title: Computational prediction of plant miRNA targets.
abstract: MicroRNAs (miRNAs) are a specific class of 21-nt small RNAs. They regulate the expression of specific target genes by various types of post-transcriptional regulation mechanisms, such as transcript cleavage and translation suppression. The biological function of an miRNA is therefore intimately associated with the function of their target genes. Target gene identification becomes an essential step towards understanding miRNA functions. In this protocol, we describe a computational procedure for plant miRNA target prediction. It involves two key steps: (1) search of transcript sequence databases for target sequences that have a near-perfect sequence complementarity to the miRNA sequence using the "scan_for_matches" program and (2) evaluation of the miRNA:target sequence pair for pairing complementarity using specific rules, such as positional dependent penalty score and minimum free energy ratio filter, to identify the most likely candidate targets.
authors.affiliation: Forest Biotechnology Group, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7247, USA.
authors.forename: Ying-Hsuan
authors.initials: YH
authors.lastname: Sun
authors.forename: Shanfa
authors.initials: S
authors.lastname: Lu
authors.forename: Rui
authors.initials: R
authors.lastname: Shi
authors.forename: Vincent L
authors.initials: VL
authors.lastname: Chiang
mesh_terms: D001483:Base Sequence; D019295:Computational Biology; D030561:Databases, Nucleic Acid; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism*; D010944:Plants / Q000235:genetics / Q000378:metabolism; D018749:RNA, Plant / Q000235:genetics* / Q000378:metabolism*; D012984:Software
chemical_list: D035683:MicroRNAs; D018749:RNA, Plant