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  • 1
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 20 March 2018, Vol.115(12), pp.E2859-E2868
    Description: Disturbed RNA processing and subcellular transport contribute to the pathomechanisms of motoneuron diseases such as amyotrophic lateral sclerosis and spinal muscular atrophy. RNA-binding proteins are involved in these processes, but the mechanisms by which they regulate the subcellular diversity of transcriptomes, particularly in axons, are not understood. Heterogeneous nuclear ribonucleoprotein R (hnRNP R) interacts with several proteins involved in motoneuron diseases. It is located in axons of developing motoneurons, and its depletion causes defects in axon growth. Here, we used individual nucleotide-resolution cross-linking and immunoprecipitation (iCLIP) to determine the RNA interactome of hnRNP R in motoneurons. We identified ∼3,500 RNA targets, predominantly with functions in synaptic transmission and axon guidance. Among the RNA targets identified by iCLIP, the noncoding RNA 7SK was the top interactor of hnRNP R. We detected 7SK in the nucleus and also in the cytosol of motoneurons. In axons, 7SK localized in close proximity to hnRNP R, and depletion of hnRNP R reduced axonal 7SK. Furthermore, suppression of 7SK led to defective axon growth that was accompanied by axonal transcriptome alterations similar to those caused by hnRNP R depletion. Using a series of 7SK-deletion mutants, we show that the function of 7SK in axon elongation depends on its interaction with hnRNP R but not with the PTEF-B complex involved in transcriptional regulation. These results propose a role for 7SK as an essential interactor of hnRNP R to regulate its function in axon maintenance.
    Keywords: 7sk ; Axon ; Hnrnp R ; Iclip ; Motoneuron ; Axons -- Physiology ; Heterogeneous-Nuclear Ribonucleoproteins -- Metabolism ; Motor Neurons -- Physiology ; RNA, Small Nuclear -- Metabolism
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 2
    Language: English
    In: The Journal of biological chemistry, 13 February 2015, Vol.290(7), pp.4192-201
    Description: The prokaryotic immune system CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated) is a defense system that protects prokaryotes against foreign DNA. The short CRISPR RNAs (crRNAs) are central components of this immune system. In CRISPR-Cas systems type I and III, crRNAs are generated by the endonuclease Cas6. We developed a Cas6b-independent crRNA maturation pathway for the Haloferax type I-B system in vivo that expresses a functional crRNA, which we termed independently generated crRNA (icrRNA). The icrRNA is effective in triggering degradation of an invader plasmid carrying the matching protospacer sequence. The Cas6b-independent maturation of the icrRNA allowed mutation of the repeat sequence without interfering with signals important for Cas6b processing. We generated 23 variants of the icrRNA and analyzed them for activity in the interference reaction. icrRNAs with deletions or mutations of the 3' handle are still active in triggering an interference reaction. The complete 3' handle could be removed without loss of activity. However, manipulations of the 5' handle mostly led to loss of interference activity. Furthermore, we could show that in the presence of an icrRNA a strain without Cas6b (Δcas6b) is still active in interference.
    Keywords: Archaea ; Crispr/Cas ; Cas6 ; Haloferax Volcanii ; Type I-B ; Crrna ; Gene Expression Regulation, Archaeal ; Archaeal Proteins -- Immunology ; Crispr-Cas Systems -- Immunology ; Clustered Regularly Interspaced Short Palindromic Repeats -- Immunology ; Haloferax Volcanii -- Immunology ; Plasmids -- Genetics ; RNA, Archaeal -- Immunology
    ISSN: 00219258
    E-ISSN: 1083-351X
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  • 3
    In: Nature, 2017
    Description: Transposable elements are viewed as 'selfish genetic elements', yet they contribute to gene regulation and genome evolution in diverse ways. More than half of the human genome consists of transposable elements. Alu elements belong to the short interspersed nuclear element (SINE) family of repetitive elements, and with over 1 million insertions they make up more than 10% of the human genome. Despite their abundance and the potential evolutionary advantages they confer, Alu elements can be mutagenic to the host as they can act as splice acceptors, inhibit translation of mRNAs and cause genomic instability. Alu elements are the main targets of the RNA-editing enzyme ADAR and the formation of Alu exons is suppressed by the nuclear ribonucleoprotein HNRNPC, but the broad effect of massive secondary structures formed by inverted-repeat Alu elements on RNA processing in the nucleus remains unknown. Here we show that DHX9, an abundant nuclear RNA helicase, binds specifically to inverted-repeat Alu elements that are transcribed as parts of genes. Loss of DHX9 leads to an increase in the number of circular-RNA-producing genes and amount of circular RNAs, translational repression of reporters containing inverted-repeat Alu elements, and transcriptional rewiring (the creation of mostly nonsensical novel connections between exons) of susceptible loci. Biochemical purifications of DHX9 identify the interferon-inducible isoform of ADAR (p150), but not the constitutively expressed ADAR isoform (p110), as an RNA-independent interaction partner. Co-depletion of ADAR and DHX9 augments the double-stranded RNA accumulation defects, leading to increased circular RNA production, revealing a functional link between these two enzymes. Our work uncovers an evolutionarily conserved function of DHX9. We propose that it acts as a nuclear RNA resolvase that neutralizes the immediate threat posed by transposon insertions and allows these elements to evolve as tools for the post-transcriptional regulation of gene expression.
