RNA-seq profiling reveals different pathways between remodeled vessels and myocardium in hypertrophic cardiomyopathy.

OBJECTIVE: Coronary microvascular dysfunction (CMD) is a key pathophysiological feature of hypertrophic cardiomyopathy (HCM), contributing to myocardial ischemia and representing a critical determinant of patients' adverse outcome. The molecular mechanisms underlying the morphological and functional changes of CMD are still unknown. Aim of this study was to obtain insights on the molecular pathways associated with microvessel remodeling in HCM. METHODS: Interventricular septum myectomies from patients with obstructive HCM (n = 20) and donors' hearts (CTRL, discarded for technical reasons, n = 7) were collected. Remodeled intramyocardial arterioles and cardiomyocytes were microdissected by laser capture and next-generation sequencing was used to delineate the transcriptome profile. RESULTS: We identified 720 exclusive differentially expressed genes (DEGs) in cardiomyocytes and 1315 exclusive DEGs in remodeled arterioles of HCM. Performing gene ontology and pathway enrichment analyses, we identified selectively altered pathways between remodeled arterioles and cardiomyocytes in HCM patients and controls. CONCLUSIONS: We demonstrate the existence of distinctive pathways between remodeled arterioles and cardiomyocytes in HCM patients and controls at the transcriptome level.

Discovering sequence and structure landscapes in RNA interaction motifs.

RNA molecules are able to bind proteins, DNA and other small or long RNAs using information at primary, secondary or tertiary structure level. Recent techniques that use cross-linking and immunoprecipitation of RNAs can detect these interactions and, if followed by high-throughput sequencing, molecules can be analysed to find recurrent elements shared by interactors, such as sequence and/or structure motifs. Many tools are able to find sequence motifs from lists of target RNAs, while others focus on structure using different approaches to find specific interaction elements. In this work, we make a systematic analysis of RBP-RNA and RNA-RNA datasets to better characterize the interaction landscape with information about multi-motifs on the same RNAs. To achieve this goal, we updated our BEAM algorithm to combine both sequence and structure information to create pairs of patterns that model motifs of interaction. This algorithm was applied to several RNA binding proteins and ncRNAs interactors, confirming already known motifs and discovering new ones. This landscape analysis on interaction variability reflects the diversity of target recognition and underlines that often both primary and secondary structure are involved in molecular recognition.

BEAM web server: a tool for structural RNA motif discovery.

Motivation: RNA structural motif finding is a relevant problem that becomes computationally hard when working on high-throughput data (e.g. eCLIP, PAR-CLIP), often represented by thousands of RNA molecules. Currently, the BEAM server is the only web tool capable to handle tens of thousands of RNA in input with a motif discovery procedure that is only limited by the current secondary structure prediction accuracies. Results: The recently developed method BEAM (BEAr Motifs finder) can analyze tens of thousands of RNA molecules and identify RNA secondary structure motifs associated to a measure of their statistical significance. BEAM is extremely fast thanks to the BEAR encoding that transforms each RNA secondary structure in a string of characters. BEAM also exploits the evolutionary knowledge contained in a substitution matrix of secondary structure elements, extracted from the RFAM database of families of homologous RNAs. The BEAM web server has been designed to streamline data pre-processing by automatically handling folding and encoding of RNA sequences, giving users a choice for the preferred folding program. The server provides an intuitive and informative results page with the list of secondary structure motifs identified, the logo of each motif, its significance, graphic representation and information about its position in the RNA molecules sharing it. Availability and implementation: The web server is freely available at http://beam.uniroma2.it/ and it is implemented in NodeJS and Python with all major browsers supported. Contact: marco.pietrosanto@uniroma2.it. Supplementary information: Supplementary data are available at Bioinformatics online.

Revealing protein-lncRNA interaction.

Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein-RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP-lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein-lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations.

A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications.

Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.

The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset.

The most common mutation in human melanoma, BRAF(V600E), activates the serine/threonine kinase BRAF and causes excessive activity in the mitogen-activated protein kinase pathway. BRAF(V600E) mutations are also present in benign melanocytic naevi, highlighting the importance of additional genetic alterations in the genesis of malignant tumours. Such changes include recurrent copy number variations that result in the amplification of oncogenes. For certain amplifications, the large number of genes in the interval has precluded an understanding of the cooperating oncogenic events. Here we have used a zebrafish melanoma model to test genes in a recurrently amplified region of chromosome 1 for the ability to cooperate with BRAF(V600E) and accelerate melanoma. SETDB1, an enzyme that methylates histone H3 on lysine 9 (H3K9), was found to accelerate melanoma formation significantly in zebrafish. Chromatin immunoprecipitation coupled with massively parallel DNA sequencing and gene expression analyses uncovered genes, including HOX genes, that are transcriptionally dysregulated in response to increased levels of SETDB1. Our studies establish SETDB1 as an oncogene in melanoma and underscore the role of chromatin factors in regulating tumorigenesis.

