Federico Comoglio

MicroRNA Signature of Malignant Mesothelioma with Potential Diagnostic and Prognostic Implications

MicroRNAs (miRNAs) post-transcriptionally regulate the expression of target genes, and may behave as oncogenes or tumor suppressors. Human malignant mesothelioma is an asbestos-related cancer, with poor prognosis and low median survival. Here we report, for the first time, a cross-evaluation of miRNA expression in mesothelioma (MPP-89, REN) and human mesothelial cells (HMC-telomerase reverse transcriptase). Microarray profiling, confirmed by real-time quantitative RT-PCR, revealed a differential expression of miRNAs between mesothelioma and mesothelial cells. In addition, a computational analysis combining miRNA and gene expression profiles allowed the accurate prediction of genes potentially targeted by dysregulated miRNAs. Several predicted genes belong to terms of Gene Ontology (GO) that are associated with the development and progression of mesothelioma. This suggests that miRNAs may be key players in mesothelioma oncogenesis. We further investigated miRNA expression on a panel of 24 mesothelioma specimens, representative of the three histotypes (epithelioid, biphasic, and sarcomatoid), by quantitative RT-PCR. The expression of miR-17-5p, miR-21, miR-29a, miR-30c, miR-30e-5p, miR-106a, and miR-143 was significantly associated with the histopathological subtypes. Notably, the reduced expression of two miRNAs (miR-17-5p and miR-30c) correlated with better survival of patients with sarcomatoid subtype. Our preliminary analysis points at miRNAs as potential diagnostic and prognostic markers of mesothelioma, and suggests novel tools for the therapy of this malignancy.

Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data

The Photo-Activatable Ribonucleoside-enhanced CrossLinking and ImmunoPrecipitation (PAR-CLIP) method was recently developed for global identification of RNAs interacting with proteins. The strength of this versatile method results from induction of specific T to C transitions at sites of interaction. However, current analytical tools do not distinguish between non-experimentally and experimentally induced transitions. Furthermore, geometric properties at potential binding sites are not taken into account. To surmount these shortcomings, we developed a two-step algorithm consisting of a non-parametric two-component mixture model and a wavelet-based peak calling procedure. Our algorithm can reduce the number of false positives up to 24% thereby identifying high confidence interaction sites. We successfully employed this approach in conjunction with a modified PAR-CLIP protocol to study the functional role of nuclear Moloney leukemia virus 10, a putative RNA helicase interacting with Argonaute2 and Polycomb. Our method, available as the R package wavClusteR, is generally applicable to any substitution-based inference problem in genomics.

DNAshapeR: an R/Bioconductor package for DNA shape prediction and feature encoding

Summary: DNAshapeR predicts DNA shape features in an ultra-fast, high-throughput manner from genomic sequencing data. The package takes either nucleotide sequence or genomic coordinates as input and generates various graphical representations for visualization and further analysis. DNAshapeR further encodes DNA sequence and shape features as user-defined combinations of k-mer and DNA shape features. The resulting feature matrices can be readily used as input of various machine learning software packages for further modeling studies. Availability and implementation: The DNAshapeR software package was implemented in the statistical programming language R and is freely available through the Bioconductor project at https://www.bioconductor.org/packages/devel/bioc/html/DNAshapeR.html and at the GitHub developer site, http://tsupeichiu.github.io/DNAshapeR/. Contact: rohs@usc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

High-Resolution Profiling of Drosophila Replication Start Sites Reveals a DNA Shape and Chromatin Signature of Metazoan Origins

At every cell cycle, faithful inheritance of metazoan genomes requires the concerted activation of thousands of DNA replication origins. However, the genetic and chromatin features defining metazoan replication start sites remain largely unknown. Here, we delineate the origin repertoire of the Drosophila genome at high resolution. We address the role of origin-proximal G-quadruplexes and suggest that they transiently stall replication forks in vivo. We dissect the chromatin configuration of replication origins and identify a rich spatial organization of chromatin features at initiation sites. DNA shape and chromatin configurations, not strict sequence motifs, mark and predict origins in higher eukaryotes. We further examine the link between transcription and origin firing and reveal that modulation of origin activity across cell types is intimately linked to cell-type-specific transcriptional programs. Our study unravels conserved origin features and provides unique insights into the relationship among DNA topology, chromatin, transcription, and replication initiation across metazoa.

