PreTIS: A Tool to Predict Non-canonical 5’ UTR Translational Initiation Sites in Human and Mouse

Translation of mRNA sequences into proteins typically starts at an AUG triplet. In rare cases, translation may also start at alternative non–AUG codons located in the annotated 5’ UTR which leads to an increased regulatory complexity. Since ribosome profiling detects translational start sites at the nucleotide level, the properties of these start sites can then be used for the statistical evaluation of functional open reading frames. We developed a linear regression approach to predict in–frame and out–of–frame translational start sites within the 5’ UTR from mRNA sequence information together with their translation initiation confidence. Predicted start codons comprise AUG as well as near–cognate codons. The underlying datasets are based on published translational start sites for human HEK293 and mouse embryonic stem cells that were derived by the original authors from ribosome profiling data. The average prediction accuracy of true vs. false start sites for HEK293 cells was 80%. When applied to mouse mRNA sequences, the same model predicted translation initiation sites observed in mouse ES cells with an accuracy of 76%. Moreover, we illustrate the effect of in silico mutations in the flanking sequence context of a start site on the predicted initiation confidence. Our new webservice PreTIS visualizes alternative start sites and their respective ORFs and predicts their ability to initiate translation. Solely, the mRNA sequence is required as input. PreTIS is accessible at http://service.bioinformatik.uni-saarland.de/pretis.Author Summary: Ribosome profiling data and mRNA sequence features can be used to build reliable classification models with accuracies of about 80% for start codon and open reading frame prediction in human. All predicted start sites of one transcript are postulated to have the potential to initiate translation. They could, for example, be used in different tissues or in a specific cellular condition, such as stress response. Although there exist already several other approaches to predict translational initiation start sites, so far none of them considers all in– and out–of–frame AUG and near–cognate codons. The provided web service PreTIS considerably simplifies and assists the analysis of mRNA sequences in terms of prediction of possible translation start sites and their visualization.