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.

RNA 编辑对许多生物过程产生重要影响。虽然已经在人类身上发现了数以百万计的 RNA 编辑，但预计还会发现更多。在这项工作中，我们构建了卷积神经网络 (CNN) 模型来预测 Alu 区域和非 Alu 区域中的人类 RNA 编辑事件。使用由 CRISPR/Cas9 敲除ADAR1酶产生的验证数据集，Alu 和非 Alu 区域的验证准确度分别达到 99.5% 和 93.6%。我们将 CNN 模型移植到名为 EditPredict 的 Web 服务中。EditPredict 不仅适用于参考基因组序列，还可以考虑单核苷酸变异在个人基因组中。除了人类基因组，EditPredict 还处理其他模式生物，包括大黄蜂、果蝇、小鼠和鱿鱼基因组。EditPredict 可以单独使用来预测新的 RNA 编辑，它可以用来帮助过滤从 RNA-Seq 数据中检测到的候选 RNA 编辑。