MicroRNAs (miRNAs) are known to play critical roles in plant development and stress-response regulation, and they frequently display multi-targeting characteristics. The control of defined rice phenotypes occurs through multiple genes; however, evidence demonstrating the relationship between agronomic traits and miRNA expression profiles is lacking. In this study, we investigated eight yield-related traits in 187 local rice cultivars and profiled the expression levels of 193 miRNAs in these cultivars using microarray analyses. By integrating the miRBase database, the rice annotation project database, and the miRanda and psRNATarget web servers, we constructed a database (RiceATM) that can be employed to investigate the association between rice agronomic traits and miRNA expression. The functions of this platform include phenotype selection, sample grouping, microarray data pretreatment, statistical analysis and target gene predictions. To demonstrate the utility of RiceATM, we used the database to identify four miRNAs associated with the heading date and validated their expression trends in the cultivars with early or late heading date by real-time PCR. RiceATM is a useful tool for researchers seeking to characterize the role of certain miRNAs for a specific phenotype and discover potential biomarkers for breeding or functional studies.Database URL: http://syslab3.nchu.edu.tw/rice/. © The Author(s) 2016. Published by Oxford University Press.
