In silico modelling of RNA-RNA dimer and its application for rational siRNA design and ncRNA target search

Non-protein coding region, which constitutes 98.5% of the human genome, were long depreciated as evolutive relict. It is only recently that the biological relevance of\ud the non-coding RNAs associated with these non-coding regions was recognized. The development of experimental and bioinformatical methods aimed at detecting these non-coding RNAs (ncRNAs) lead to the discovery of more than 29,000,000 sequences, grouped into more than 1300 families. More often than not these ncRNAs function by binding to other RNAs, either pro- tein coding or non-protein coding. Compared to the number of tools to detect and classify ncRNAs, the number of tools to search for putative RNA binding partners is negligible. This leads to the actual situation where the function of the majority of the annotated ncRNAs genes is completely unknown. The aim of this work is to assess the function of different families of ncRNAs by developing new algorithms and methods to study RNA-RNA interactions. These new methods are extensions of RNA-folding algorithms applied to the problem of RNA- RNA interactions. Depending on the class of ncRNA studied, different methods were developed and tested. This work shows that the development of RNA-folding algorithms to study RNA- RNA interactions is a promising way to functionally annotate ncRNAs. Still other factors like RNA-proteins interaction, RNA-concentration or RNA-expression, play an important role in the process of RNA hybridization and will have to be taken into account in future works in order to achieve reliable prediction of RNA binding partners.Non-protein coding region, which constitutes 98.5% of the human genome, were long depreciated as evolutive relict. It is only recently that the biological relevance of the non-coding RNAs associated with these non-coding regions was recognized. The development of experimental and bioinformatical methods aimed at detecting these non-coding RNAs (ncRNAs) lead to the discovery of more than 29,000,000 sequences, grouped into more than 1300 families. More often than not these ncRNAs function by binding to other RNAs, either pro- tein coding or non-protein coding. Compared to the number of tools to detect and classify ncRNAs, the number of tools to search for putative RNA binding partners is negligible. This leads to the actual situation where the function of the majority of the annotated ncRNAs genes is completely unknown. The aim of this work is to assess the function of different families of ncRNAs by developing new algorithms and methods to study RNA-RNA interactions. These new methods are extensions of RNA-folding algorithms applied to the problem of RNA- RNA interactions. Depending on the class of ncRNA studied, different methods were developed and tested. This work shows that the development of RNA-folding algorithms to study RNA- RNA interactions is a promising way to functionally annotate ncRNAs. Still other factors like RNA-proteins interaction, RNA-concentration or RNA-expression, play an important role in the process of RNA hybridization and will have to be taken into account in future works in order to achieve reliable prediction of RNA binding partners

RNApredator: fast accessibility-based prediction of sRNA targets

Bacterial genomes encode a plethora of small RNAs (sRNAs), which are heterogeneous in size, structure and function. Most sRNAs act as post-transcriptional regulators by means of specific base pairing interactions with the 5′-untranslated region of mRNA transcripts, thereby modifying the stability of the target transcript and/or its ability to be translated. Here, we present RNApredator, a web server for the prediction of sRNA targets. The user can choose from a set of over 2155 genomes and plasmids from 1183 bacterial species. RNApredator then uses a dynamic programming approach, RNAplex, to compute putative targets. Compared to web servers with a similar task, RNApredator takes the accessibility of the target during the target search into account, improving the specificity of the predictions. Furthermore, enrichment in Gene Ontology terms, cellular pathways as well as changes in accessibilities along the target sequence can be done in fully automated post-processing steps. The predictive performance of the underlying dynamic programming approach RNAplex is similar to that of more complex methods, but needs at least three orders of magnitude less time to complete. RNApredator is available at http://rna.tbi.univie.ac.at/RNApredator

Nonrandom structure in the urea-unfolded Escherichia coli outer membrane protein X (OmpX)

On the basis of sequence-specific resonance assignments for the complete polypeptide backbone and most of the amino acid side chains by heteronuclear nuclear magnetic resonance (NMR) spectroscopy, the urea-unfolded form of the outer membrane protein X (OmpX) from Escherichia coli has been structurally characterized. (1)H-(1)H nuclear Overhauser effects (NOEs), dispersion of the chemical shifts, amide proton chemical shift temperature coefficients, amide proton exchange rates, and (15)N[(1)H]-NOEs show that OmpX in 8 M urea at pH 6.5 is globally unfolded, but adopts local nonrandom conformations in the polypeptide segments of residues 73-82 and 137-145. For these two regions, numerous medium-range and longer-range NOEs were observed, which were used as the input for structure calculations of these polypeptide segments with the program DYANA. The segment 73-82 forms a quite regular helical structure, with only loosely constrained amino acid side chains. In the segment 137-145, the tryptophan residue 140 forms the core of a small hydrophobic cluster. Both nonrandom structures are present with an abundance of about 25% of the protein molecules. The sequence-specific NMR assignment and the physicochemical characterization of urea-denatured OmpX presented in this paper are currently used as a platform for investigations of the folding mechanism of this integral membrane protein

Transcriptome Study of an Exophiala dermatitidis PKS1 Mutant on an ex Vivo Skin Model: Is Melanin Important for Infection?

