Pharmaco-miR:linking microRNAs and drug effects

MicroRNAs (miRNAs) are short regulatory RNAs that down-regulate gene expression. They are essential for cell homeostasis and active in many disease states. A major discovery is the ability of miRNAs to determine the efficacy of drugs, which has given rise to the field of ‘miRNA pharmacogenomics’ through ‘Pharmaco-miRs’. miRNAs play a significant role in pharmacogenomics by down-regulating genes that are important for drug function. These interactions can be described as triplet sets consisting of a miRNA, a target gene and a drug associated with the gene. We have developed a web server which links miRNA expression and drug function by combining data on miRNA targeting and protein–drug interactions. miRNA targeting information derive from both experimental data and computational predictions, and protein–drug interactions are annotated by the Pharmacogenomics Knowledge base (PharmGKB). Pharmaco-miR’s input consists of miRNAs, genes and/or drug names and the output consists of miRNA pharmacogenomic sets or a list of unique associated miRNAs, genes and drugs. We have furthermore built a database, named Pharmaco-miR Verified Sets (VerSe), which contains miRNA pharmacogenomic data manually curated from the literature, can be searched and downloaded via Pharmaco-miR and informs on trends and generalities published in the field. Overall, we present examples of how Pharmaco-miR provides possible explanations for previously published observations, including how the cisplatin and 5-fluorouracil resistance induced by miR-148a may be caused by miR-148a targeting of the gene KIT. The information is available at www.Pharmaco-miR.org

Dissecting the target specificity of RNase H recruiting oligonucleotides using massively parallel reporter analysis of short RNA motifs

Processing and post-transcriptional regulation of RNA often depend on binding of regulatory molecules to short motifs in RNA. The effects of such interactions are difficult to study, because most regulatory molecules recognize partially degenerate RNA motifs, embedded in a sequence context specific for each RNA. Here, we describe Library Sequencing (LibSeq), an accurate massively parallel reporter method for completely characterizing the regulatory potential of thousands of short RNA sequences in a specific context. By sequencing cDNA derived from a plasmid library expressing identical reporter genes except for a degenerate 7mer subsequence in the 3′UTR, the regulatory effects of each 7mer can be determined. We show that LibSeq identifies regulatory motifs used by RNA-binding proteins and microRNAs. We furthermore apply the method to cells transfected with RNase H recruiting oligonucleotides to obtain quantitative information for >15000 potential target sequences in parallel. These comprehensive datasets provide insights into the specificity requirements of RNase H and allow a specificity measure to be calculated for each tested oligonucleotide. Moreover, we show that inclusion of chemical modifications in the central part of an RNase H recruiting oligonucleotide can increase its sequence-specificity

Evolution of Alternative Splicing Regulation: Changes in Predicted Exonic Splicing Regulators Are Not Associated with Changes in Alternative Splicing Levels in Primates

Alternative splicing is tightly regulated in a spatio-temporal and quantitative manner. This regulation is achieved by a complex interplay between spliceosomal (trans) factors that bind to different sequence (cis) elements. cis-elements reside in both introns and exons and may either enhance or silence splicing. Differential combinations of cis-elements allows for a huge diversity of overall splicing signals, together comprising a complex ‘splicing code’. Many cis-elements have been identified, and their effects on exon inclusion levels demonstrated in reporter systems. However, the impact of interspecific differences in these elements on the evolution of alternative splicing levels has not yet been investigated at genomic level. Here we study the effect of interspecific differences in predicted exonic splicing regulators (ESRs) on exon inclusion levels in human and chimpanzee. For this purpose, we compiled and studied comprehensive datasets of predicted ESRs, identified by several computational and experimental approaches, as well as microarray data for changes in alternative splicing levels between human and chimpanzee. Surprisingly, we found no association between changes in predicted ESRs and changes in alternative splicing levels. This observation holds across different ESR exon positions, exon lengths, and 5′ splice site strengths. We suggest that this lack of association is mainly due to the great importance of context for ESR functionality: many ESR-like motifs in primates may have little or no effect on splicing, and thus interspecific changes at short-time scales may primarily occur in these effectively neutral ESRs. These results underscore the difficulties of using current computational ESR prediction algorithms to identify truly functionally important motifs, and provide a cautionary tale for studies of the effect of SNPs on splicing in human disease

Satanisk symbolbruk i norsk Black metal-kultur

Denne avhandlingen tar for seg satanisk symbolbruk i norsk Black metal-kultur. Fokuset dreier seg rundt hvordan aktører erverver religiøse symboler og terminologi inn i sine musikalske konsepter, og hvordan de selv benytter og forstår denne symbolbruken. Det trekkes paralleller mellom grunnverdier i LaVey-satanisme og Black metal-kultur, med fokus på elementer som individorientering og antikonvensjonalisme. Andre vesentlige fokus er rettet mot aspekter som forholdet mellom musikk og konsept, undergrunn og mainstream, samt symbolsynkretisme og –eklektisisme. Et av hovedargumentene er at personer tilknyttet Black metal-kultur gjennom religiøs symbolbruk utvikler refleksjon over religiøse og metafysiske temaer, og at det gjennom en form for ”søkermentalitet” kan forekomme individuelle religionskonstruksjoner. Gjennomgående ligger Christopher Partridges teori om okkultur som et teoretisk bakteppe for analysen. Også teorier om kulturelle nøkkelsymboler, anerkjennelsespolitikk og grenseoverskridende subkulturell kapital, av henholdsvis Sherry B. Ortner, Charles Taylor og Keith Kahn-Harris er vesentlige analytiske verktøy i avhandlingen. Empirisk sett baserer avhandlingen seg på såkalte fanzine- og webzine-intervjuer, intervjuer fra videodokumentarer, intervjuer og deltakende observasjon fra feltarbeid, sangtekster fra forskjellige Black metal-band, samt avis- og nettartikler

Functional and evolutionary analysis of alternatively spliced genes is consistent with an early eukaryotic origin of alternative splicing-2

<p><b>Copyright information:</b></p><p>Taken from "Functional and evolutionary analysis of alternatively spliced genes is consistent with an early eukaryotic origin of alternative splicing"</p><p>http://www.biomedcentral.com/1471-2148/7/188</p><p>BMC Evolutionary Biology 2007;7():188-188.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2082043.</p><p></p> ancestor of animals, plants and fungi. Dispensable genes (black): the KOG's to which they belong was lost in at least one of the animal or fungal species included in KOG database. Indispensable genes (grey): KOG's present in the seven studied species

Functional and evolutionary analysis of alternatively spliced genes is consistent with an early eukaryotic origin of alternative splicing-0

<p><b>Copyright information:</b></p><p>Taken from "Functional and evolutionary analysis of alternatively spliced genes is consistent with an early eukaryotic origin of alternative splicing"</p><p>http://www.biomedcentral.com/1471-2148/7/188</p><p>BMC Evolutionary Biology 2007;7():188-188.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2082043.</p><p></p>is an estimated interval for intron density of the ancestor of animals and plants (from 3.5 [18] to 7.0 [15]). : Frequency of AS versus intron numbers per gene for the 8 species showing relatively high values of AS. Abbreviations: Hsa (), Mmu (), Gga (), Dre (), Cel (), Dme (), Ath (), Sce (), Spo (), Ecu (), Pfa (), Cne ()