Пошук подібних нуклеотидних сайтів у геномних сиквенсах фітопатогенних вірусів

Проведено комп’ютерний пошук подібних нуклеотидних сайтів у геномах фітопатогенних вірусів шляхом послідовного співставлення двох геномних сиквенсів зі зростаючою величиною зсуву їх початкових позицій. Встановлено граничні параметри невипадкової збіжності нуклеотидів у сиквенсах, показано наявність подібних нуклеотидних сайтів у філогенетично далеких родів вірусів, уточнено систематичне положення вірусу некрозу лізіантусу, виявлено особливості локалізації подібних нуклеотидних сайтів у вірусних геномах.Проведено компьютерный поиск подобных нуклеотидных сайтов в геномах фитопатогенных вирусов путем последовательного сопоставления двух геномных сиквенсов с возрастающей величиной сдвига их начальных позиций. Установлено граничные параметры неслучайного совпадения нуклеотидов в сиквенсах, показано наличие подобных нуклеотидных сайтов у филогенетически далеких родов вирусов, уточнено систематическое положение вируса некроза лизиантуса, выявлено особенности локализации подобных нуклеотидных сайтов в вирусных геномах.Computational search for similar nucleotide sites in genomes of plant viruses was performed by successive comparison of two genomic sequences with increasing the displacement of their initial positions. Parameter limits of non-random nucleotide coincidence in sequences were determined, presence of similar nucleotide sites in phylogenetically different viral genera was shown, a taxonomy of lisianthus necrosis virus was specified, localization peculiarity of similar nucleotide sites in viral genomes was revealed

Workflows for the Large-Scale Assessment of miRNA Evolution: Birth and Death of miRNA Genes in Tunicates

