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RESEARCH PRODUCT
RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.
Giovanni PercontiGiorgio BertolazziSerena BivonaSalvatore FeoAgata GiallongoMichele TumminelloClaudia CoronnelloFlavia ContinoPatrizia Rubinosubject
Chromatin ImmunoprecipitationSupport Vector MachineRIP-Chip data analysisMiRNA bindingComputational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryAutoantigens03 medical and health sciencesOpen Reading Frames0302 clinical medicineStructural BiologymicroRNARIP-Chip data analysiCoding regionGene silencingHumansRNA MessengerMolecular BiologyGenelcsh:QH301-705.5030304 developmental biology0303 health sciencesBinding SitesApplied MathematicsGene Expression ProfilingResearchRNARNA-Binding ProteinsmicroRNA target predictionRISC proteins AGO2 and GW182Computer Science ApplicationsSettore BIO/18 - GeneticaMicroRNAslcsh:Biology (General)Gene Expression Regulation030220 oncology & carcinogenesismicroRNA regulatory activityArgonaute ProteinsMCF-7 Cellslcsh:R858-859.7DNA microarrayRIP-Chipdescription
Background MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Methods We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipitated fraction and the unbound sample resulting from the RIP experiment. We used the expression profile of the input sample to compute several variables, using formulae capable of integrating the information on miRNA binding sites, both in the 3’UTR and coding regions, with miRNA and mRNA expression level profiles. We compared immunoprecipitated vs unbound samples to determine the enriched or underrepresented genes in the immunoprecipitated fractions, independently for AGO2 and GW182 related samples. Results For each of the two proteins, we trained and tested several support vector machine algorithms capable of distinguishing the enriched from the underrepresented genes that were experimentally detected. The most efficient algorithm for distinguishing the enriched genes in AGO2 immunoprecipitated samples was trained by using variables involving the number of binding sites in both the 3’UTR and coding region, integrated with the miRNA expression profile, as expected for miRNA targets. On the other hand, we found that the best variable for distinguishing the enriched genes in the GW182 immunoprecipitated samples was the length of the coding region. Conclusions Due to the major role of GW182 in GW/P-bodies, our data suggests that the AGO2-GW182 RISC recruits genes based on miRNA binding sites in the 3’UTR and coding region, but only the longer mRNAs probably remain sequestered in GW/P-bodies, functioning as a repository for translationally silenced RNAs. Electronic supplementary material The online version of this article (10.1186/s12859-019-2683-y) contains supplementary material, which is available to authorized users.
year | journal | country | edition | language |
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2019-04-01 | BMC bioinformatics |