Web-Beagle: a web server for the alignment of RNA secondary structures.

Web-Beagle (http://beagle.bio.uniroma2.it) is a web server for the pairwise global or local alignment of RNA secondary structures. The server exploits a new encoding for RNA secondary structure and a substitution matrix of RNA structural elements to perform RNA structural alignments. The web server allows the user to compute up to 10 000 alignments in a single run, taking as input sets of RNA sequences and structures or primary sequences alone. In the latter case, the server computes the secondary structure prediction for the RNAs on-the-fly using RNAfold (free energy minimization). The user can also compare a set of input RNAs to one of five pre-compiled RNA datasets including lncRNAs and 3' UTRs. All types of comparison produce in output the pairwise alignments along with structural similarity and statistical significance measures for each resulting alignment. A graphical color-coded representation of the alignments allows the user to easily identify structural similarities between RNAs. Web-Beagle can be used for finding structurally related regions in two or more RNAs, for the identification of homologous regions or for functional annotation. Benchmark tests show that Web-Beagle has lower computational complexity, running time and better performances than other available methods.

The human rs1050286 polymorphism alters LOX-1 expression through modifying miR-24 binding.

The up-regulation of lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), encoded by the OLR1 gene, plays a fundamental role in the pathogenesis of atherosclerosis. Moreover, OLR1 polymorphisms were associated with increased susceptibility to acute myocardial infarction (AMI) and coronary artery diseases (CAD). In these pathologies, the identification of therapeutic approaches that can inhibit or reduce LOX-1 overexpression is crucial. Predictive analysis showed a putative hsa-miR-24 binding site in the 3'UTR of OLR1, 'naturally' mutated by the presence of the rs1050286 single nucleotide polymorphism (SNP). Luciferase assays revealed that miR-24 targets OLR1 3'UTR-G, but not 3'UTR-A (P < 0.0005). The functional relevance of miR-24 in regulating the expression of OLR1 was established by overexpressing miR-24 in human cell lines heterozygous (A/G, HeLa) and homozygous (A/A, HepG2) for rs1050286 SNP. Accordingly, HeLa (A/G), but not HepG2 (A/A), showed a significant down-regulation of OLR1 both at RNA and protein level. Our results indicate that rs1050286 SNP significantly affects miR-24 binding affinity to the 3'UTR of OLR1, causing a more efficient post-transcriptional gene repression in the presence of the G allele. On this basis, we considered that OLR1 rs1050286 SNP may contribute to modify OLR1 susceptibility to AMI and CAD, so ORL1 SNPs screening could help to stratify patients risk.

Next Generation Sequencing and Linkage Analysis for the Molecular Diagnosis of a Novel Overlapping Syndrome Characterized by Hypertrophic Cardiomyopathy and Typical Electrical Instability of Brugada Syndrome.

BACKGROUND: Familial hypertrophic cardiomyopathy (HCM) is an autosomal dominant inherited disorder; mutations in at least 20 genes have been associated. Brugada syndrome (BrS) is an autosomal dominant inherited disorder caused by mutations mainly in theSCN5Agene. A new clinical entity that consists of HCM, typical electrical instability of BrS and sudden death (SD), is described. METHODS AND RESULTS: The family was constituted by 7 members, 4 of who presented clinical features of HCM and electrical instability of BrS. The clinical presentation of proband was ventricular fibrillation. All members were clinically evaluated by physical examination, 12-lead electrocardiography, 2-dimensional echocardiography, stress test, electrocardiogram Holter, flecainide test, and electrophysiological study. An integrated linkage analysis and next generation sequencing (NGS) approach was used to identify the causative mutation. Linkage with the α-tropomyosin (TPM1) gene on chromosome 15q22 was identified. The NGS study identified a missense mutation within theTPM1gene (c.574G>A; p.E192K), exactly located in a binding domain with polycystin-2 protein. No other pathogenic mutations were identified. CONCLUSIONS: This is the first report of an association between HCM and BrS, and the first to use a combined approach of linkage and NGS to identify a causative mutation in SD. The present study expands the clinical spectrum of disorders associated with theTPM1gene and may be useful to report novel mechanisms of electrical instability in HCM and BrS.

