Hasselt University, Interuniversity institute for biostatistics and statistical bioinformatics, Hasselt, 3500, Belgium.
Durham University, Wolfson Research Institute for Health and Wellbeing, Durham, United Kingdom.
Sci Rep. 2018 May 29;8(1):8331. doi: 10.1038/s41598-018-26695-9.
Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events have been linked to genetic disorders. Therefore, understanding mechanisms of alternative splicing regulation and differences in splicing events between diseased and healthy tissues is crucial in advancing personalized medicine and drug developments. We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events using Human Transcriptome Arrays (HTA). For each exon, a splicing score is calculated based on two scores, an exon score and an array score. The junction information is used to rank the identified exons from strongly confident to less confident candidates for alternative splicing. The design of junctions was also discussed to highlight the complexity of exon-exon and exon-junction interactions. Based on a list of Rt-PCR validated probe sets, REIDS outperforms AltAnalyze and iGems in the % recall rate.
可变剪接是一种常见的现象,即一个基因可以产生多种转录本异构体。该过程受到严格的调控,涉及多种蛋白质和调控复合物。不幸的是,异常剪接事件与遗传疾病有关。因此,了解可变剪接调控的机制以及疾病组织和健康组织之间剪接事件的差异,对于推进个性化医学和药物开发至关重要。我们提出了一种线性混合模型,即用于识别差异剪接的随机效应模型(Random Effects for the Identification of Differential Splicing,REIDS),用于使用人类转录组芯片(Human Transcriptome Arrays,HTA)识别可变剪接事件。对于每个外显子,根据两个分数(外显子分数和芯片分数)计算剪接分数。使用连接信息对鉴定的外显子进行排序,从强置信度到弱置信度的候选可变剪接。还讨论了连接的设计,以突出外显子-外显子和外显子-连接相互作用的复杂性。基于一系列经 RT-PCR 验证的探针集,REIDS 在 %召回率方面优于 AltAnalyze 和 iGems。