Intragenomic matching reveals a huge potential for miRNA-mediated regulation in plants.

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microRNAs (miRNAs) are important post-transcriptional regulators, but the extent of this regulation is uncertain, both with regard to the number of miRNA genes and their targets. Using an algorithm based on intragenomic matching of potential miRNAs and their targets coupled with support vector machine classification of miRNA precursors, we explore the potential for regulation by miRNAs in three plant genomes: Arabidopsis thaliana, Populus trichocarpa, and Oryza sativa. We find that the intragenomic matching in conjunction with a supervised learning approach contains enough information to allow reliable computational prediction of miRNA candidates without requiring conservation across species. Using this method, we identify approximately 1,200, approximately 2,500, and approximately 2,100 miRNA candidate genes capable of extensive base-pairing to potential target mRNAs in A. thaliana, P. trichocarpa, and O. sativa, respectively. This is more than five times the number of currently annotated miRNAs in the plants. Many of these candidates are derived from repeat regions, yet they seem to contain the features necessary for correct processing by the miRNA machinery. Conservation analysis indicates that only a few of the candidates are conserved between the species. We conclude that there is a large potential for miRNA-mediated regulatory interactions encoded in the genomes of the investigated plants. We hypothesize that some of these interactions may be realized under special environmental conditions, while others can readily be recruited when organisms diverge and adapt to new niches.
Original languageEnglish
JournalPLoS Computational Biology
Issue number11
Pages (from-to)e238
Publication statusPublished - 2007

Bibliographical note

Keywords: Chromosome Mapping; Gene Expression Regulation, Plant; Genome, Plant; MicroRNAs; Phenotype; Plant Proteins; Plants; Sequence Analysis, RNA; Sequence Homology, Nucleic Acid; Species Specificity

ID: 2736966