Computational prediction of candidate miRNAs and their targets from Medicago truncatula non-protein-coding transcripts.
Identification and analysis of miRNAs enhances our understanding of the important roles that small RNAs play in complex regulatory networks. It is often difficult to perform large-scale validation of miRNA expression that is predicted from genomic regions. Expressed transcripts provide an alternative resource to facilitate identification of miRNAs and their targets. We developed a computational pipeline to scan for miRNA genes from polyadenylated transcripts that were associated with limited protein coding potentials, corresponding to the intergenic regions of Medicago truncatula genomic sequences. Each predicted miRNA was required to have a near perfect match with target genes. We also searched for miRNA conservation in other plant species, clustered highly similar miRNAs, and provided a functional classification of target genes.
Wen
Jiayu
J
Australian Research Council (ARC) Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Research School of Biological Sciences, Australian National University, Canberra, Australia.
Frickey
Tancred
T
Weiller
Georg F
GF
D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D018506:Gene Expression Regulation, Plant; D046913:Medicago truncatula / Q000235:genetics*; D035683:MicroRNAs / Q000235:genetics*; D018749:RNA, Plant / Q000235:genetics*; D022661:RNA, Untranslated / Q000235:genetics
D035683:MicroRNAs; D018749:RNA, Plant; D022661:RNA, Untranslated