PlantMirnaT

miRNA is known to regulate up to several hundreds coding genes, thus the integrated analysis of miRNA and mRNA expression data is an important problem. Unfortunately, the integrated analysis is challenging since it needs to consider expression data of two different types, miRNA and mRNA, and target relationship between miRNA and mRNA is not clear, especially when microarray data is used. Fortunately, due to the low sequencing cost, small RNA and RNA sequencing are routinely processed and we may be able to infer regulation relationships between miRNAs and mRNAs more accurately by using sequencing data. However, no method is developed specifically for sequencing data. Thus we developed PlantMirnaT, a new miRNA-mRNA integrated analysis system. To fully leverage the power of sequencing data, three major features are developed and implemented in PlantMirnaT. First, we implemented a plant-specific short read mapping tool based on recent discoveries on miRNA target relationship in plant. Second, we designed and implemented an algorithm considering miRNA targets in the full intragenic region, not just 3' UTR. Lastly but most importantly, our algorithm is designed to consider quantity of miRNA expression and its distribution on target mRNAs. The new algorithm was used to characterize rice under drought condition using our proprietary data. Our algorithm successfully discovered that two miRNAs, miRNA1425-5p, miRNA 398b, that are involved in suppression of glucose pathway in a naturally drought resistant rice, Vandana. The system can be downloaded at https://sites.google.com/site/biohealthinformaticslab/resources.[1]

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