dc.contributorUTFPR - CÂMPUS CORNELIO PROCOPIO
dc.contributorUniversity Leipzig
dc.contributorUniversity of Leipzig
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2019-10-06T15:18:04Z
dc.date.accessioned2022-12-19T18:24:03Z
dc.date.available2019-10-06T15:18:04Z
dc.date.available2022-12-19T18:24:03Z
dc.date.created2019-10-06T15:18:04Z
dc.date.issued2017-05-30
dc.identifierBriefings in Bioinformatics, v. 19, n. 6, p. 1273-1289, 2017.
dc.identifier1477-4054
dc.identifier1467-5463
dc.identifierhttp://hdl.handle.net/11449/186862
dc.identifier10.1093/bib/bbx058
dc.identifier2-s2.0-85040539277
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5367900
dc.description.abstractThe competing endogenous RNA hypothesis has gained increasing attention as a potential global regulatory mechanism of microRNAs (miRNAs), and as a powerful tool to predict the function of many noncoding RNAs, including miRNAs themselves. Most studies have been focused on animals, although target mimic (TMs) discovery as well as important computational and experimental advances has been developed in plants over the past decade. Thus, our contribution summarizes recent progresses in computational approaches for research of miRNA:TM interactions. We divided this article in three main contributions. First, a general overview of research on TMs in plants is presented with practical descriptions of the available literature, tools, data, databases and computational reports. Second, we describe a common protocol for the computational and experimental analyses of TM. Third, we provide a bioinformatics approach for the prediction of TM motifs potentially cross-targeting both members within the same or from different miRNA families, based on the identification of consensus miRNA-binding sites from known TMs across sequenced genomes, transcriptomes and known miRNAs. This computational approach is promising because, in contrast to animals, miRNA families in plants are large with identical or similar members, several of which are also highly conserved. From the three consensus TM motifs found with our approach: MIM166, MIM171 and MIM159/319, the last one has found strong support on the recent experimental work by Reichel and Millar [Specificity of plant microRNA TMs: cross-targeting of mir159 and mir319. J Plant Physiol 2015;180:45-8]. Finally, we stress the discussion on the major computational and associated experimental challenges that have to be faced in future ceRNA studies.
dc.languageeng
dc.relationBriefings in Bioinformatics
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectBioinformatics
dc.subjectCeRNA
dc.subjectComputational method
dc.subjectConsensus ceRNA motif
dc.subjectNoncoding RNA
dc.subjectTarget mimics
dc.titleCeRNAs in plants: Computational approaches and associated challenges for target mimic research
dc.typeArtículos de revistas


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