A High-Density Map for Navigating the Human Polycomb Complexome

Polycomb group (PcG) proteins are major determinants of gene silencing and epigenetic memory in higher eukaryotes. Here, we systematically mapped the human PcG complexome using a robust affinity purification mass spectrometry approach. Our high-density protein interaction network uncovered a diverse range of PcG complexes. Moreover, our analysis identified PcG interactors linking them to the PcG system, thus providing insight into the molecular function of PcG complexes and mechanisms of recruitment to target genes. We identified two human PRC2 complexes and two PR-DUB deubiquitination complexes, which contain the O-linked N-acetylglucosamine transferase OGT1 and several transcription factors. Finally, genome-wide profiling of PR-DUB components indicated that the human PR-DUB and PRC1 complexes bind distinct sets of target genes, suggesting differential impact on cellular processes in mammals.

Stable Polycomb-dependent transgenerational inheritance of chromatin states in Drosophila

Transgenerational epigenetic inheritance (TEI) describes the transmission of alternative functional states through multiple generations in the presence of the same genomic DNA sequence. Very little is known about the principles and the molecular mechanisms governing this type of inheritance. Here, by transiently enhancing 3D chromatin interactions, we established stable and isogenic Drosophila epilines that carry alternative epialleles, as defined by differential levels of Polycomb-dependent trimethylation of histone H3 Lys27 (forming H3K27me3). After being established, epialleles can be dominantly transmitted to naive flies and can induce paramutation. Importantly, epilines can be reset to a naive state by disruption of chromatin interactions. Finally, we found that environmental changes modulate the expressivity of the epialleles, and we extended our paradigm to naturally occurring phenotypes. Our work sheds light on how nuclear organization and Polycomb group (PcG) proteins contribute to epigenetically inheritable phenotypic variability.

Combinatorial modeling of chromatin features quantitatively predicts DNA replication timing in Drosophila.

In metazoans, each cell type follows a characteristic, spatio-temporally regulated DNA replication program. Histone modifications (HMs) and chromatin binding proteins (CBPs) are fundamental for a faithful progression and completion of this process. However, no individual HM is strictly indispensable for origin function, suggesting that HMs may act combinatorially in analogy to the histone code hypothesis for transcriptional regulation. In contrast to gene expression however, the relationship between combinations of chromatin features and DNA replication timing has not yet been demonstrated. Here, by exploiting a comprehensive data collection consisting of 95 CBPs and HMs we investigated their combinatorial potential for the prediction of DNA replication timing in Drosophila using quantitative statistical models. We found that while combinations of CBPs exhibit moderate predictive power for replication timing, pairwise interactions between HMs lead to accurate predictions genome-wide that can be locally further improved by CBPs. Independent feature importance and model analyses led us to derive a simplified, biologically interpretable model of the relationship between chromatin landscape and replication timing reaching 80% of the full model accuracy using six model terms. Finally, we show that pairwise combinations of HMs are able to predict differential DNA replication timing across different cell types. All in all, our work provides support to the existence of combinatorial HM patterns for DNA replication and reveal cell-type independent key elements thereof, whose experimental investigation might contribute to elucidate the regulatory mode of this fundamental cellular process.

