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Background: Comparative genomics approaches have facilitated the discovery of many novel non-coding and structured RNAs (ncRNAs). The increasing availability of related genomes now makes it possible to systematically search for compensatory base changes – and thus for conserved secondary structures – even in genomic regions that are poorly alignable in the primary sequence. The wealth of available transcriptome data can add valuable insight into expression and possible function for new ncRNA candidates. Earlier work identifying ncRNAs in Drosophila melanogaster made use of sequence-based alignments and employed a sliding window approach, inevitably biasing identification toward RNAs encoded in the more conserved parts of the genome. Results: To search for conserved RNA structures (CRSs) that may not be highly conserved in sequence and to assess the expression of CRSs, we conducted a genome-wide structural alignment screen of 27 insect genomes including D. melanogaster and integrated this with an extensive set of tiling array data. The structural alignment screen revealed ∼30,000 novel candidate CRSs at an estimated false discovery rate of less than 10%. With more than one quarter of all individual CRS motifs showing sequence identities below 60%, the predicted CRSs largely complement the findings of sliding window approaches applied previously. While a sixth of the CRSs were ubiquitously expressed, we found that most were expressed in specific developmental stages or cell lines. Notably, most statistically significant enrichment of CRSs were observed in pupae, mainly in exons of untranslated regions, promotors, enhancers, and long ncRNAs. Interestingly, cell lines were found to express a different set of CRSs than were found in vivo. Only a small fraction of intergenic CRSs were co-expressed with the adjacent protein coding genes, which suggests that most intergenic CRSs are independent genetic units. Conclusions: This study provides a more comprehensive view of the ncRNA transcriptome in fly as well as evidence for differential expression of CRSs during development and in cell lines. [ABSTRACT FROM AUTHOR]

Simple Summary: In humans, a dietary intake of omega-3 polyunsaturated fatty acids along with antioxidants has been shown to have anti-inflammatory and antioxidant activities. In pigs, on the other hand, there are few studies dealing with the use of omega-3 polyunsaturated fatty acids in the diet. For this reason, our study aimed to investigate the differences in gene expression of the Longissimus thoracis muscle of Italian Large White pigs fed with four different diets: a standard diet for growing-finishing pigs and three experimental diets; one supplemented with extruded linseed, a source of omega-3 polyunsaturated fatty acids, another with extruded linseed plus vitamin E and selenium as antioxidants, and another with extruded linseed plus oregano and grape skin extracts, which are natural polyphenols. From the results of the expression analysis, it was possible to deduce that, in the diets, the oxidative stability of the n-3 fatty acids increased, consistent with an increase in the fluidity of cell membranes, and increasing the anti-inflammatory potential of muscle. This can determine the high quality of the muscle tissue as regards the lipid composition; consequently, the meat will be qualitatively better for human health. The addition of n-3 polyunsaturated fatty acids (n-3 PUFAs) to the swine diet increases their content in muscle cells, and the additional supplementation of antioxidants promotes their oxidative stability. However, to date, the functionality of these components within muscle tissue is not well understood. Using a published RNA-seq dataset and a selective workflow, the study aimed to find the differences in gene expression and investigate how differentially expressed genes (DEGs) were implicated in the cellular composition and metabolism of muscle tissue of 48 Italian Large White pigs under different dietary conditions. A functional enrichment analysis of DEGs, using Cytoscape, revealed that the diet enriched with extruded linseed and supplemented with vitamin E and selenium promoted a more rapid and massive immune system response because the overall function of muscle tissue was improved, while those enriched with extruded linseed and supplemented with grape skin and oregano extracts promoted the presence and oxidative stability of n-3 PUFAs, increasing the anti-inflammatory potential of the muscular tissue. [ABSTRACT FROM AUTHOR]

