The Experimentally Obtained Functional Impact Assessments of 5' Splice Site GT'GC Variants Differ Markedly from Those Predicted.

ABSTRACT:

Introduction

5' splice site GT>GC or +2T>C variants have been frequently reported to cause human genetic disease and are routinely scored as pathogenic splicing mutations. However, we have recently demonstrated that such variants in human disease genes may not invariably be pathogenic. Moreover, we found that no splicing prediction tools appear to be capable of reliably distinguishing those +2T>C variants that generate wild-type transcripts from those that do not.

Methodology

Herein, we evaluated the performance of a novel deep learning-based tool, SpliceAI, in the context of three datasets of +2T>C variants, all of which had been characterized functionally in terms of their impact on pre-mRNA splicing. The first two datasets refer to our recently described "in vivo"

SUBMITTER: Chen JM 

PROVIDER: S-EPMC7324893 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature