Kids Neuroscience Centre, Kids Research, Children's Hospital at Westmead, Sydney, New South Wales, Australia.
Discipline of Child and Adolescent Health, Faculty of Health and Medicine, University of Sydney, Sydney, New South Wales, Australia.
Nat Genet. 2023 Feb;55(2):324-332. doi: 10.1038/s41588-022-01293-8. Epub 2023 Feb 6.
Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification.
即使是那些几乎可以肯定会改变 mRNA 剪接的必需剪接位点变异，目前也没有可靠的方法可以预测外显子跳跃、隐性激活或多种事件的结果，这极大地增加了致病性临床解释的复杂性。引人注目的是，对 335663 个参考 RNA 测序 (RNA-seq) 样本中的 4 种最常见的未注释剪接事件进行排名（300K-RNA 前 4 名），可以以 92%的灵敏度预测与变体相关的错误剪接的性质。对于 140 个接受 RNA 检测的临床病例，300K-RNA 前 4 名事件正确识别了 96%的外显子跳跃事件和 86%的隐性剪接位点，其灵敏度和阳性预测值均高于 SpliceAI。值得注意的是，RNA 重新分析表明，在开发这种经验预测方法之前，我们已经错过了几个经过测试的临床病例的 300K-RNA 前 4 名事件。简单来说，在 RNA-seq 数据中发生在剪接位点周围的错误剪接事件最有可能被剪接位点变异激活。SpliceVault 门户网站允许用户轻松访问 300K-RNA，以进行明智的剪接位点变异解释和分类。
