Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants

Abstract

Assessing the impact of variants of unknown significance (VUS) on splicing is a key issue in molecular diagnosis. This impact can be predicted by in silico tools, but proper evaluation and user guidelines are lacking. To fill this gap, we embarked upon the largest BRCA1 and BRCA2 splice study to date by testing 272 VUSs (327 analyses) within the BRCA splice network of Unicancer. All these VUSs were analyzed by using six tools (splice site prediction by neural network, splice site finder (SSF), MaxEntScan (MES), ESE finder, relative enhancer and silencer classification by unanimous enrichment, and human splicing finder) and the predictions obtained were compared with transcript analysis results. Combining MES and SSF gave 96% sensitivity and 83% specificity for VUSs occurring in the vicinity of consensus splice sites, that is, the surrounding 11 and 14 bases for the 5' and 3' sites, respectively. This study was also an opportunity to define guidelines for transcript analysis along with a tentative classification of splice variants. The guidelines drawn from this large series should be useful for the whole community, particularly in the context of growing sequencing capacities that require robust pipelines for variant interpretation.