players involved in hormone signaling pathways in other plant species.

DOI:http://dx.doi.org/10.7554/eLife.00675.002

Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells

Induced pluripotent stem cells (iPSCs) offer immense potential for regenerative medicine and studies of disease and development. Somatic cell reprogramming involves epigenomic reconfiguration, conferring iPSCs with characteristics similar to embryonic stem (ES) cells. However, it remains unknown how complete the reestablishment of ES-cell-like DNA methylation patterns is throughout the genome. Here we report the first whole-genome profiles of DNA methylation at single-base resolution in five human iPSC lines, along with methylomes of ES cells, somatic cells, and differentiated iPSCs and ES cells. iPSCs show significant reprogramming variability, including somatic memory and aberrant reprogramming of DNA methylation. iPSCs share megabase-scale differentially methylated regions proximal to centromeres and telomeres that display incomplete reprogramming of non-CG methylation, and differences in CG methylation and histone modifications. Lastly, differentiation of iPSCs into trophoblast cells revealed that errors in reprogramming CG methylation are transmitted at a high frequency, providing an iPSC reprogramming signature that is maintained after differentiation.

Germline competency of parthenogenetic embryonic stem cells from immature oocytes of adult mouse ovary

Parthenogenetic embryonic stem cells (pESCs) have been generated in several mammalian species from parthenogenetic embryos that would otherwise die around mid-gestation. However, previous reports suggest that pESCs derived from in vivo ovulated (IVO) mature oocytes show limited pluripotency, as evidenced by low chimera production, high tissue preference and especially deficiency in germline competence, a critical test for genetic integrity and pluripotency of ESCs. Here, we report efficient generation of germline-competent pESC lines (named as IVM pESCs) from parthenogenetic embryos developed from immature oocytes of adult mouse ovaries following in vitro maturation (IVM) and artificial activation. In contrast, pESCs derived from IVO oocytes show defective germline competence, consistent with previous reports. Further, IVM pESCs resemble more ESCs from fertilized embryos (fESCs) than do IVO pESCs on genome-wide DNA methylation and global protein profiles. In addition, IVM pESCs express higher levels of Blimp1, Lin28 and Stella, relative to fESCs, and in their embryoid bodies following differentiation. This may indicate differences in differentiation potentially to the germline. The mechanisms for acquisition of pluripotency and germline competency of IVM pESCs from immature oocytes remain to be determined.

Methylated DNA immunoprecipitation genome-wide analysis

DNA methylation is an important and potentially heritable component of the epigenetic machinery that has a major role in the control of gene expression and can be deregulated in many diseases. This modification of genomic DNA can be assessed using the methylated DNA immunoprecipitation (MeDIP) method, based on the quantification of methylated DNA fragments enriched using an antibody specific for methyl-cytosines.The relationship between the enrichment level and the real DNA methylation status is complex, and only a few methods have been developed to evaluate MeDIP enrichment measures to estimate the absolute or relative number of methyl-cytosines in a given sample. Two such methods are MEDME and BATMAN. This chapter focuses on the description and use of the former with a brief discussion of the latter.

The DNA methylome

Methylation of cytosines is a pervasive feature of eukaryotic genomes and an important epigenetic layer that is fundamental for cellular differentiation processes and control of transcriptional potential. DNA methylation patterns can be inherited and influenced by the environment, diet and aging, and disrupted in diseases. Complete DNA methylomes for several organisms are now available, helping clarify the evolutionary story of this epigenetic mark and its distribution in key genomic elements. Nonetheless, a complete understanding of its role, the mechanisms responsible for its establishment and maintenance, and its cross talk with other components of cellular machinery remains elusive.

Temporal gene expression profile of the hippocampus following trace fear conditioning

In this paper we report the results of gene expression profiling of C57Bl/6N mice hippocampus after trace fear conditioning (TFC), and the identification of genes regulated at early and late steps after conditioning. Several of the genes regulated at early steps following TFC appeared common to many training protocols. At later stages (2 and 6 h), most of the genes identified were different from those identified following other learning paradigms resulting in memory consolidation. At 6 h after training, few genes were upregulated in respect to the naïve condition, suggesting that many gene products have eventually to be downregulated to achieve stable synapses modification and memory formation. In conclusion, the results presented highlight a number of genes whose expression is specifically modified in the mouse hippocampus following TFC and demonstrate the specificity associated to different forms of conditioning.

Genome-wide screen of promoter methylation identifies novel markers in melanoma

DNA methylation is an important component of epigenetic modifications, which influences the transcriptional machinery aberrant in many human diseases. In this study we present the first genome-wide integrative analysis of promoter methylation and gene expression for the identification of methylation markers in melanoma. Genome-wide promoter methylation and gene expression of eight early-passage human melanoma cell strains were compared with newborn and adult melanocytes. We used linear mixed effect models (LME) in combination with a series of filters based on the localization of promoter methylation relative to the transcription start site, overall promoter CpG content, and differential gene expression to discover DNA methylation markers. This approach identified 76 markers, of which 68 were hyper- and eight hypomethylated (LME, P < 0.05). Promoter methylation and differential gene expression of five markers (COL1A2, NPM2, HSPB6, DDIT4L, MT1G) were validated by sequencing of bisulfite-modified DNA and real-time reverse transcriptase PCR, respectively. Importantly, the incidence of promoter methylation of the validated markers increased moderately in early and significantly in advanced-stage melanomas, using early-passage cell strains and snap-frozen tissues (n = 18 and n = 24, respectively) compared with normal melanocytes and nevi (n = 11 and n = 9, respectively). Our approach allows robust identification of methylation markers that can be applied to other studies involving genome-wide promoter methylation. In conclusion, this study represents the first unbiased systematic effort to determine methylation markers in melanoma and revealed several novel genes regulated by promoter methylation that were not described in cancer cells before.

