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Submitted by ChenLiang on Fri, 09/02/2016 - 21:59



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Rainbow trout represent an important teleost research model and aquaculture species. As such, rainbow trout are employed in diverse areas of biological research, including basic biological disciplines such as comparative physiology, toxicology, and, since rainbow trout have undergone both teleost- and salmonid-specific rounds of genome duplication, molecular evolution. In recent years, microRNAs (miRNAs, small non-protein coding RNAs) have emerged as important posttranscriptional regulators of gene expression in animals. Given the increasingly recognized importance of miRNAs as an additional layer in the regulation of gene expression and hence biological function, recent efforts using RNA- and genome sequencing approaches have resulted in the creation of several resources for the construction of a comprehensive repertoire of rainbow trout miRNAs and isomiRs (variant miRNA sequences that all appear to derive from the same gene but vary in sequence due to post-transcriptional processing). Importantly, through the recent publication of the rainbow trout genome (Berthelot et al., 2014), mRNA 3'UTR information has become available, allowing for the first time the genome-wide prediction of miRNA-target RNA relationships in this species. We here report the creation of the microtrout database, a comprehensive resource for rainbow trout miRNA and annotated 3'UTRs. The comprehensive database was used to implement an algorithm to predict genome-wide rainbow trout-specific miRNA-mRNA target relationships, generating an improved predictive framework over previously published approaches. This work will serve as a useful framework and sequence resource to experimentally address the role of miRNAs in several research areas using the rainbow trout model, examples of which are discussed.[1]


  1. MicroTrout: A comprehensive, genome-wide miRNA target prediction framework for rainbow trout, Oncorhynchus mykiss.,
    Mennigen, Jan A., and Zhang Dapeng
    , Comp Biochem Physiol Part D Genomics Proteomics, 2016 Jul 28, Volume 20, p.19-26, (2016)