Equipe GENDEV, Centre de Recherche en Neurosciences de Lyon, Inserm U1028, CNRS UMR5292, Université Lyon 1, Université St Etienne, Lyon, France.
Laboratoire de Biométrie et Biologie Évolutive, CNRS UMR5558, Université Lyon 1, Villeurbanne, and EPI ERABLE - Inria Grenoble, Villeurbanne, Rhône-Alpes, France.
PLoS One. 2020 Jul 6;15(7):e0235655. doi: 10.1371/journal.pone.0235655. eCollection 2020.
Biallelic variants in RNU4ATAC, a non-coding gene transcribed into the minor spliceosome component U4atac snRNA, are responsible for three rare recessive developmental diseases, namely Taybi-Linder/MOPD1, Roifman and Lowry-Wood syndromes. Next-generation sequencing of clinically heterogeneous cohorts (children with either a suspected genetic disorder or a congenital microcephaly) recently identified mutations in this gene, illustrating how profoundly these technologies are modifying genetic testing and assessment. As RNU4ATAC has a single non-coding exon, the bioinformatic prediction algorithms assessing the effect of sequence variants on splicing or protein function are irrelevant, which makes variant interpretation challenging to molecular diagnostic laboratories. In order to facilitate and improve clinical diagnostic assessment and genetic counseling, we present i) an update of the previously reported RNU4ATAC mutations and an analysis of the genetic variations affecting this gene using the Genome Aggregation Database (gnomAD) resource; ii) the pathogenicity prediction performances of scores computed based on an RNA structure prediction tool and of those produced by the Combined Annotation Dependent Depletion tool for the 285 RNU4ATAC variants identified in patients or in large-scale sequencing projects; iii) a method, based on a cellular assay, that allows to measure the effect of RNU4ATAC variants on splicing efficiency of a minor (U12-type) reporter intron. Lastly, the concordance of bioinformatic predictions and cellular assay results was investigated.
RNU4ATAC 中的双等位基因变异,该基因编码的非编码 RNA 转录成小核核糖核蛋白 U4atac snRNA,负责三种罕见的隐性发育疾病,即 Taybi-Linder/MOPD1、Roifman 和 Lowry-Wood 综合征。对临床异质队列(疑似遗传疾病或先天性小头畸形的儿童)进行下一代测序最近发现了该基因的突变,这说明了这些技术如何深刻地改变了遗传检测和评估。由于 RNU4ATAC 只有一个单一的非编码外显子,因此评估序列变异对剪接或蛋白功能影响的生物信息学预测算法是不相关的,这使得分子诊断实验室对变异的解释具有挑战性。为了促进和改善临床诊断评估和遗传咨询,我们提出了:i)对以前报道的 RNU4ATAC 突变进行更新,并使用基因组聚集数据库(gnomAD)资源分析影响该基因的遗传变异;ii)基于 RNA 结构预测工具计算的评分和综合注释依赖耗竭工具产生的评分对在患者或大规模测序项目中鉴定的 285 个 RNU4ATAC 变异的致病性预测性能;iii)一种基于细胞测定的方法,可测量 RNU4ATAC 变异对小(U12 型)报告内含子剪接效率的影响。最后,研究了生物信息学预测和细胞测定结果的一致性。