Integrative analysis of epigenetic modulation in melanoma cell response to decitabine: clinical implications

Decitabine, an epigenetic modifier that reactivates genes otherwise suppressed by DNA promoter methylation, is effective for some, but not all cancer patients, especially those with solid tumors. It is commonly recognized that to overcome resistance and improve outcome, treatment should be guided by tumor biology, which includes genotype, epigenotype, and gene expression profile. We therefore took an integrative approach to better understand melanoma cell response to clinically relevant dose of decitabine and identify complementary targets for combined therapy. We employed eight different melanoma cell strains, determined their growth, apoptotic and DNA damage responses to increasing doses of decitabine, and chose a low, clinically relevant drug dose to perform whole-genome differential gene expression, bioinformatic analysis, and protein validation studies. The data ruled out the DNA damage response, demonstrated the involvement of p21(Cip1) in a p53-independent manner, identified the TGFbeta pathway genes CLU and TGFBI as markers of sensitivity to decitabine and revealed an effect on histone modification as part of decitabine-induced gene expression. Mutation analysis and knockdown by siRNA implicated activated beta-catenin/MITF, but not BRAF, NRAS or PTEN mutations as a source for resistance. The importance of protein stability predicted from the results was validated by the synergistic effect of Bortezomib, a proteasome inhibitor, in enhancing the growth arrest of decitabine in otherwise resistant melanoma cells. Our integrative analysis show that improved therapy can be achieved by comprehensive analysis of cancer cells, identified biomarkers for patient's selection and monitoring response, as well as targets for improved combination therapy.

MEDME: an experimental and analytical methodology for the estimation of DNA methylation levels based on microarray derived MeDIP-enrichment

DNA methylation is an important component of epigenetic modifications that influences the transcriptional machinery and is aberrant in many human diseases. Several methods have been developed to map DNA methylation for either limited regions or genome-wide. In particular, antibodies specific for methylated CpG have been successfully applied in genome-wide studies. However, despite the relevance of the obtained results, the interpretation of antibody enrichment is not trivial. Of greatest importance, the coupling of antibody-enriched methylated fragments with microarrays generates DNA methylation estimates that are not linearly related to the true methylation level. Here, we present an experimental and analytical methodology, MEDME (modeling experimental data with MeDIP enrichment), to obtain enhanced estimates that better describe the true values of DNA methylation level throughout the genome. We propose an experimental scenario for evaluating the true relationship in a high-throughput setting and a model-based analysis to predict the absolute and relative DNA methylation levels. We successfully applied this model to evaluate DNA methylation status of normal human melanocytes compared to a melanoma cell strain. Despite the low resolution typical of methods based on immunoprecipitation, we show that model-derived estimates of DNA methylation provide relatively high correlation with measured absolute and relative levels, as validated by bisulfite genomic DNA sequencing. Importantly, the model-derived DNA methylation estimates simplify the interpretation of the results both at single-loci and at chromosome-wide levels.

Statistical similarities between transcriptomics and quantitative shotgun proteomics data

If the large collection of microarray-specific statistical tools was applicable to the analysis of quantitative shotgun proteomics datasets, it would certainly foster an important advancement of proteomics research. Here we analyze two large multidimensional protein identification technology datasets, one containing eight replicates of the soluble fraction of a yeast whole-cell lysate and one containing nine replicates of a human immunoprecipitate, to test whether normalized spectral abundance factor (NSAF) values share substantially similar statistical properties with transcript abundance values from Affymetrix GeneChip data. First we show similar dynamic range and distribution properties of these two types of numeric values. Next we show that the standard deviation (S.D.) of a protein's NSAF values was dependent on the average NSAF value of the protein itself, following a power law. This relationship can be modeled by a power law global error model (PLGEM), initially developed to describe the variance-versus-mean dependence that exists in GeneChip data. PLGEM parameters obtained from NSAF datasets proved to be surprisingly similar to the typical parameters observed in GeneChip datasets. The most important common feature identified by this approach was that, although in absolute terms the S.D. of replicated abundance values increases as a function of increasing average abundance, the coefficient of variation, a relative measure of variability, becomes progressively smaller under the same conditions. We next show that PLGEM parameters were reasonably stable to decreasing numbers of replicates. We finally illustrate one possible application of PLGEM in the identification of differentially abundant proteins that might potentially outperform standard statistical tests. In summary, we believe that this body of work lays the foundation for the application of microarray-specific tools in the analysis of NSAF datasets.

The genopolis microarray database

Background

Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood.

Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions.

Results

The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip^® platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users.

Conclusion

The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local database and a public repository, where the development of a common coherent annotation is important. In its current implementation, it provides a uniform coherently annotated dataset on dendritic cells and macrophage differentiation.