CRISPRroots: on- and off-target assessment of RNA-seq data in CRISPR-Cas9 edited cells.

The CRISPR-Cas9 genome editing tool is used to study genomic variants and gene knockouts, and can be combined with transcriptomic analyses to measure the effects of such alterations on gene expression. But how can one be sure that differential gene expression is due to a successful intended edit and not to an off-target event, without performing an often resource-demanding genome-wide sequencing of the edited cell or strain? To address this question we developed CRISPRroots: CRISPR-Cas9-mediated edits with accompanying RNA-seq data assessed for on-target and off-target sites. Our method combines Cas9 and guide RNA binding properties, gene expression changes, and sequence variants between edited and non-edited cells to discover potential off-targets. Applied on seven public datasets, CRISPRroots identified critical off-target candidates that were overlooked in all of the corresponding previous studies. CRISPRroots is available via https://rth.dk/resources/crispr.

Does rapid sequence divergence preclude RNA structure conservation in vertebrates?

Accelerated evolution of any portion of the genome is of significant interest, potentially signaling positive selection of phenotypic traits and adaptation. Accelerated evolution remains understudied for structured RNAs, despite the fact that an RNA's structure is often key to its function. RNA structures are typically characterized by compensatory (structure-preserving) basepair changes that are unexpected given the underlying sequence variation, i.e., they have evolved through negative selection on structure. We address the question of how fast the primary sequence of an RNA can change through evolution while conserving its structure. Specifically, we consider predicted and known structures in vertebrate genomes. After careful control of false discovery rates, we obtain 13 de novo structures (and three known Rfam structures) that we predict to have rapidly evolving sequences-defined as structures where the primary sequences of human and mouse have diverged at least twice as fast (1.5 times for Rfam) as nearby neutrally evolving sequences. Two of the three known structures function in translation inhibition related to infection and immune response. We conclude that rapid sequence divergence does not preclude RNA structure conservation in vertebrates, although these events are relatively rare.

The transcriptomic landscape of neurons carrying PSEN1 mutations reveals changes in extracellular matrix components and non-coding gene expression.

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 (Aß) 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.

Alteration of microglial metabolism and inflammatory profile contributes to neurotoxicity in a hiPSC-derived microglia model of frontotemporal dementia 3.

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.

CRISPRi screen for enhancing heterologous α-amylase yield in Bacillus subtilis.

Yield improvements in cell factories can potentially be obtained by fine-tuning the regulatory mechanisms for gene candidates. In pursuit of such candidates, we performed RNA-sequencing of two α-amylase producing Bacillus strains and predict hundreds of putative novel non-coding transcribed regions. Surprisingly, we found among hundreds of non-coding and structured RNA candidates that non-coding genomic regions are proportionally undergoing the highest changes in expression during fermentation. Since these classes of RNA are also understudied, we targeted the corresponding genomic regions with CRIPSRi knockdown to test for any potential impact on the yield. From differentially expression analysis, we selected 53 non-coding candidates. Although CRISPRi knockdowns target both the sense and the antisense strand, the CRISPRi experiment cannot link causes for yield changes to the sense or antisense disruption. Nevertheless, we observed on several instances with strong changes in enzyme yield. The knockdown targeting the genomic region for a putative antisense RNA of the 3' UTR of the skfA-skfH operon led to a 21% increase in yield. In contrast, the knockdown targeting the genomic regions of putative antisense RNAs of the cytochrome c oxidase subunit 1 (ctaD), the sigma factor sigH, and the uncharacterized gene yhfT decreased yields by 31 to 43%.

Flagella disruption in Bacillus subtilis increases amylase production yield.

BACKGROUND: Bacillus subtilis is a Gram-positive bacterium used as a cell factory for protein production. Over the last decades, the continued optimization of production strains has increased yields of enzymes, such as amylases, and made commercial applications feasible. However, current yields are still significantly lower than the theoretically possible yield based on the available carbon sources. In its natural environment, B. subtilis can respond to unfavorable growth conditions by differentiating into motile cells that use flagella to swim towards available nutrients. RESULTS: In this study, we analyze existing transcriptome data from a B. subtilis α-amylase production strain at different time points during a 5-day fermentation. We observe that genes of the fla/che operon, essential for flagella assembly and motility, are differentially expressed over time. To investigate whether expression of the flagella operon affects yield, we performed CRISPR-dCas9 based knockdown of the fla/che operon with sgRNA target against the genes flgE, fliR, and flhG, respectively. The knockdown resulted in inhibition of mobility and a striking 2-threefold increase in α-amylase production yield. Moreover, replacing flgE (required for flagella hook assembly) with an erythromycin resistance gene followed by a transcription terminator increased α-amylase yield by about 30%. Transcript levels of the α-amylase were unaltered in the CRISPR-dCas9 knockdowns as well as the flgE deletion strain, but all manipulations disrupted the ability of cells to swim on agar. CONCLUSIONS: We demonstrate that the disruption of flagella in a B. subtilis α-amylase production strain, either by CRISPR-dCas9-based knockdown of the operon or by replacing flgE with an erythromycin resistance gene followed by a transcription terminator, increases the production of α-amylase in small-scale fermentation.