    Keywords: Sciences (General) ; Physics;
    ISSN: 0028-0836
    E-ISSN: 1476-4687
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  • 4
    Language: English
    In: PLoS ONE, Vol.11(9), p.e0162466
    Description: Genome-wide association studies (GWAS) evaluate associations between genetic variants and a trait or disease of interest free of prior biological hypotheses. GWAS require stringent correction for multiple testing, with genome-wide significance typically defined as association p-value 〈5*10-8. This study presents a new tool that uses external information about genes to prioritize SNP associations (GenToS). For a given list of candidate genes, GenToS calculates an appropriate statistical significance threshold and then searches for trait-associated variants in summary statistics from human GWAS. It thereby allows for identifying trait-associated genetic variants that do not meet genome-wide significance. The program additionally tests for enrichment of significant candidate gene associations in the human GWAS data compared to the number expected by chance. As proof of principle, this report used external information from a comprehensive resource of genetically manipulated and systematically phenotyped mice. Based on selected murine phenotypes for which human GWAS data for corresponding traits were publicly available, several candidate gene input lists were derived. Using GenToS for the investigation of candidate genes underlying murine skeletal phenotypes in data from a large human discovery GWAS meta-analysis of bone mineral density resulted in the identification of significantly associated variants in 29 genes. Index variants in 28 of these loci were subsequently replicated in an independent GWAS replication step, highlighting that they are true positive associations. One signal, COL11A1, has not been discovered through GWAS so far and represents a novel human candidate gene for altered bone mineral density. The number of observed genes that contained significant SNP associations in human GWAS based on murine candidate gene input lists was much greater than the number expected by chance across several complex human traits (enrichment p-value as low as 10-10). GenToS can be used with any candidate gene list, any GWAS summary file, runs on a desktop computer and is freely available.
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 5
    Language: English
    In: PLoS ONE, Vol.8(5), p.e62732
    Description: Src homology 2 (SH2) domains are the largest family of the peptide-recognition modules (PRMs) that bind to phosphotyrosine containing peptides. Knowledge about binding partners of SH2-domains is key for a deeper understanding of different cellular processes. Given the high binding specificity of SH2, in-silico ligand peptide prediction is of great interest. Currently however, only a few approaches have been published for the prediction of SH2-peptide interactions. Their main shortcomings range from limited coverage, to restrictive modeling assumptions (they are mainly based on position specific scoring matrices and do not take into consideration complex amino acids inter-dependencies) and high computational complexity. We propose a simple yet effective machine learning approach for a large set of known human SH2 domains. We used comprehensive data from micro-array and peptide-array experiments on 51 human SH2 domains. In order to deal with the high data imbalance problem and the high signal-to-noise ration, we casted the problem in a semi-supervised setting. We report competitive predictive performance w.r.t. state-of-the-art. Specifically we obtain 0.83 AUC ROC and 0.93 AUC PR in comparison to 0.71 AUC ROC and 0.87 AUC PR previously achieved by the position specific scoring matrices (PSSMs) based SMALI approach. Our work provides three main contributions. First, we showed that better models can be obtained when the information on the non-interacting peptides (negative examples) is also used. Second, we improve performance when considering high order correlations between the ligand positions employing regularization techniques to effectively avoid overfitting issues. Third, we developed an approach to tackle the data imbalance problem using a semi-supervised strategy. Finally, we performed a genome-wide prediction of human SH2-peptide binding, uncovering several findings of biological relevance. We make our models and genome-wide predictions, for all the 51 SH2-domains, freely available to the scientific community under the following URLs: http://www.bioinf.uni-freiburg.de/Software/SH2PepInt/SH2PepInt.tar.gz and http://www.bioinf.uni-freiburg.de/Software/SH2PepInt/Genome-wide-predictions.tar.gz, respectively.