PcG-Mediated Higher-Order Chromatin Structures Modulate Replication Programs at the Drosophila BX-C

Polycomb group proteins (PcG) exert conserved epigenetic functions that convey maintenance of repressed transcriptional states, via post-translational histone modifications and high order structure formation. During S-phase, in order to preserve cell identity, in addition to DNA information, PcG-chromatin-mediated epigenetic signatures need to be duplicated requiring a tight coordination between PcG proteins and replication programs. However, the interconnection between replication timing control and PcG functions remains unknown. Using Drosophila embryonic cell lines, we find that, while presence of specific PcG complexes and underlying transcription state are not the sole determinants of cellular replication timing, PcG-mediated higher-order structures appear to dictate the timing of replication and maintenance of the silenced state. Using published datasets we show that PRC1, PRC2, and PhoRC complexes differently correlate with replication timing of their targets. In the fully repressed BX-C, loss of function experiments revealed a synergistic role for PcG proteins in the maintenance of replication programs through the mediation of higher-order structures. Accordingly, replication timing analysis performed on two Drosophila cell lines differing for BX-C gene expression states, PcG distribution, and chromatin domain conformation revealed a cell-type-specific replication program that mirrors lineage-specific BX-C higher-order structures. Our work suggests that PcG complexes, by regulating higher-order chromatin structure at their target sites, contribute to the definition and the maintenance of genomic structural domains where genes showing the same epigenetic state replicate at the same time.

Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

BackgroundPAR-CLIP is a recently developed Next Generation Sequencing-based method enabling transcriptome-wide identification of interaction sites between RNA and RNA-binding proteins. The PAR-CLIP procedure induces specific base transitions that originate from sites of RNA-protein interactions and can therefore guide the identification of binding sites. However, additional sources of transitions, such as cell type-specific SNPs and sequencing errors, challenge the inference of binding sites and suitable statistical approaches are crucial to control false discovery rates. In addition, a highly resolved delineation of binding sites followed by an extensive downstream analysis is necessary for a comprehensive characterization of the protein binding preferences and the subsequent design of validation experiments.ResultsWe present a statistical and computational framework for PAR-CLIP data analysis. We developed a sensitive transition-centered algorithm specifically designed to resolve protein binding sites at high resolution in PAR-CLIP data. Our method employes a Bayesian network approach to associate posterior log-odds with the observed transitions, providing an overall quantification of the confidence in RNA-protein interaction. We use published PAR-CLIP data to demonstrate the advantages of our approach, which compares favorably with alternative algorithms. Lastly, by integrating RNA-Seq data we compute conservative experimentally-based false discovery rates of our method and demonstrate the high precision of our strategy.ConclusionsOur method is implemented in the R package wavClusteR 2.0. The package is distributed under the GPL-2 license and is available from BioConductor at http://www.bioconductor.org/packages/devel/bioc/html/wavClusteR.html.

A Deterministic Analysis of Genome Integrity during Neoplastic Growth in Drosophila

The development of cancer has been associated with the gradual acquisition of genetic alterations leading to a progressive increase in malignancy. In various cancer types this process is enabled and accelerated by genome instability. While genome sequencing-based analysis of tumor genomes becomes increasingly a standard procedure in human cancer research, the potential necessity of genome instability for tumorigenesis in Drosophila melanogaster has, to our knowledge, never been determined at DNA sequence level. Therefore, we induced formation of tumors by depletion of the Drosophila tumor suppressor Polyhomeotic and subjected them to genome sequencing. To achieve a highly resolved delineation of the genome structure we developed the Deterministic Structural Variation Detection (DSVD) algorithm, which identifies structural variations (SVs) with high accuracy and at single base resolution. The employment of long overlapping paired-end reads enables DSVD to perform a deterministic, i.e. fragment size distribution independent, identification of a large size spectrum of SVs. Application of DSVD and other algorithms to our sequencing data reveals substantial genetic variation with respect to the reference genome reflecting temporal separation of the reference and laboratory strains. The majority of SVs, constituted by small insertions/deletions, is potentially caused by erroneous replication or transposition of mobile elements. Nevertheless, the tumor did not depict a loss of genome integrity compared to the control. Altogether, our results demonstrate that genome stability is not affected inevitably during sustained tumor growth in Drosophila implying that tumorigenesis, in this model organism, can occur irrespective of genome instability and the accumulation of specific genetic alterations.