The identification and functional annotation of RNA structures conserved in vertebrates.

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for conserved RNA structures (CRSs), leveraging structure-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ∼516,000 human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (1) colocalize consistently with binding sites of the same RNA binding proteins (RBPs) or (2) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared expression and shared structure despite low abundance and low sequence identity. About 30,000 CRS regions are located near coding or long noncoding RNA genes or within enhancers. Structured (CRS overlapping) enhancer RNAs and extended 3' ends have significantly increased expression levels over their nonstructured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality.

Identification and characterization of novel conserved RNA structures in Drosophila.

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.

RNAscClust: clustering RNA sequences using structure conservation and graph based motifs.

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. AVAILABILITY AND IMPLEMENTATION: RNAscClust is available at http://www.bioinf.uni-freiburg.de/Software/RNAscClust . CONTACT: gorodkin@rth.dk or backofen@informatik.uni-freiburg.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain.

A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus.

Optimizing RNA structures by sequence extensions using RNAcop.

A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop.

The RNAsnp web server: predicting SNP effects on local RNA secondary structure.

The function of many non-coding RNA genes and cis-regulatory elements of messenger RNA largely depends on the structure, which is in turn determined by their sequence. Single nucleotide polymorphisms (SNPs) and other mutations may disrupt the RNA structure, interfere with the molecular function and hence cause a phenotypic effect. RNAsnp is an efficient method to predict the effect of SNPs on local RNA secondary structure based on the RNA folding algorithms implemented in the Vienna RNA package. The SNP effects are quantified in terms of empirical P-values, which, for computational efficiency, are derived from extensive pre-computed tables of distributions of substitution effects as a function of gene length and GC content. Here, we present a web service that not only provides an interface for RNAsnp but also features a graphical output representation. In addition, the web server is connected to a local mirror of the UCSC genome browser database that enables the users to select the genomic sequences for analysis and visualize the results directly in the UCSC genome browser. The RNAsnp web server is freely available at: http://rth.dk/resources/rnasnp/.

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.

Sequence and expression analysis of gaps in human chromosome 20.

The finished human genome-assemblies comprise several hundred un-sequenced euchromatic gaps, which may be rich in long polypurine/polypyrimidine stretches. Human chromosome 20 (chr 20) currently has three unfinished gaps remaining on its q-arm. All three gaps are within gene-dense regions and/or overlap disease-associated loci, including the DLGAP4 locus. In this study, we sequenced ∼ 99% of all three unfinished gaps on human chr 20, determined their complete genomic sizes and assessed epigenetic profiles using a combination of Sanger sequencing, mate pair paired-end high-throughput sequencing and chromatin, methylation and expression analyses. We found histone 3 trimethylated at Lysine 27 to be distributed across all three gaps in immortalized B-lymphocytes. In one gap, five novel CpG islands were predominantly hypermethylated in genomic DNA from peripheral blood lymphocytes and human cerebellum. One of these CpG islands was differentially methylated and paternally hypermethylated. We found all chr 20 gaps to comprise structured non-coding RNAs (ncRNAs) and to be conserved in primates. We verified expression for 13 candidate ncRNAs, some of which showed tissue specificity. Four ncRNAs expressed within the gap at DLGAP4 show elevated expression in the human brain. Our data suggest that unfinished human genome gaps are likely to comprise numerous functional elements.

Patent data-driven analysis of literature associations with changing innovation trends.

Patents are essential for transferring scientific discoveries to meaningful products that benefit societies. While the academic community focuses on the number of citations to rank scholarly works according to their "scientific merit," the number of citations is unrelated to the relevance for patentable innovation. To explore associations between patents and scholarly works in publicly available patent data, we propose to utilize statistical methods that are commonly used in biology to determine gene-disease associations. We illustrate their usage on patents related to biotechnological trends of high relevance for food safety and ecology, namely the CRISPR-based gene editing technology (>60,000 patents) and cyanobacterial biotechnology (>33,000 patents). Innovation trends are found through their unexpected large changes of patent numbers in a time-series analysis. From the total set of scholarly works referenced by all investigated patents (~254,000 publications), we identified ~1,000 scholarly works that are statistical significantly over-represented in the references of patents from changing innovation trends that concern immunology, agricultural plant genomics, and biotechnological engineering methods. The detected associations are consistent with the technical requirements of the respective innovations. In summary, the presented data-driven analysis workflow can identify scholarly works that were required for changes in innovation trends, and, therefore, is of interest for researches that would like to evaluate the relevance of publications beyond the number of citations.

Clusters of mammalian conserved RNA structures in UTRs associate with RBP binding sites.

RNA secondary structures play essential roles in the formation of the tertiary structure and function of a transcript. Recent genome-wide studies highlight significant potential for RNA structures in the mammalian genome. However, a major challenge is assigning functional roles to these structured RNAs. In this study, we conduct a guilt-by-association analysis of clusters of computationally predicted conserved RNA structure (CRSs) in human untranslated regions (UTRs) to associate them with gene functions. We filtered a broad pool of ∼500 000 human CRSs for UTR overlap, resulting in 4734 and 24 754 CRSs from the 5' and 3' UTR of protein-coding genes, respectively. We separately clustered these CRSs for both sets using RNAscClust, obtaining 793 and 2403 clusters, each containing an average of five CRSs per cluster. We identified overrepresented binding sites for 60 and 43 RNA-binding proteins co-localizing with the clustered CRSs. Furthermore, 104 and 441 clusters from the 5' and 3' UTRs, respectively, showed enrichment for various Gene Ontologies, including biological processes such as 'signal transduction', 'nervous system development', molecular functions like 'transferase activity' and the cellular components such as 'synapse' among others. Our study shows that significant functional insights can be gained by clustering RNA structures based on their structural characteristics.

Generating universal anti-CD19 CAR T cells with a defined memory phenotype by CRISPR/Cas9 editing and safety evaluation of the transcriptome.

Introduction: Chimeric antigen receptor-expressing T cells (CAR T cells) have revolutionized cancer treatment, particularly in B cell malignancies. However, the use of autologous T cells for CAR T therapy presents several limitations, including high costs, variable efficacy, and adverse effects linked to cell phenotype. Methods: To overcome these challenges, we developed a strategy to generate universal and safe anti-CD19 CAR T cells with a defined memory phenotype. Our approach utilizes CRISPR/Cas9 technology to target and eliminate the B2M and TRAC genes, reducing graft-versus-host and host-versus-graft responses. Additionally, we selected less differentiated T cells to improve the stability and persistence of the universal CAR T cells. The safety of this method was assessed using our CRISPRroots transcriptome analysis pipeline, which ensures successful gene knockout and the absence of unintended off-target effects on gene expression or transcriptome sequence. Results: In vitro experiments demonstrated the successful generation of functional universal CAR T cells. These cells exhibited potent lytic activity against tumor cells and a reduced cytokine secretion profile. The CRISPRroots analysis confirmed effective gene knockout and no unintended off-target effects, validating it as a pioneering tool for on/off-target and transcriptome analysis in genome editing experiments. Discussion: Our findings establish a robust pipeline for manufacturing safe, universal CAR T cells with a favorable memory phenotype. This approach has the potential to address the current limitations of autologous CAR T cell therapy, offering a more stable and persistent treatment option with reduced adverse effects. The use of CRISPRroots enhances the reliability and safety of gene editing in the development of CAR T cell therapies. Conclusion: We have developed a potent and reliable method for producing universal CAR T cells with a defined memory phenotype, demonstrating both efficacy and safety in vitro. This innovative approach could significantly improve the therapeutic landscape for patients with B cell malignancies.

RNAsnp: efficient detection of local RNA secondary structure changes induced by SNPs.

Structural characteristics are essential for the functioning of many noncoding RNAs and cis-regulatory elements of mRNAs. SNPs may disrupt these structures, interfere with their molecular function, and hence cause a phenotypic effect. RNA folding algorithms can provide detailed insights into structural effects of SNPs. The global measures employed so far suffer from limited accuracy of folding programs on large RNAs and are computationally too demanding for genome-wide applications. Here, we present a strategy that focuses on the local regions of maximal structural change between mutant and wild-type. These local regions are approximated in a "screening mode" that is intended for genome-wide applications. Furthermore, localized regions are identified as those with maximal discrepancy. The mutation effects are quantified in terms of empirical P values. To this end, the RNAsnp software uses extensive precomputed tables of the distribution of SNP effects as function of length and GC content. RNAsnp thus achieves both a noise reduction and speed-up of several orders of magnitude over shuffling-based approaches. On a data set comprising 501 SNPs associated with human-inherited diseases, we predict 54 to have significant local structural effect in the untranslated region of mRNAs.

RILogo: visualizing RNA-RNA interactions.

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.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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

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/