Abstract

Motivation: MicroRNAs (miRNAs) are important regulatory molecules. A critical step in elucidating miRNA function is identifying potential miRNA targets. However, few reliable tools have been developed for identifying miRNA targets in plants. Results: Here, we developed a Smith–Waterman-like alignment tool in order to accurately predict miRNA targets. Dynamic programming was used to build a score matrix based on the complementarity of nucleotides in order to trace the optimal local alignments. Important parameters, such as maximum mismatches and maximum consecutive mismatches between miRNAs and their targets, were also used for filtering the optimal local alignments. Almost all of the parameters in this alignment tool can be adjusted by users. Compared to other target prediction tools, Target-align exhibits strong sensitivity and accuracy for identifying miRNA targets. More importantly, Target-align can identify multi-target sites as well potential for non-cleaved targets sites by change the default settings. Windows, web and command-line versions were developed to better serve different users.