Department of Biochemistry, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Department of Pediatrics, Hamamatsu University School of Medicine, Hamamatsu, Japan.
J Hum Genet. 2023 Jul;68(7):499-505. doi: 10.1038/s10038-023-01143-3. Epub 2023 Mar 10.
The recent introduction of genome sequencing in genetic analysis has led to the identification of pathogenic variants located in deep introns. Recently, several new tools have emerged to predict the impact of variants on splicing. Here, we present a Japanese boy of Joubert syndrome with biallelic TCTN2 variants. Exome sequencing identified only a heterozygous maternal nonsense TCTN2 variant (NM_024809.5:c.916C >T, p.(Gln306Ter)). Subsequent genome sequencing identified a deep intronic variant (c.1033+423G>A) inherited from his father. The machine learning algorithms SpliceAI, Squirls, and Pangolin were unable to predict alterations in splicing by the c.1033+423G>A variant. SpliceRover, a tool for splice site prediction using FASTA sequence, was able to detect a cryptic exon which was 85-bp away from the variant and within the inverted Alu sequence while SpliceRover scores for these splice sites showed slight increase (donor) or decrease (acceptor) between the reference and mutant sequences. RNA sequencing and RT-PCR using urinary cells confirmed inclusion of the cryptic exon. The patient showed major symptoms of TCTN2-related disorders such as developmental delay, dysmorphic facial features and polydactyly. He also showed uncommon features such as retinal dystrophy, exotropia, abnormal pattern of respiration, and periventricular heterotopia, confirming these as one of features of TCTN2-related disorders. Our study highlights usefulness of genome sequencing and RNA sequencing using urinary cells for molecular diagnosis of genetic disorders and suggests that database of cryptic splice sites predicted in introns by SpliceRover using the reference sequences can be helpful in extracting candidate variants from large numbers of intronic variants in genome sequencing.
最近在遗传分析中引入基因组测序,导致鉴定出位于深内含子中的致病性变异。最近,出现了几种新的工具来预测变异对剪接的影响。在这里,我们介绍了一位具有双等位基因 TCTN2 变异的日本 Joubert 综合征男孩。外显子组测序仅发现一个杂合的母源性无义 TCTN2 变异(NM_024809.5:c.916C>T,p.(Gln306Ter))。随后的基因组测序发现了一个从他父亲那里遗传来的深内含子变异(c.1033+423G>A)。机器学习算法 SpliceAI、Squirls 和 Pangolin 无法预测 c.1033+423G>A 变异对剪接的改变。SpliceRover 是一种使用 FASTA 序列预测剪接位点的工具,能够检测到一个距变异 85bp 且位于反转 Alu 序列内的隐匿外显子,而这些剪接位点的 SpliceRover 评分显示在参考序列和突变序列之间略有增加(供体)或减少(受体)。使用尿液细胞进行 RNA 测序和 RT-PCR 证实了隐匿外显子的包含。该患者表现出与 TCTN2 相关疾病的主要症状,如发育迟缓、畸形面部特征和多指(趾)畸形。他还表现出不常见的特征,如视网膜营养不良、外斜视、呼吸模式异常和脑室周围异位,这证实了这些是 TCTN2 相关疾病的特征之一。我们的研究强调了使用基因组测序和尿液细胞进行 RNA 测序进行遗传疾病分子诊断的有用性,并表明使用参考序列通过 SpliceRover 预测内含子中隐匿剪接位点的数据库可以帮助从基因组测序中的大量内含子变异中提取候选变异。