RNA-Sequencing for profiling goat milk transcriptome in colostrum and mature milk.

BACKGROUND: In this work we aimed at sequencing and assembling the goat milk transcriptome corresponding at colostrum and 120 days of lactation. To reconstruct transcripts we used both the genome as reference, and a de novo assembly approach. Additionally, we aimed at identifying the differentially expressed genes (DEGs) between the two lactation stages and at analyzing the expression of genes involved in oligosaccharides metabolism. RESULTS: A total of 44,635 different transcripts, organized in 33,757 tentative genes, were obtained using the goat genome as reference. A significant sequence similarity match was found for 40,353 transcripts (90%) against the NCBI NT and for 35,701 (80%) against the NR databases. 68% and 69% of the de novo assembled transcripts, in colostrum and 120 days of lactation samples respectively, have a significant match with the merged transcriptome obtained using Cufflinks/Cuffmerge. CSN2, PAEP, CSN1S2, CSN3, LALBA, TPT1, FTH1, M-SAA3, SPP1, GLYCAM1, EEF1A1, CTSD, FASN, RPS29, CSN1S1, KRT19 and CHEK1 were found between the top fifteen highly expressed genes. 418 loci were differentially expressed between lactation stages, among which 207 and 122 were significantly up- and down-regulated in colostrum, respectively. Functional annotation and pathway enrichment analysis showed that in goat colostrum somatic cells predominate biological processes involved in glycolysis, carbohydrate metabolism, defense response, cytokine activity, regulation of cell proliferation and cell death, vasculature development, while in mature milk, biological process associated with positive regulation of lymphocyte activation and anatomical structure morphogenesis are enriched. The analysis of 144 different oligosaccharide metabolism-related genes showed that most of these (64%) were more expressed in colostrum than in mature milk, with eight expressed at very high levels (SLCA3, GMSD, NME2, SLC2A1, B4GALT1, B3GNT2, NANS, HEXB). CONCLUSIONS: To our knowledge, this is the first study comparing goat transcriptome of two lactation stages: colostrum and 120 days. Our findings suggest putative differences of expression between stages and can be envisioned as a base for further research in the topic. Moreover because a higher expression of genes involved in immune defense response, carbohydrate metabolism and related to oligosaccharide metabolism was identified in colostrum we here corroborate the potential of goat milk as a natural source of lactose-derived oligosaccharides and for the development of functional foods.

A Proteome-wide Domain-centric Perspective on Protein Phosphorylation.

Phosphorylation is a widespread post-translational modification that modulates the function of a large number of proteins. Here we show that a significant proportion of all the domains in the human proteome is significantly enriched or depleted in phosphorylation events. A substantial improvement in phosphosites prediction is achieved by leveraging this observation, which has not been tapped by existing methods. Phosphorylation sites are often not shared between multiple occurrences of the same domain in the proteome, even when the phosphoacceptor residue is conserved. This is partly because of different functional constraints acting on the same domain in different protein contexts. Moreover, by augmenting domain alignments with structural information, we were able to provide direct evidence that phosphosites in protein-protein interfaces need not be positionally conserved, likely because they can modulate interactions simply by sitting in the same general surface area.

A novel approach to represent and compare RNA secondary structures.

Structural information is crucial in ribonucleic acid (RNA) analysis and functional annotation; nevertheless, how to include such structural data is still a debated problem. Dot-bracket notation is the most common and simple representation for RNA secondary structures but its simplicity leads also to ambiguity requiring further processing steps to dissolve. Here we present BEAR (Brand nEw Alphabet for RNA), a new context-aware structural encoding represented by a string of characters. Each character in BEAR encodes for a specific secondary structure element (loop, stem, bulge and internal loop) with specific length. Furthermore, exploiting this informative and yet simple encoding in multiple alignments of related RNAs, we captured how much structural variation is tolerated in RNA families and convert it into transition rates among secondary structure elements. This allowed us to compute a substitution matrix for secondary structure elements called MBR (Matrix of BEAR-encoded RNA secondary structures), of which we tested the ability in aligning RNA secondary structures. We propose BEAR and the MBR as powerful resources for the RNA secondary structure analysis, comparison and classification, motif finding and phylogeny.

