ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo K-Tuple Nucleotide Compositional Features.

Prabina Kumar Meher,Om Parkash Dhankher,Tanmaya Kumar Sahu,Upendra Kumar,Anuj Kumar,Shbana Begam,Atmakuri Ramakrishna Rao,Krishna Pal Singh,Ajit Gupta

doi:10.3390/ijms23031612

Abstract

MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set were 62.33, 64.85, 69.21 percentages, respectively, for the three datasets. The SVM also achieved higher accuracy than other learning methods such as random forest, extreme gradient boosting, and adaptive boosting. To implement our method with ease, an online prediction server “ASRmiRNA” has been developed. The proposed approach is believed to supplement the existing effort for identification of abiotic stress-responsive miRNAs and Pre-miRNAs.

Highlights

MicroRNAs are 20–24 nucleotides long, small non-coding RNA molecules, widely distributed in the plant kingdom [1,2]
The miRNAs act as a post-transcriptional regulators of gene expression in a sequence-specific manner to respond to different abiotic stresses, where the gene expression is regulated via translational inhibition [50]
It cannot be guaranteed that the miRNA sequence is solely responsible for the abiotic stress response, at the same time it cannot be ignored that the whole process of translational repression occurs with the specific base pairing of miRNA with the target region where the order of nucleotides in the miRNA plays an important role

Summary

Introduction

MicroRNAs (miRNAs) are 20–24 nucleotides long, small non-coding RNA molecules, widely distributed in the plant kingdom [1,2]. By regulating the expression of stressresponsive genes, miRNAs play a vital role in plant response to different abiotic stresses and are regarded as the bio-regulators of plant stress response [3,4,5,6]. The miR169 was inhibited by drought stress [47] but was found to be induced by salinity treatment in Arabidopsis [48], which demonstrates that abiotic stresses induce the expression of miRNAs in a stress-dependent manner. As far as plant response to abiotic stresses in miRNAs-dependent manner is concerned, the expression of miR397 was significantly induced but the expression of miR398 was significantly inhibited in Arabidopsis under salinity stress [8]. All the above cited studies suggest that miRNAs play a significant role in plant response to different abiotic stresses

Methods

Results

Conclusion