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 6
    Language: English
    In: PLoS ONE, Vol.8(2), p.e56470
    Description: The CRISPR-Cas (Clustered Regularly Interspaced Short Palindrome Repeats--CRISPR associated proteins) system provides adaptive immunity in archaea and bacteria. A hallmark of CRISPR-Cas is the involvement of short crRNAs that guide associated proteins in the destruction of invading DNA or RNA. We present three fundamentally distinct processing pathways in the cyanobacterium Synechocystis sp. PCC6803 for a subtype I-D (CRISPR1), and two type III systems (CRISPR2 and CRISPR3), which are located together on the plasmid pSYSA. Using high-throughput transcriptome analyses and assays of transcript accumulation we found all CRISPR loci to be highly expressed, but the individual crRNAs had profoundly varying abundances despite single transcription start sites for each array. In a computational analysis, CRISPR3 spacers with stable secondary structures displayed a greater ratio of degradation products. These structures might interfere with the loading of the crRNAs into RNP complexes, explaining the varying abundancies. The maturation of CRISPR1 and CRISPR2 transcripts depends on at least two different Cas6 proteins. Mutation of gene sll7090, encoding a Cmr2 protein led to the disappearance of all CRISPR3-derived crRNAs, providing in vivo evidence for a function of Cmr2 in the maturation, regulation of expression, Cmr complex formation or stabilization of CRISPR3 transcripts. Finally, we optimized CRISPR repeat structure prediction and the results indicate that the spacer context can influence individual repeat structures.
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 7
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 10 September 2013, Vol.110(37), pp.E3487-96
    Description: Small RNAs (sRNAs) constitute a large and heterogeneous class of bacterial gene expression regulators. Much like eukaryotic microRNAs, these sRNAs typically target multiple mRNAs through short seed pairing, thereby acting as global posttranscriptional regulators. In some bacteria, evidence for hundreds to possibly more than 1,000 different sRNAs has been obtained by transcriptome sequencing. However, the experimental identification of possible targets and, therefore, their confirmation as functional regulators of gene expression has remained laborious. Here, we present a strategy that integrates phylogenetic information to predict sRNA targets at the genomic scale and reconstructs regulatory networks upon functional enrichment and network analysis (CopraRNA, for Comparative Prediction Algorithm for sRNA Targets). Furthermore, CopraRNA precisely predicts the sRNA domains for target recognition and interaction. When applied to several model sRNAs, CopraRNA revealed additional targets and functions for the sRNAs CyaR, FnrS, RybB, RyhB, SgrS, and Spot42. Moreover, the mRNAs gdhA, lrp, marA, nagZ, ptsI, sdhA, and yobF-cspC were suggested as regulatory hubs targeted by up to seven different sRNAs. The verification of many previously undetected targets by CopraRNA, even for extensively investigated sRNAs, demonstrates its advantages and shows that CopraRNA-based analyses can compete with experimental target prediction approaches. A Web interface allows high-confidence target prediction and efficient classification of bacterial sRNAs.
    Keywords: E. Coli ; RNA–RNA Interaction ; Regulatory RNA ; RNA, Bacterial -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 8
    In: Nucleic Acids Research, 2017, Vol. 45(W1), pp.W435-W439
    Description: The IntaRNA algorithm enables fast and accurate prediction of RNA–RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNA v2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA–RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNA v2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage.
    Keywords: Web Server Issue;
    ISSN: 0305-1048
    E-ISSN: 1362-4962
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  • 9
    Language: English
    In: Nucleic acids research, July 2011, Vol.39(Web Server issue), pp.W107-11
    Description: 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/
    Keywords: Software ; RNA -- Chemistry
    ISSN: 03051048
    E-ISSN: 1362-4962
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  • 10
    Language: English
    In: Nucleic acids research, 06 September 2017, Vol.45(15), pp.8745-8757
    Description: MicroRNAs (miRNAs) are key regulators of cell-fate decisions in development and disease with a vast array of target interactions that can be investigated using computational approaches. For this study, we developed metaMIR, a combinatorial approach to identify miRNAs that co-regulate identified subsets of genes from a user-supplied list. We based metaMIR predictions on an improved dataset of human miRNA-target interactions, compiled using a machine-learning-based meta-analysis of established algorithms. Simultaneously, the inverse dataset of negative interactions not likely to occur was extracted to increase classifier performance, as measured using an expansive set of experimentally validated interactions from a variety of sources. In a second differential mode, candidate miRNAs are predicted by indicating genes to be targeted and others to be avoided to potentially increase specificity of results. As an example, we investigate the neural crest, a transient structure in vertebrate development where miRNAs play a pivotal role. Patterns of metaMIR-predicted miRNA regulation alone partially recapitulated functional relationships among genes, and separate differential analysis revealed miRNA candidates that would downregulate components implicated in cancer progression while not targeting tumour suppressors. Such an approach could aid in therapeutic application of miRNAs to reduce unintended effects. The utility is available at http://rna.informatik.uni-freiburg.de/metaMIR/.
    Keywords: Algorithms ; Gene Regulatory Networks ; Computational Biology -- Methods ; Micrornas -- Genetics
    ISSN: 03051048
    E-ISSN: 1362-4962
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