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Abstract Background The availability of transcriptomic data for species without a reference genome enables the construction of de novo transcriptome assemblies as alternative reference resources from RNA-Seq data. A transcriptome provides direct information about a species’ protein-coding genes under specific experimental conditions. The de novo assembly process produces a unigenes file in FASTA format, subsequently targeted for the annotation. Homology-based annotation, a method to infer the function of sequences by estimating similarity with other sequences in a reference database, is a computationally demanding procedure. Results To mitigate the computational burden, we introduce HPC-T-Annotator, a tool for de novo transcriptome homology annotation on high performance computing (HPC) infrastructures, designed for straightforward configuration via a Web interface. Once the configuration data are given, the entire parallel computing software for annotation is automatically generated and can be launched on a supercomputer using a simple command line. The output data can then be easily viewed using post-processing utilities in the form of Python notebooks integrated in the proposed software. Conclusions HPC-T-Annotator expedites homology-based annotation in de novo transcriptome assemblies. Its efficient parallelization strategy on HPC infrastructures significantly reduces computational load and execution times, enabling large-scale transcriptome analysis and comparison projects, while its intuitive graphical interface extends accessibility to users without IT skills.

Abstract We present a de novo transcriptome of the mosquito vector Culex pipiens, assembled by sequences of susceptible and insecticide resistant larvae. The high quality of the assembly was confirmed by TransRate and BUSCO. A mapping percentage until 94.8% was obtained by aligning contigs to Nr, SwissProt, and TrEMBL, with 27,281 sequences that simultaneously mapped on the three databases. A total of 14,966 ORFs were also functionally annotated by using the eggNOG database. Among them, we identified ORF sequences of the main gene families involved in insecticide resistance. Therefore, this resource stands as a valuable reference for further studies of differential gene expression as well as to identify genes of interest for genetic-based control tools.

Abstract Understanding the genomic underpinnings of thermal adaptation is a hot topic in eco-evolutionary studies of parasites. Marine heteroxenous parasites have complex life cycles encompassing a free-living larval stage, an ectothermic intermediate host and a homeothermic definitive host, thus representing compelling systems for the study of thermal adaptation. The Antarctic anisakid Contracaecum osculatum sp. D is a marine parasite able to survive and thrive both at very cold and warm temperatures within the environment and its hosts. Here, a de novo transcriptome of C. osculatum sp. D was generated for the first time, by performing RNA-Seq experiments on a set of individuals exposed to temperatures experienced by the nematode during its life cycle. The analysis generated 425,954,724 reads, which were assembled and then annotated. The high-quality assembly was validated, achieving over 88% mapping against the transcriptome. The transcriptome of this parasite will represent a valuable genomic resource for future studies aimed at disentangling the genomic architecture of thermal tolerance and metabolic pathways related to temperature stress.

Abstract Dispersal is a key process in ecology and evolutionary biology, as it shapes biodiversity patterns over space and time. Attitude to disperse is unevenly distributed among individuals within populations, and that individual personality can have pivotal roles in the shaping of this attitude. Here, we assembled and annotated the first de novo transcriptome of the head tissues of Salamandra salamandra from individuals, representative of distinct behavioral profiles. We obtained 1,153,432,918 reads, which were successfully assembled and annotated. The high-quality of the assembly was confirmed by three assembly validators. The alignment of contigs against the de novo transcriptome led to a mapping percentage higher than 94%. The homology annotation with DIAMOND led to 153,048 (blastx) and 95,942 (blastp) shared contigs, annotated on NR, Swiss-Prot and TrEMBL. The domain and site protein prediction led to 9850 GO-annotated contigs. This de novo transcriptome represents reliable reference for comparative gene expression studies between alternative behavioral types, for comparative gene expression studies within Salamandra, and for whole transcriptome and proteome studies in amphibians.

Measurement(s) Transcriptome Technology Type(s) RNA-seq of total RNA Factor Type(s) Behavior Sample Characteristic - Organism Bombina pachypus Sample Characteristic - Environment natural environment Sample Characteristic - Location Italy

Chronic exposure to ultraviolet (UV) radiation is known to induce the formation of DNA photo-adducts, including cyclobutane pyrimidine dimers (CPDs) and Dewar valence derivatives (DVs). While CPDs usually occur at higher frequency than DVs, recent studies have shown that the latter display superior selectivity and significant stability in interaction with the human DNA/topoisomerase 1 complex (TOP1). With the aim to deeply investigate the mechanism of interaction of DVs with TOP1, we report here four all-atom molecular dynamic simulations spanning one microsecond. These simulations are focused on the stability and conformational changes of two DNA/TOP1-DV complexes in solution, the data being compared with the biomimetic thymine dimer counterparts. Results from root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) analyses unequivocally confirmed increased stability of the DNA/TOP1-DV complexes throughout the simulation duration. Detailed interaction analyses, uncovering the presence of salt bridges, hydrogen bonds, water-mediated interactions, and hydrophobic interactions, as well as pinpointing the non-covalent interactions within the complexes, enabled the identification of specific TOP1 residues involved in the interactions over time and suggested a potential TOP1 inhibition mechanism in action.

