一个实用的框架,用于预测在外基因组测序中的单核酸变体拼接
Yasuhiro Utsuno1, Kohei Hamanaka1, Masamune Sakamoto1,2
1Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Japan.
NAR genomics and bioinformatics
|December 22, 2025
概括
我们创建了一个新的框架,以轻松评估孟德尔疾病的致病拼接单核酸变体 (SNV). 这个工具可以更好地检测出这些变异在外基因组测序数据中的变异.
科学领域:
- 遗传学 遗传学 是一个
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 拼接变体是孟德尔疾病的关键贡献者.
- 预测拼接变异的致病性仍然是遗传诊断中的一个重大挑战.
研究的目的:
- 开发一个简化的框架来评估致病拼接单核酸变体 (SNVs).
- 为了与2023年ACMG/AMP指南和ClinGen对变种分类的建议保持一致.
主要方法:
- 开发了一个评分系统,为开放阅读框架地区的SNV分配优先分数 (-10到14分).
- 使用来自人类基因突变数据库的致病拼接SNV和来自gnomAD的常见SNV验证了框架.
- 与框架对SpliceAI的歧视力进行了比较.
主要成果:
- 与单独使用SpliceAI相比,该框架显示出更高的歧视性 (AUC 0.991 与 0.983 相比,P = 2.11 × 10−23).
- 在1257名尚未确诊的患者中,确定了已知基因 (COL2A1,PDHA1,MECP2,JAKMIP1) 中的致病拼接变体.
- 建议潜在的候选致病基因 (UBN1,NFE2L1).
结论:
- 开发的框架简化了拼接SNVs的致病性评估.
- 这种方法通过外体序列测序增强了拼接变异的检测,有助于诊断遗传疾病.
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