Summary: With the increasing amount of newly discovered non-coding RNAs, the interactions between RNA molecules become an increasingly important aspect for characterizing their functionality. Many computational tools have been developed to predict the formation of duplexes between two RNAs, either based on single sequences or alignments of homologous sequences. Here, we present RILogo, a program to visualize inter- and intramolecular base pairing between two RNA molecules. The input for RILogo is a pair of structure-annotated sequences or alignments. In the latter case, RILogo displays the alignments in the form of sequence logos, including the mutual information of base paired columns. We also introduce two novel mutual information based measures that weigh the covariance information by the evolutionary distances of the aligned sequences. We show that the new measures have an increased accuracy compared with previous mutual information measures.Availability and implementation: RILogo is freely available as a stand-alone program and is accessible via a web server at http://rth.dk/resources/rilogo.Contact: pmenzel@gmail.comSupplementary Information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Motivation: Predicting RNA–RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA–RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA–RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences.Results: PETcofold's ability to predict RNA–RNA interactions was evaluated on a carefully curated dataset of 32 bacterial small RNAs and their targets, which was manually extracted from the literature. For evaluation of both RNA–RNA interaction and structure prediction, we were able to extract only a few high-quality examples: one vertebrate small nucleolar RNA and four bacterial small RNAs. For these we show that the prediction can be improved by our comparative approach. Furthermore, PETcofold was evaluated on controlled data with phylogenetically simulated sequences enriched for covariance patterns at the interaction sites. We observed increased performance with increased amounts of covariance.Availability: The program PETcofold is available as source code and can be downloaded from http://rth.dk/resources/petcofold.Contact: gorodkin@rth.dk; backofen@informatik.uni-freiburg.deSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background: Many regulatory non-coding RNAs (ncRNAs) function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting these RNA interactions is essential for functional studies of putative ncRNAs or for the design of artificial RNAs. Many ncRNAs show clear signs of undergoing compensating base changes over evolutionary time. Here, we postulate that a non-negligible part of the existing RNARNA interactions contain preserved but covarying patterns of interactions. Methods: We present a novel method that takes compensating base changes across the binding sites into account. The algorithm works in two steps on two pre-generated multiple alignments. In the first step, individual base pairs with high reliability are found using the PETfold algorithm, which includes evolutionary and thermodynamic properties. In step two (where high reliability base pairs from step one are constrained as unpaired), the principle of cofolding is combined with hierarchical folding. The final prediction of intra- and inter-molecular base pairs consists of the reliabilities computed from the constrained expected accuracy scoring, which is an extended version of that used for individual multiple alignments. Results: We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNARNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach. [ABSTRACT FROM AUTHOR]

[Display omitted] • CHMP2B heterozygous microglia display "tolerant" immune depleted profile, whilst homozygous CHMP2B microglia are hyperactive with proinflammatory profile. • Metabolic defects are key factors in the CHMP2B microglia activity. • Mild immune boosting could be a beneficial therapeutic approach in FTD3 patients with CHMP2B heterozygous mutations. Frontotemporal dementia (FTD) is a common cause of early-onset dementia, with no current treatment options. FTD linked to chromosome 3 (FTD3) is a rare sub-form of the disease, caused by a point mutation in the Charged Multivesicular Body Protein 2B (CHMP2B). This mutation causes neuronal phenotypes, such as mitochondrial deficiencies, accompanied by metabolic changes and interrupted endosomal-lysosomal fusion. However, the contribution of glial cells to FTD3 pathogenesis has, until recently, been largely unexplored. Glial cells play an important role in most neurodegenerative disorders as drivers and facilitators of neuroinflammation. Microglia are at the center of current investigations as potential pro-inflammatory drivers. While gliosis has been observed in FTD3 patient brains, it has not yet been systematically analyzed. In the light of this, we investigated the role of microglia in FTD3 by implementing human induced pluripotent stem cells (hiPSC) with either a heterozygous or homozygous CHMP2B mutation, introduced into a healthy control hiPSC line via CRISPR-Cas9 precision gene editing. These hiPSC were differentiated into microglia to evaluate the pro-inflammatory profile and metabolic state. Moreover, hiPSC-derived neurons were cultured with conditioned microglia media to investigate disease specific interactions between the two cell populations. Interestingly, we identified two divergent inflammatory microglial phenotypes resulting from the underlying mutations: a severe pro-inflammatory profile in CHMP2B homozygous FTD3 microglia, and an "unresponsive" CHMP2B heterozygous FTD3 microglial state. These findings correlate with our observations of increased phagocytic activity in CHMP2B homozygous, and impaired protein degradation in CHMP2B heterozygous FTD3 microglia. Metabolic mapping confirmed these differences, revealing a metabolic reprogramming of the CHMP2B FTD3 microglia, displayed as a compensatory up-regulation of glutamine metabolism in the CHMP2B homozygous FTD3 microglia. Intriguingly, conditioned CHMP2B homozygous FTD3 microglia media caused neurotoxic effects, which was not evident for the heterozygous microglia. Strikingly, IFN-γ treatment initiated an immune boost of the CHMP2B heterozygous FTD3 microglia, and conditioned microglia media exposure promoted neural outgrowth. Our findings indicate that the microglial profile, activity, and behavior is highly dependent on the status of the CHMP2B mutation. Our results suggest that the heterozygous state of the mutation in FTD3 patients could potentially be exploited in form of immune-boosting intervention strategies to counteract neurodegeneration. [ABSTRACT FROM AUTHOR]