Abstract Objectives Anisakis pegreffii is a zoonotic parasite requiring marine organisms to complete its life-history. Human infection (anisakiasis) occurs when the third stage larvae (L3) are accidentally ingested with raw or undercooked infected fish or squids. A new de novo transcriptome of A. pegreffii was here generated aiming to provide a robust bulk of data to be used for a comprehensive "ready-to-use" resource for detecting functional studies on genes and gene products of A. pegreffii involved in the molecular mechanisms of parasite-host interaction. Data description A RNA-seq library of A. pegreffii L3 was here newly generated by using Illumina TruSeq platform. It was combined with other five RNA-seq datasets previously gathered from L3 of the same species stored in SRA of NCBI. The final dataset was analyzed by launching three assembler programs and two validation tools. The use of a robust pipeline produced a high-confidence protein-coding transcriptome of A. pegreffii. These data represent a more robust and complete transcriptome of this species with respect to the actually existing resources. This is of importance for understanding the involved adaptive and immunomodulatory genes implicated in the “cross talk” between the parasite and its hosts, including the accidental one (humans).

IntroductionAnisakis pegreffii is a sibling species within the A. simplex (s.l.) complex requiring marine homeothermic (mainly cetaceans) and heterothermic (crustaceans, fish, and cephalopods) organisms to complete its life cycle. It is also a zoonotic species, able to accidentally infect humans (anisakiasis). To investigate the molecular signals involved in this host-parasite interaction and pathogenesis, the proteomic composition of the extracellular vesicles (EVs) released by the third-stage larvae (L3) of A. pegreffii, was characterized.MethodsGenetically identified L3 of A. pegreffii were maintained for 24 h at 37°C and EVs were isolated by serial centrifugation and ultracentrifugation of culture media. Proteomic analysis was performed by Shotgun Analysis.Results and discussionEVs showed spherical shaped structure (size 65-295 nm). Proteomic results were blasted against the A. pegreffii specific transcriptomic database, and 153 unique proteins were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis predicted several proteins belonging to distinct metabolic pathways. The similarity search employing selected parasitic nematodes database revealed that proteins associated with A. pegreffii EVs might be involved in parasite survival and adaptation, as well as in pathogenic processes. Further, a possible link between the A. pegreffii EVs proteins versus those of human and cetaceans’ hosts, were predicted by using HPIDB database. The results, herein described, expand knowledge concerning the proteins possibly implied in the host-parasite interactions between this parasite and its natural and accidental hosts.

Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand–receptor binding interactions (lrbi) to be studied. In this study, we present MD–ligand–receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand–receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand–receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations.

Abstract Stressful experiences are part of everyday life and animals have evolved physiological and behavioral responses aimed at coping with stress and maintaining homeostasis. However, repeated or intense stress can induce maladaptive reactions leading to behavioral disorders. Adaptations in the brain, mediated by changes in gene expression, have a crucial role in the stress response. Recent years have seen a tremendous increase in studies on the transcriptional effects of stress. The input raw data are freely available from public repositories and represent a wealth of information for further global and integrative retrospective analyses. We downloaded from the Sequence Read Archive 751 samples (SRA-experiments), from 18 independent BioProjects studying the effects of different stressors on the brain transcriptome in mice. We performed a massive bioinformatics re-analysis applying a single, standardized pipeline for computing differential gene expression. This data mining allowed the identification of novel candidate stress-related genes and specific signatures associated with different stress conditions. The large amount of computational results produced was systematized in the interactive “Stress Mice Portal”.

Abstract Background RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2 . Conclusions HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.

Abstract Background The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the “Big Data” era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center. Results Starting from April 2016, CINECA and ELIXIR-IT launched the pilot Call “ELIXIR-IT HPC@CINECA”, offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~ 8 Millions of CPU/hours and, for data storage, ~ 100 TB of permanent and ~ 300 TB of temporary space. Conclusions Three years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals.

Human Topoisomerase I (hTop1p) is a ubiquitous enzyme that relaxes supercoiled DNA through a conserved mechanism involving transient breakage, rotation, and binding. Htop1p is the molecular target of the chemotherapeutic drug camptothecin (CPT). It causes the hTop1p-DNA complex to slow down the binding process and clash with the replicative machinery during the S phase of the cell cycle, forcing cells to activate the apoptotic response. This gives hTop1p a central role in cancer therapy. Recently, two artesunic acid derivatives (compounds c6 and c7) have been proposed as promising inhibitors of hTop1p with possible antitumor activity. We used several computational approaches to obtain in silico confirmations of the experimental data and to form a comprehensive dynamic description of the ligand-receptor system. We performed molecular docking analyses to verify the ability of the two new derivatives to access the enzyme-DNA interface, and a classical molecular dynamics simulation was performed to assess the capacity of the two compounds to maintain a stable binding pose over time. Finally, we calculated the noncovalent interactions between the two new derivatives and the hTop1p receptor in order to propose a possible inhibitory mechanism like that adopted by CPT.

