Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants

Abstract Background: Branch points (BPs) map within short motifs upstream of acceptor splice sites (3’ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3’ss. Results: We used a large set of constitutive and alternative human 3’ss collected from Ensembl (n = 264,787 3’ss) and from in-house RNAseq experiments (n = 51,986 3’ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3’ss (99.48 % and 65.84 % accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17 %. Conclusions: Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3’ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area. Keywords: Branch Point, Prediction, RNA, Benchmark, HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR, RNABPS, Variants