Domestic dogs share the same environment as humans, and they represent a valuable animal model to study naturally-occurring human disease. Platelet proteomics holds promise for the discovery of biomarkers that capture the contribution of platelets to the pathophysiology of many disease states, however, canine platelet proteomic studies are lacking. Our study objectives were to establish a protocol for proteomic identification and quantification of the thrombin-activated canine platelet secretome (CAPS), and to compare the CAPS proteins to human and murine platelet proteomic data. Washed platelets were isolated from healthy dogs, and stimulated with saline (control) or gamma-thrombin (releasate). Proteins were separated by SDS-page, trypsin-digested and analyzed by liquid chromatography and tandem mass spectrometry (MS). CAPS proteins were defined as those with a MS1-abundance ratio of two or more for releasate vs. unstimulated saline control. A total of 1,918 proteins were identified, with 908 proteins common to all dogs and 693 characterized as CAPS proteins. CAPS proteins were similar to human and murine platelet secretomes and were highly represented in hemostatic pathways. Differences unique to CAPS included replacement of platelet factor 4 with other cleavage products of platelet basic protein (e.g. interleukin-8), novel proteins (e.g. C-C motif chemokine 14), and proteins in relatively high (e.g. protease nexin-1) or low (e.g. von Willebrand factor) abundance. This study establishes the first in-depth platelet releasate proteome from healthy dogs with a reference database of 693 CAPS proteins. Similarities between CAPS and the human secretome confirm the utility of dogs as translational models of human disease, but we also identify differences unique to canine platelets. Our findings provide a resource for further investigations into disease-related CAPS profiles, and for comparative pathway analyses of platelet activation among species. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive and irreversible brain disorder, which can occur either sporadically, due to a complex combination of environmental, genetic, and epigenetic factors, or because of rare genetic variants in specific genes (familial AD, or fAD). A key hallmark of AD is the accumulation of amyloid beta (Aβ) and Tau hyperphosphorylated tangles in the brain, but the underlying pathomechanisms and interdependencies remain poorly understood. Here, we identify and characterise gene expression changes related to two fAD mutations (A79V and L150P) in the Presenilin-1 (PSEN1) gene. We do this by comparing the transcriptomes of glutamatergic forebrain neurons derived from fAD-mutant human induced pluripotent stem cells (hiPSCs) and their individual isogenic controls generated via precision CRISPR/Cas9 genome editing. Our analysis of Poly(A) RNA-seq data detects 1111 differentially expressed coding and non-coding genes significantly altered in fAD. Functional characterisation and pathway analysis of these genes reveal profound expression changes in constituents of the extracellular matrix, important to maintain the morphology, structural integrity, and plasticity of neurons, and in genes involved in calcium homeostasis and mitochondrial oxidative stress. Furthermore, by analysing total RNA-seq data we reveal that 30 out of 31 differentially expressed circular RNA genes are significantly upregulated in the fAD lines, and that these may contribute to the observed protein-coding gene expression changes. The results presented in this study contribute to a better understanding of the cellular mechanisms impacted in AD neurons, ultimately leading to neuronal damage and death. • Extracellular matrix components are altered in fAD neurons compared to controls • Merging GENCODE and FANTOM-CAT annotations improves lncRNA identification in RNA-seq • CircRNAs are predominantly upregulated in fAD neurons compared to controls • Competing endogenous RNAs may contribute to gene expression modulation in fAD [ABSTRACT FROM AUTHOR]

