Establishment of a prediction model for the miRNA-based heading date characteristics of rice in the booting stage

Rice (Oryza sativa L.) is one of the most important food crops in the world. In Taiwan, due to the warm climate, there are two harvests annually. However, the yield and quality of rice can vary between each crop season in any given year. Previous reports have shown that microRNAs (miRNAs) play a crucial role in many developmental and physiological processes in plants. In this study, the heading date characteristics of 167 rice cultivars from the second crop season were recorded, and 27 rice cultivars were selected for preliminary microarray analysis. A total of 14 miRNAs from different heading date characteristics in 21 cultivars were selected based on significant differences in their expression profiles. Using a correlation analysis between the heading date and selected miRNA expression obtained from real-time polymerase chain reaction (PCR) assays, we developed a heading date prediction model. The model includes nine miRNA genes with corresponding R2 values of 0.8. To confirm the model, a real-time PCR analysis was performed on an additional 27 rice cultivars and we found the model predicted the heading date with accuracy. Therefore, the developed prediction may be useful in further studies aimed at confirming the reliability of the use of miRNA in molecular breeding and to increase the selection efficiency of rice cultivars and breeding.