As described over 20 years ago with the discovery of RNA interference (RNAi), double-stranded RNAs occupied key roles in regulation and as defense-line in animal cells. This thesis focuses on metazoan microRNAs (miRNAs). These small non-coding RNAs are distinguished from their small-interfering RNA (siRNA) relatives by their tightly controlled, efficient and flexible biogenesis, together with a broader flexibility to target multiple mRNAs by a seed imperfect base-pairing. As potent regulators, miRNAs are involved in mRNA stability and post-transcriptional regulation tasks, being a conserved mechanism used repetitively by the evolution, not only in metazoans, but plants and unicellular organisms. Through a comprehensive revision of the current animal miRNA model, the canonical pathway dominates the extensive literature about miRNAs, and served as a scaffold to understand the scenes behind the regulatory landscape performed by the cell. The characterization of a diverse set of non-canonical pathways has expanded this view, suggesting a diverse, rich and flexible regulatory landscape to generate mature miRNAs. The production of miRNAs, derived from isolated or clustered transcripts, is an efficient and highly conserved mechanism traced back to animals with high fidelity at family level. In evolutionary terms, expansions of miRNA families have been associated with an increasing morphological and developmental complexity. In particular, the Chordata clade (the ancient cephalochordates, highly derived and secondary simplified tunicates, and the well-known vertebrates) represents an interesting scenario to study miRNA evolution. Despite clearly conserved miRNAs along these clades, tunicates display massive restructuring events, including emergence of highly derived miRNAs. As shown in this thesis, model organisms or vertebrate-specific bias exist in current animal miRNA annotations, misrepresenting more diverse groups, such as marine invertebrates. Current miRNA databases, such as miRBase and Rfam, classified miRNAs under different definitions and possessed annotations that are not simple to be linked. As an alternative, this thesis proposes a method to curate and merge those annotations, making use of miRBase precursor/mature annotations and genomes together with Rfam predicted sequences. This approach generated structural models for shared miRNA families, based on the alignment of their correct-positioned mature sequences as anchors. In this process, the developed structural curation steps flagged 33 miRNA families from the Rfam as questionable. Curated Rfam and miRBase anchored-structural alignments provided a rich resource for constructing predictive miRNA profiles, using correspondent hidden Markov (HMMs) and covariance models (CMs). As a direct application, the use of those models is time-consuming, and the user has to deal with multiple iterations to achieve a genome-wide non-overlapping annotation. To resolve this, the proposed miRNAture pipeline provides an automatic and flexible solution to annotate miRNAs. It combines multiple homology approaches to generate the best candidates validated at sequence and structural levels. This increases the achievable sensitivity to annotate canonical miRNAs, and the evaluation against human annotation shows that clear false positive calls are rare and additional counterparts lie in retained-introns, transcribed lncRNAs or repeat families. Further development of miRNAture suggests an inclusion of multiple rules to distinguish non-canonical miRNA families. This thesis describes multiple homology approaches to annotate the genomic information from a non-model chordate: the colonial tunicate Didemnum vexillum. Detected high levels of genetic variance and unexpected levels of DNA degradation were evidenced through a comprehensive analysis of genome-assembly methods and gene annotation. Despite those challenges, it was possible to find candidate homeobox and skeletogenesis- related genes. On its own, the ncRNA annotation included expected conserved families, and an extensive search of the Rhabdomyosarcoma 2-associated transcript (RMST) lncRNA family traced-back at the divergence of deuterostomes. In addition, a complete study of the annotation thresholds suggested variations to detect miRNAs, later implemented on the miRNAture tool. This chapter is a showcase of the usual workflow that should follow comprehensive sequencing, assembly and annotation project, in the light of the increasing research approaching DNA sequencing. In the last 10 years, the remarkable increment in tunicate sequencing projects boosted the access to an expanded miRNA annotation landscape. In this way, a comprehensive homology approach annotated the miRNA complement of 28 deuterostome genomes (including current 16 reported tunicates) using miRNAture. To get proper structural models as input, corrected miRBase structural alignments served as a scaffold for building correspondent CMs, based on a developed genetic algorithm. By this means, this automatic approach selected the set of sequences that composed the alignments, generating 2492 miRNA CMs. Despite the multiple sources and associated heterogeneity of the studied genomes, a clustering approach successfully gathered five groups of similar assemblies and highlighted low quality assemblies. The overall family and loci reduction on tunicates is notorious, showing on average 374 microRNA (miRNA) loci, in comparison to other clades: Cephalochordata (2119), Vertebrata (3638), Hemichordata (1092) and Echinodermata (2737). Detection of 533 miRNA families on the divergence of tunicates shows an expanded landscape regarding currently miRNA annotated families. Shared sets of ancestral, chordates, Olfactores, and specific clade-specific miRNAs were uncovered using a phyloge- netic conservation criteria. Compared to current annotations, the family repertories were expanded in all cases. Finally, relying on the adjacent elements from annotated miRNAs, this thesis proposes an additional syntenic support to cluster miRNA loci. In this way, the structural alignment of miR-1497, originally annotated in three model tunicates, was expanded with a clear syntenic support on tunicates

Recognition of short functional motifs in protein sequences

The main goal of this study was to develop a method for computational de novo prediction of short linear motifs (SLiMs) in protein sequences that would provide advantages over existing solutions for the users. The users are typically biological laboratory researchers, who want to elucidate the function of a protein that is possibly mediated by a short motif. Such a process can be subcellular localization, secretion, post-translational modification or degradation of proteins. Conducting such studies only with experimental techniques is often associated with high costs and risks of uncertainty. Preliminary prediction of putative motifs with computational methods, them being fast and much less expensive, provides possibilities for generating hypotheses and therefore, more directed and efficient planning of experiments. To meet this goal, I have developed HH-MOTiF – a web-based tool for de novo discovery of SLiMs in a set of protein sequences. While working on the project, I have also detected patterns in sequence properties of certain SLiMs that make their de novo prediction easier. As some of these patterns are not yet described in the literature, I am sharing them in this thesis. While evaluating and comparing motif prediction results, I have identified conceptual gaps in theoretical studies, as well as existing practical solutions for comparing two sets of positional data annotating the same set of biological sequences. To close this gap and to be able to carry out in-depth performance analyses of HH-MOTiF in comparison to other predictors, I have developed a corresponding statistical method, SLALOM (for StatisticaL Analysis of Locus Overlap Method). It is currently available as a standalone command line tool