Role of CTCF protein in regulating FMR1 locus transcription.

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability, is caused by epigenetic silencing of the FMR1 gene, through expansion and methylation of a CGG triplet repeat (methylated full mutation). An antisense transcript (FMR1-AS1), starting from both promoter and intron 2 of the FMR1 gene, was demonstrated in transcriptionally active alleles, but not in silent FXS alleles. Moreover, a DNA methylation boundary, which is lost in FXS, was recently identified upstream of the FMR1 gene. Several nuclear proteins bind to this region, like the insulator protein CTCF. Here we demonstrate for the first time that rare unmethylated full mutation (UFM) alleles present the same boundary described in wild type (WT) alleles and that CTCF binds to this region, as well as to the FMR1 gene promoter, exon 1 and intron 2 binding sites. Contrariwise, DNA methylation prevents CTCF binding to FXS alleles. Drug-induced CpGs demethylation does not restore this binding. CTCF knock-down experiments clearly established that CTCF does not act as insulator at the active FMR1 locus, despite the presence of a CGG expansion. CTCF depletion induces heterochromatinic histone configuration of the FMR1 locus and results in reduction of FMR1 transcription, which however is not accompanied by spreading of DNA methylation towards the FMR1 promoter. CTCF depletion is also associated with FMR1-AS1 mRNA reduction. Antisense RNA, like sense transcript, is upregulated in UFM and absent in FXS cells and its splicing is correlated to that of the FMR1-mRNA. We conclude that CTCF has a complex role in regulating FMR1 expression, probably through the organization of chromatin loops between sense/antisense transcriptional regulatory regions, as suggested by bioinformatics analysis.

Nucleos: a web server for the identification of nucleotide-binding sites in protein structures.

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

webPDBinder: a server for the identification of ligand binding sites on protein structures.

The webPDBinder (http://pdbinder.bio.uniroma2.it/PDBinder) is a web server for the identification of small ligand-binding sites in a protein structure. webPDBinder searches a protein structure against a library of known binding sites and a collection of control non-binding pockets. The number of similarities identified with the residues in the two sets is then used to derive a propensity value for each residue of the query protein associated to the likelihood that the residue is part of a ligand binding site. The predicted binding residues can be further refined using conservation scores derived from the multiple alignment of the PFAM protein family. webPDBinder correctly identifies residues belonging to the binding site in 77% of the cases and is able to identify binding pockets starting from holo or apo structures with comparable performances. This is important for all the real world cases where the query protein has been crystallized without a ligand and is also difficult to obtain clear similarities with bound pockets from holo pocket libraries. The input is either a PDB code or a user-submitted structure. The output is a list of predicted binding pocket residues with propensity and conservation values both in text and graphical format.

Alternative splicing tends to avoid partial removals of protein-protein interaction sites.

BACKGROUND: Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In the present study we performed a statistical analysis of the alternative splicing of a non-redundant dataset of human protein-protein interfaces known at molecular level to determine the importance of this way of modulation of protein-protein interactions through AS. RESULTS: Using a Cochran-Mantel-Haenszel chi-square test we demonstrated that the alternative splicing-mediated partial removal of both heterodimeric and homodimeric binding sites occurs at lower frequencies than expected, and this holds true even if we consider only those isoforms whose sequence is less different from that of the canonical protein and which therefore allow to selectively regulate functional regions of the protein. On the other hand, large removals of the binding site are not significantly prevented, possibly because they are associated to drastic structural changes of the protein. The observed protection of the binding sites from AS is not preferentially directed towards putative hot spot interface residues, and is widespread to all protein functional classes. CONCLUSIONS: Our findings indicate that protein-protein binding sites are generally protected from alternative splicing-mediated partial removals. However, some cases in which the binding site is selectively removed exist, and here we discuss one of them.

Specific tagging of the egress-related osmiophilic bodies in the gametocytes of Plasmodium falciparum.

