Circular RNA (circRNAs) may mediate mRNA expression as miRNA sponge, control the process of protein translation, or produce protein directly via translation. Since the community has pay more attention on circRNAs, a lot of circRNA databases has been developed for plant (Chu et al., 2017; Ye et al., 2017; Zhang et al., 2017). However, a comprehensive collection of circRNAs in crop is still lacking. Following our previous work (Ye et al., 2017), we applied a big-data approach to take full advantage of large-scale sequencing data, and developed a rich circRNA resource: CropCircDB (http://deepbiology.cn/crop/) for maize and rice, later extending to incorporate more crop species.
In summary, we systematically investigated 244 and 288 RNA-Seq samples for maize and rice, respecitvely, including 111 stress-related maize samples (drought and salt) and 148 stress-related rice samples (drought, salt and cold), and found 38,785 circRNAs in maize, and 63,048 circRNAs in rice. To improve the prediction accuracy, we applied a straightforward metric: detection score to screen and rank the circular RNA. In regards of the interaction between miRNA and circular RNAs, we utilized psRNAtarget to evaluate the statistical significance. Together, this database will host all predicted and validated crop circular RNAs, and provide valuable and comprehensive information for studying this newly emerging non-coding RNA.