Molecular Identification of Atlantic Bluefin Tuna (Thunnus thynnus, Scombridae) Larvae and Development of a DNA Character-Based Identification Key for Mediterranean Scombrids

The Atlantic bluefin tuna, Thunnus thynnus, is a commercially important species that has been severely over-exploited in the recent past. Although the eastern Atlantic and Mediterranean stock is now showing signs of recovery, its current status remains very uncertain and as a consequence their recovery is dependent upon severe management informed by rigorous scientific research. Monitoring of early life history stages can inform decision makers about the health of the species based upon recruitment and survival rates. Misidentification of fish larvae and eggs can lead to inaccurate estimates of stock biomass and productivity which can trigger demands for increased quotas and unsound management conclusions. Herein we used a molecular approach employing mitochondrial and nuclear genes (CO1 and ITS1, respectively) to identify larvae (n = 188) collected from three spawning areas in the Mediterranean Sea by different institutions working with a regional fisheries management organization. Several techniques were used to analyze the genetic sequences (sequence alignments using search algorithms, neighbour joining trees, and a genetic character-based identification key) and an extensive comparison of the results is presented. During this process various inaccuracies in related publications and online databases were uncovered. Our results reveal important differences in the accuracy of the taxonomic identifications carried out by different ichthyoplanktologists following morphology- based methods. While less than half of larvae provided were bluefin tuna, other dominant taxa were bullet tuna (Auxis rochei), albacore (Thunnus alalunga) and little tunny (Euthynnus alletteratus). We advocate an expansion of expertise for a new generation of morphology-based taxonomists, increased dialogue between morphology-based and molecular taxonomists and increased scrutiny of public sequence databases.Versión del editor4,411

Recognition of short functional motifs in protein sequences

The main goal of this study was to develop a method for computational de novo prediction of short linear motifs (SLiMs) in protein sequences that would provide advantages over existing solutions for the users. The users are typically biological laboratory researchers, who want to elucidate the function of a protein that is possibly mediated by a short motif. Such a process can be subcellular localization, secretion, post-translational modification or degradation of proteins. Conducting such studies only with experimental techniques is often associated with high costs and risks of uncertainty. Preliminary prediction of putative motifs with computational methods, them being fast and much less expensive, provides possibilities for generating hypotheses and therefore, more directed and efficient planning of experiments. To meet this goal, I have developed HH-MOTiF – a web-based tool for de novo discovery of SLiMs in a set of protein sequences. While working on the project, I have also detected patterns in sequence properties of certain SLiMs that make their de novo prediction easier. As some of these patterns are not yet described in the literature, I am sharing them in this thesis. While evaluating and comparing motif prediction results, I have identified conceptual gaps in theoretical studies, as well as existing practical solutions for comparing two sets of positional data annotating the same set of biological sequences. To close this gap and to be able to carry out in-depth performance analyses of HH-MOTiF in comparison to other predictors, I have developed a corresponding statistical method, SLALOM (for StatisticaL Analysis of Locus Overlap Method). It is currently available as a standalone command line tool

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Automatic Configuration of Programmable Logic Controller Emulators

Programmable logic controllers (PLCs), which are used to control much of the world\u27s critical infrastructures, are highly vulnerable and exposed to the Internet. Many efforts have been undertaken to develop decoys, or honeypots, of these devices in order to characterize, attribute, or prevent attacks against Industrial Control Systems (ICS) networks. Unfortunately, since ICS devices typically are proprietary and unique, one emulation solution for a particular vendor\u27s model will not likely work on other devices. Many previous efforts have manually developed ICS honeypots, but it is a very time intensive process. Thus, a scalable solution is needed in order to automatically configure PLC emulators. The ScriptGenE Framework presented in this thesis leverages several techniques used in reverse engineering protocols in order to automatically configure PLC emulators using network traces. The accuracy, flexibility, and efficiency of the ScriptGenE Framework is tested in three fully automated experiments