EditPredict: Prediction of RNA editable sites with convolutional neural network.

Journal: Genomics
PMID: 34562567

Abstract

RNA editing exerts critical impacts on numerous biological processes. While millions of RNA editings have been identified in humans, much more are expected to be discovered. In this work, we constructed Convolutional Neural Network (CNN) models to predict human RNA editing events in both Alu regions and non-Alu regions. With a validation dataset resulting from CRISPR/Cas9 knockout of the ADAR1 enzyme, the validation accuracies reached 99.5% and 93.6% for Alu and non-Alu regions, respectively. We ported our CNN models in a web service named EditPredict. EditPredict not only works on reference genome sequences but can also take into consideration single nucleotide variants in personal genomes. In addition to the human genome, EditPredict tackles other model organisms including bumblebee, fruitfly, mouse, and squid genomes. EditPredict can be used stand-alone to predict novel RNA editing and it can be used to assist in filtering for candidate RNA editing detected from RNA-Seq data.

Authors

  • Jiandong Wang
    Department of Computer Science and Engineering,University of South Carolina, Columbia, 29208, SC, USA.
  • Scott Ness
    Comprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87109, USA.
  • Roger Brown
    Comprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87109, USA.
  • Hui Yu
    Engineering Technology Research Center of Shanxi Province for Opto-Electric Information and Instrument, Taiyuan 030051, China. 13934603474@nuc.edu.cn.
  • Olufunmilola Oyebamiji
    Comprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, NM 87109, USA.
  • Limin Jiang
    School of Computer Science and Technology, Tianjin University, Tianjin 300350, China; School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China.
  • Quanhu Sheng
    Department of Biostatistics, Vanderbilt University Medical Center, TN 37232, USA.
  • David C Samuels
    Vanderbilt University School of Medicine,Vanderbilt University, Nashville, 37232, TN, USA.
  • Ying-Yong Zhao
    Key Laboratory of Resource Biology and Biotechnology in Western China, School of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China.
  • Jijun Tang
    School of Computer Science and Engineering, Tianjin University, Tianjin, 300072, China. jtang@cse.sc.edu.
  • Yan Guo
    State Key Laboratory of Pathogen and Biosecurity, Beijing 100071, China.

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