184 research outputs found

    The PETfold and PETcofold web servers for intra- and intermolecular structures of multiple RNA sequences

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    The function of non-coding RNA genes largely depends on their secondary structure and the interaction with other molecules. Thus, an accurate prediction of secondary structure and RNA–RNA interaction is essential for the understanding of biological roles and pathways associated with a specific RNA gene. We present web servers to analyze multiple RNA sequences for common RNA structure and for RNA interaction sites. The web servers are based on the recent PET (Probabilistic Evolutionary and Thermodynamic) models PETfold and PETcofold, but add user friendly features ranging from a graphical layer to interactive usage of the predictors. Additionally, the web servers provide direct access to annotated RNA alignments, such as the Rfam 10.0 database and multiple alignments of 16 vertebrate genomes with human. The web servers are freely available at: http://rth.dk/resources/petfold

    Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

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    BACKGROUND: Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. RESULTS: By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. CONCLUSIONS: Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function

    From Structure Prediction to Genomic Screens for Novel Non-Coding RNAs

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    Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other

    Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

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    BACKGROUND: We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm. RESULTS: We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. CONCLUSION: Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding. Constraining on alignment is a straightforward method of reducing the runtime and memory requirements of the algorithm. Five practical implementations of the pairwise Sankoff algorithm – this work (Consan), David Mathews' Dynalign, Ian Holmes' Stemloc, Ivo Hofacker's PMcomp, and Jan Gorodkin's FOLDALIGN – have comparable overall performance with different strengths and weaknesses

    BSGatlas : a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access

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    A large part of our current understanding of gene regulation in Gram-positive bacteria is based on Bacillus subtilis , as it is one of the most well studied bacterial model systems. The rapid growth in data concerning its molecular and genomic biology is distributed across multiple annotation resources. Consequently, the interpretation of data from further B. subtilis experiments becomes increasingly challenging in both low- and large-scale analyses. Additionally, B. subtilis annotation of structured RNA and non-coding RNA (ncRNA), as well as the operon structure, is still lagging behind the annotation of the coding sequences. To address these challenges, we created the B. subtilis genome atlas, BSGatlas, which integrates and unifies multiple existing annotation resources. Compared to any of the individual resources, the BSGatlas contains twice as many ncRNAs, while improving the positional annotation for 70 % of the ncRNAs. Furthermore, we combined known transcription start and termination sites with lists of known co-transcribed gene sets to create a comprehensive transcript map. The combination with transcription start/termination site annotations resulted in 717 new sets of co-transcribed genes and 5335 untranslated regions (UTRs). In comparison to existing resources, the number of 5′ and 3′ UTRs increased nearly fivefold, and the number of internal UTRs doubled. The transcript map is organized in 2266 operons, which provides transcriptional annotation for 92 % of all genes in the genome compared to the at most 82 % by previous resources. We predicted an off-target-aware genome-wide library of CRISPR–Cas9 guide RNAs, which we also linked to polycistronic operons. We provide the BSGatlas in multiple forms: as a website (https://rth.dk/resources/bsgatlas/), an annotation hub for display in the UCSC genome browser, supplementary tables and standardized GFF3 format, which can be used in large scale -omics studies. By complementing existing resources, the BSGatlas supports analyses of the B. subtilis genome and its molecular biology with respect to not only non-coding genes but also genome-wide transcriptional relationships of all genes

    Engineering a family of synthetic splicing ribozymes

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    Controlling RNA splicing opens up possibilities for the synthetic biologist. The Tetrahymena ribozyme is a model group I self-splicing ribozyme that has been shown to be useful in synthetic circuits. To create additional splicing ribozymes that can function in synthetic circuits, we generated synthetic ribozyme variants by rationally mutating the Tetrahymena ribozyme. We present an alignment visualization for the ribozyme termed as structure information diagram that is similar to a sequence logo but with alignment data mapped on to secondary structure information. Using the alignment data and known biochemical information about the Tetrahymena ribozyme, we designed synthetic ribozymes with different primary sequences without altering the secondary structure. One synthetic ribozyme with 110 nt mutated retained 12% splicing efficiency in vivo. The results indicate that our biochemical understanding of the ribozyme is accurate enough to engineer a family of active splicing ribozymes with similar secondary structure but different primary sequences

    A study of alternative splicing in the pig

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    <p>Abstract</p> <p>Background</p> <p>Since at least half of the genes in mammalian genomes are subjected to alternative splicing, alternative pre-mRNA splicing plays an important contribution to the complexity of the mammalian proteome. Expressed sequence tags (ESTs) provide evidence of a great number of possible alternative isoforms. With the EST resource for the domestic pig now containing more than one million porcine ESTs, it is possible to identify alternative splice forms of the individual transcripts in this species from the EST data with some confidence.</p> <p>Results</p> <p>The pig EST data generated by the Sino-Danish Pig Genome project has been assembled with publicly available ESTs and made available in the PigEST database. Using the Distiller package 2,515 EST clusters with candidate alternative isoforms were identified in the EST data with high confidence. In agreement with general observations in human and mouse, we find putative splice variants in about 30% of the contigs with more than 50 ESTs. Based on the criteria that a minimum of two EST sequences confirmed each splice event, a list of 100 genes with the most distinct tissue-specific alternative splice events was generated from the list of candidates. To confirm the tissue specificity of the splice events, 10 genes with functional annotation were randomly selected from which 16 individual splice events were chosen for experimental verification by quantitative PCR (qPCR). Six genes were shown to have tissue specific alternatively spliced transcripts with expression patterns matching those of the EST data. The remaining four genes had tissue-restricted expression of alternative spliced transcripts. Five out of the 16 splice events that were experimentally verified were found to be putative pig specific.</p> <p>Conclusions</p> <p>In accordance with human and rodent studies we estimate that approximately 30% of the porcine genes undergo alternative splicing. We found a good correlation between EST predicted tissue-specificity and experimentally validated splice events in different porcine tissue. This study indicates that a cluster size of around 50 ESTs is optimal for <it>in silico </it>detection of alternative splicing. Although based on a limited number of splice events, the study supports the notion that alternative splicing could have an important impact on species differentiation since 31% of the splice events studied appears to be species specific.</p
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