Motivation: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. Results: Here, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments. [ABSTRACT FROM AUTHOR]

• The Bacillaceae-1 RNA motif consists of two distinct classes. • Reverse complementary B-1 structure upstream of 16S rRNA has one stable motif. • Intergenic B-1 motifs have high structure diversity and may act as structural switch. Non-coding RNAs are key regulatory players in bacteria. Many computationally predicted non-coding RNAs, however, lack functional associations. An example is the Bacillaceae-1 RNA motif, whose Rfam model consists of two hairpin loops. We find the motif conserved in nine of 13 non-pathogenic strains of the genus Bacillus but only in one pathogenic strain. To elucidate functional characteristics, we studied 118 hits of the Rfam model in 11 Bacillus spp. and found two distinct classes based on the ensemble diversity of their RNA secondary structure and the genomic context concerning the ribosomal RNA (rRNA) cluster. Forty hits are associated with the rRNA cluster, of which all 19 hits upstream flanking of 16S rRNA have a reverse complementary structure of low structural diversity. Fifty-two hits have large ensemble diversity, of which 38 are located between two coding genes. For eight hits in Bacillus subtilis , we investigated public expression data under various conditions and observed either the forward or the reverse complementary motif expressed. Five hits are associated with the rRNA cluster. Four of them are located upstream of the 16S rRNA and are not transcriptionally active, but instead, their reverse complements with low structural diversity are expressed together with the rRNA cluster. The three other hits are located between two coding genes in non-conserved genomic loci. Two of them are independently expressed from their surrounding genes and are structurally diverse. In summary, we found that Bacillaceae-1 RNA motifs upstream flanking of ribosomal RNA clusters tend to have one stable structure with the reverse complementary motif expressed in B. subtilis. In contrast, a subgroup of intergenic motifs has the thermodynamic potential for structural switches. [ABSTRACT FROM AUTHOR]

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 dec 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 dec 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. [ABSTRACT FROM AUTHOR]

Self-contained structured domains of RNA sequences have often distinct molecular functions. Determining the boundaries of structured domains of a non-coding RNA (ncRNA) is needed for many ncRNA gene finder programs that predict RNA secondary structures in aligned genomes because these methods do not necessarily provide precise information about the boundaries or the location of the RNA structure inside the predicted ncRNA. Even without having a structure prediction, it is of interest to search for structured domains, such as for finding common RNA motifs in RNA-protein binding assays. The precise definition of the boundaries are essential for downstream analyses such as RNA structure modelling, e.g., through covariance models, and RNA structure clustering for the search of common motifs. Such efforts have so far been focused on single sequences, thus here we present a comparison for boundary definition between single sequence and multiple sequence alignments. We also present a novel approach, named RNAbound, for finding the boundaries that are based on probabilities of evolutionarily conserved base pairings. We tested the performance of two different methods on a limited number of Rfam families using the annotated structured RNA regions in the human genome and their multiple sequence alignments created from 14 species. The results show that multiple sequence alignments improve the boundary prediction for branched structures compared to single sequences independent of the chosen method. The actual performance of the two methods differs on single hairpin structures and branched structures. For the RNA families with branched structures, including transfer RNA (tRNA) and small nucleolar RNAs (snoRNAs), RNAbound improves the boundary predictions using multiple sequence alignments to median differences of −6 and −11.5 nucleotides (nts) for left and right boundary, respectively (window size of 200 nts). [ABSTRACT FROM AUTHOR]