The black yeast Exophiala dermatitidis is a polyextremophilic human pathogen, especially known for growing in man-made extreme environments. Reported diseases caused by this fungus range from benign cutaneous to systemic infections with 40% fatality rate. While the number of cases steadily increases in both immunocompromised and immunocompetent people, detailed knowledge about infection mechanisms, virulence factors and host response are scarce. To understand the impact of the putative virulence factor melanin on the infection, we generated a polyketide synthase (PKS1) mutant using CRISPR/Cas9 resulting in a melanin deficient strain. The mutant and the wild-type fungus were inoculated onto skin explants using an ex vivo skin organ culture model to simulate in vivo cutaneous infection. The difference between the mutant and wild-type transcriptional landscapes, as assessed by whole RNA-sequencing, were small and were observed in pathways related to the copper homeostasis, cell wall genes and proteases. Seven days after inoculation the wild-type fungus completely colonized the stratum corneum, invaded the skin and infected keratinocytes while the mutant had only partially covered the skin and showed no invasiveness. Our results suggest that melanin dramatically improves the invasiveness and virulence of E. dermatitidis during the first days of the skin infection

Translational Control by RNA-RNA Interaction: Improved Computation of RNA-RNA Binding Thermodynamics

The thermodynamics of RNA-RNA interaction consists of two components: the energy necessary to make a potential binding region accessible, i.e., unpaired, and the energy gained from the base pairing of the two interaction partners. We show here that both components can be efficiently computed using an improved variant of RNAup. The method is then applied to a set of bacterial small RNAs involved in translational control. In all cases of biologically active sRNA target interactions, the target sites predicted by RNAup is in perfect agreement with literature. In addition to prediction of target site location, RNAup can be also be used to determine the mode of sRNA action. Using information about target site location and the accessibility change resulting form sRNA binding we can discriminate between positive and negative regulators of translation

About -rV ending verbs in the Sakhalin dialect of Ainu

Table S2. Abbreviations of peroxidase gene names used for the peroxidase-catalase superfamily. (XLSX 54 kb

Partition function and base pairing probabilities of RNA heterodimers

Background: RNA has been recognized as a key player in cellular regulation in recent years. In many cases, non-coding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. The specificity of these interactions derives from the stability of inter-molecular base pairing. The accurate computational treatment of RNA-RNA binding therefore lies at the heart of target prediction algorithms. Methods: The standard dynamic programming algorithms for computing secondary structures of linear single-stranded RNA molecules are extended to the co-folding of two interacting RNAs. Results: We present a program, RNAcofold, that computes the hybridization energy and base pairing pattern of a pair of interacting RNA molecules. In contrast to earlier approaches, complex internal structures in both RNAs are fully taken into account. RNAcofold supports the calculation of the minimum energy structure and of a complete set of suboptimal structures in an energy band above the ground state. Furthermore, it provides an extension of McCaskill's partition function algorithm to compute base pairing probabilities, realistic interaction energies, and equilibrium concentrations of duplex structures

Thermodynamics of RNA-RNA binding

Background: Reliable prediction of RNA–RNA binding energies is crucial, e.g. for the understanding on RNAi, microRNA–mRNA binding and antisense interactions. The thermodynamics of such RNA–RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to ‘open’ the binding site and (2) the energy gained from hybridization. Methods: We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired. Results: Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable with a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding energies of siRNAs to their respective mRNA target

Non-coding RNA annotation of the genome of Trichoplax adhaerens

A detailed annotation of non-protein coding RNAs is typically missing in initial releases of newly sequenced genomes. Here we report on a comprehensive ncRNA annotation of the genome of Trichoplax adhaerens, the presumably most basal metazoan whose genome has been published to-date. Since blast identified only a small fraction of the best-conserved ncRNAs—in particular rRNAs, tRNAs and some snRNAs—we developed a semi-global dynamic programming tool, GotohScan, to increase the sensitivity of the homology search. It successfully identified the full complement of major and minor spliceosomal snRNAs, the genes for RNase P and MRP RNAs, the SRP RNA, as well as several small nucleolar RNAs. We did not find any microRNA candidates homologous to known eumetazoan sequences. Interestingly, most ncRNAs, including the pol-III transcripts, appear as single-copy genes or with very small copy numbers in the Trichoplax genome

Structured RNAs and synteny regions in the pig genome

BACKGROUND: Annotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals. RESULTS: We present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure similarity search as well as class specific methods, we obtained a conservative set with a total of 3,391 structured RNA loci of which 1,011 and 2,314, respectively, hold strong sequence and structure similarity to structured RNAs in existing databases. The RNA loci cover 139 cis-regulatory element loci, 58 lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome, we obtained no matches at the highest confidence level. Additional analysis of RNA-seq data from a pooled library from 10 different pig tissues added another 165 miRNA loci, yielding an overall annotation of 3,556 structured RNA loci. This annotation represents our best effort at making an automated annotation. To further enhance the reliability, 571 of the 3,556 structured RNAs were manually curated by methods depending on the RNA class while 1,581 were declared as pseudogenes. We further created a multiple alignment of pig against 20 representative vertebrates, from which RNAz predicted 83,859 de novo RNA loci with conserved RNA structures. 528 of the RNAz predictions overlapped with the homology based annotation or novel miRNAs. We further present a substantial synteny analysis which includes 1,004 lineage specific de novo RNA loci and 4 ncRNA loci in the known annotation specific for Laurasiatheria (pig, cow, dolphin, horse, cat, dog, hedgehog). CONCLUSIONS: We have obtained one of the most comprehensive annotations for structured ncRNAs of a mammalian genome, which is likely to play central roles in both health modelling and production. The core annotation is available in Ensembl 70 and the complete annotation is available at http://rth.dk/resources/rnannotator/susscr102/version1.02. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-459) contains supplementary material, which is available to authorized users