BACKGROUND: Gametocytes, the blood stages responsible for Plasmodium falciparum transmission, contain electron dense organelles, traditionally named osmiophilic bodies, that are believed to be involved in gamete egress from the host cell. In order to provide novel tools in the cellular and molecular studies of osmiophilic body biology, a P. falciparum transgenic line in which these organelles are specifically marked by a reporter protein was produced and characterized. METHODOLOGY: A P. falciparum transgenic line expressing an 80-residue N-terminal fragment of the osmiophilic body protein Pfg377 fused to the reporter protein DsRed, under the control of pfg377 upstream and downstream regulatory regions, was produced. RESULTS: The transgenic fusion protein is expressed at the appropriate time and stage of sexual differentiation and is trafficked to osmiophilic bodies as the endogenous Pfg377 protein. These results indicate that a relatively small N-terminal portion of Pfg377 is sufficient to target the DsRed reporter to the gametocyte osmiophilic bodies. CONCLUSIONS: This is the first identification of a P. falciparum aminoacid sequence able to mediate trafficking to such organelles. To fluorescently tag such poorly characterized organelles opens novel avenues in cellular and imaging studies on their biogenesis and on their role in gamete egress.

Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments.

Structural characterization of RNAs is a dynamic field, offering many modelling possibilities. RNA secondary structure models are usually characterized by an encoding that depicts structural information of the molecule through string representations or graphs. In this work, we provide a generalization of the BEAR encoding (a context-aware structural encoding we previously developed) by expanding the set of alignments used for the construction of substitution matrices and then applying it to secondary structure encodings ranging from fine-grained to more coarse-grained representations. We also introduce a re-interpretation of the Shannon Information applied on RNA alignments, proposing a new scoring metric, the Relative Information Gain (RIG). The RIG score is available for any position in an alignment, showing how different levels of detail encoded in the RNA representation can contribute differently to convey structural information. The approaches presented in this study can be used alongside state-of-the-art tools to synergistically gain insights into the structural elements that RNAs and RNA families are composed of. This additional information could potentially contribute to their improvement or increase the degree of confidence in the secondary structure of families and any set of aligned RNAs.

The rs17084733 variant in the KIT 3' UTR disrupts a miR-221/222 binding site in gastrointestinal stromal tumour: a sponge-like mechanism conferring disease susceptibility.

Several miRNAs are dysregulated in gastrointestinal stromal tumours (GIST), and miR-221/222 appear to have a prominent role in GIST biology. Therefore, we investigated the role of DNA variants located in miR-221/222 precursor sequences and their target KIT 3'UTR. Ninety-five polymorphisms were analysed in 115 GIST cases and 88 healthy controls. KIT 3'UTR rs17084733 and pri-miR-222 rs75246947 were found significantly associated with GIST susceptibility. Specifically, KIT rs17084733 A allele was more common in GIST, particularly in KIT wild-type (WT) patients (Padj = 0.017). rs17084733 variant is located within one of the three miR-221/222 binding sites in the KIT 3'UTR, resulting in a mismatch in this seed region. Conversely, KIT mRNA levels were lower in patients carrying the variant allele, except for KIT mutant GIST. Luciferase assay data in GIST cells, generated using a construct containing all the three miR-221/222 binding sites, are consistent with KIT mRNA levels in GIST patients. Reporter assay data, generated using a construct containing only the site encompassing rs17084733, confirmed that this is a functional variant disrupting the miR-221/222 binding site. In conclusion, this is the first study investigating the role of SNPs on miR-221/222 precursor sequences and their binding region on KIT 3'UTR in GIST. We identified the KIT variant rs17084733 as a possible novel genetic biomarker for risk of developing KIT-WT GIST. Moreover, our findings suggest the role of one of the three miR-221/222 binding sites on KIT 3'UTR as endogenous sponge, soaking up and subtracting miR-221/222 to the other two sites characterized by a higher affinity.

Modeling cancer drug response through drug-specific informative genes.

Recent advances in pharmacogenomics have generated a wealth of data of different types whose analysis have helped in the identification of signatures of different cellular sensitivity/resistance responses to hundreds of chemical compounds. Among the different data types, gene expression has proven to be the more successful for the inference of drug response in cancer cell lines. Although effective, the whole transcriptome can introduce noise in the predictive models, since specific mechanisms are required for different drugs and these realistically involve only part of the proteins encoded in the genome. We analyzed the pharmacogenomics data of 961 cell lines tested with 265 anti-cancer drugs and developed different machine learning approaches for dissecting the genome systematically and predict drug responses using both drug-unspecific and drug-specific genes. These methodologies reach better response predictions for the vast majority of the screened drugs using tens to few hundreds genes specific to each drug instead of the whole genome, thus allowing a better understanding and interpretation of drug-specific response mechanisms which are not necessarily restricted to the drug known targets.