We report here the synthesis of novel thymine biomimetic photo-adducts bearing an alkane spacer between nucleobases and characterized by antimelanoma activity against two mutated cancer cell lines overexpressing human Topoisomerase 1 (TOP1), namely SKMEL28 and RPMI7951. Among them, Dewar Valence photo-adducts showed a selectivity index higher than the corresponding pyrimidine-(6-4)-pyrimidone and cyclobutane counterpart and were characterized by the highest affinity towards TOP1/DNA complex as evaluated by molecular docking analysis. The antimelanoma activity of novel photo-adducts was retained after loading into UV photo-protective lignin nanoparticles as stabilizing agent and efficient drug delivery system. Overall, these results support a combined antimelanoma and UV sunscreen strategy involving the use of photo-protective lignin nanoparticles for the controlled release of thymine dimers on the skin followed by their sacrificial transformation into photo-adducts and successive inhibition of melanoma and alert of cellular UV machinery repair pathways.

A previous genome scan on 323 Piedmontese individuals identified a cluster of 13 SNPs significantly associated with direct calving ease and centred on the three genes LAP3, LCORL and NCAPG in chromosome 6. We investigated missense mutations affecting calving ease in Piedmontese cattle in the identified region using sequences from the whole exome in eight Piedmontese individuals chosen from the extremes of the direct calving ease estimated breeding values distribution for this trait. The present study has not found missense variants in LAP3 and LCORL, while two were identified on NCAPG by three different variant calling methods. Other gene candidates in the same region harbour missense mutations, such as PPM1K, PKD2, SPP1 and MEPE, but both SIFT analysis and chi-square test on frequency of alleles make us hypothesise that NCAPG is the single gene responsible for the trait variation. The two SNPs on NCAPG are in complete linkage disequilibrium in our samples; therefore, further investigations are needed in order to discriminate their role.

Abstract Background The advent and ongoing development of next generation sequencing technologies (NGS) has led to a rapid increase in the rate of human genome re-sequencing data, paving the way for personalized genomics and precision medicine. The body of genome resequencing data is progressively increasing underlining the need for accurate and time-effective bioinformatics systems for genotyping - a crucial prerequisite for identification of candidate causal mutations in diagnostic screens. Results Here we present CoVaCS, a fully automated, highly accurate system with a web based graphical interface for genotyping and variant annotation. Extensive tests on a gold standard benchmark data-set -the NA12878 Illumina platinum genome- confirm that call-sets based on our consensus strategy are completely in line with those attained by similar command line based approaches, and far more accurate than call-sets from any individual tool. Importantly our system exhibits better sensitivity and higher specificity than equivalent commercial software. Conclusions CoVaCS offers optimized pipelines integrating state of the art tools for variant calling and annotation for whole genome sequencing (WGS), whole-exome sequencing (WES) and target-gene sequencing (TGS) data. The system is currently hosted at Cineca, and offers the speed of a HPC computing facility, a crucial consideration when large numbers of samples must be analysed. Importantly, all the analyses are performed automatically allowing high reproducibility of the results. As such, we believe that CoVaCS can be a valuable tool for the analysis of human genome resequencing studies. CoVaCS is available at: https://bioinformatics.cineca.it/covacs.

Abstract Background Plum pox virus (PPV), agent of Sharka disease, is the most important quarantine pathogen of peach (P. persica L. Batsch). Extensive evaluation of peach germplasm has highlighted the lack of resistant sources, while suggesting the presence of a quantitative disease resistance, expressed as reduction in the intensity of symptoms. Unravelling the genetic architecture of peach response to PPV infection is essential for pyramiding resistant genes and for developing more tolerant varieties. For this purpose, a genome-wide association (GWA) approach was applied in a panel of accessions phenotyped for virus susceptibility and genotyped with the IPSC peach 9 K SNP Array, and coupled with an high-coverage resequencing of the tolerant accession ‘Kamarat’. Results Genome-wide association identified three highly significant associated loci on chromosome 2 and 3, accounting for most of the reduction in PPV-M susceptibility within the analysed peach population. The exploration of associated intervals through whole-genome comparison of the tolerant accession ‘Kamarat’ and other susceptible accessions, including the PPV-resistant wild-related species P. davidiana, allow the identification of allelic variants in promising candidate genes, including an RTM2-like gene already characterized in A. thaliana. Conclusions The present study is the first effort to identify genetic factors involved in Sharka disease in peach germplasm through a GWA approach. We provide evidence of the presence of quantitative resistant loci in a collection of peach accessions, identifying major loci and highly informative SNPs that could be useful for marker assisted selection. These results could serve as reference bases for future research aimed at the comprehension of genetic mechanism regulating the complex peach-PPV interaction.