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使用HMMSTR和向长读序列的疾病相关联联重复的增强检测和基因定型

Kinsey Van Deynze¹, Camille Mumm^1,2, Connor J Maltby³

¹Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Nucleic acids research

|December 16, 2024

概括

这项研究引入了一种新的纳米孔测序方法和HMMSTR软件,用于准确分析与神经退行性疾病相关的并联重复扩张. 这些工具可以改善遗传诊断和复杂神经疾病的研究.

科学领域:

基因组学就是基因组学.
神经遗传学神经遗传学
生物信息学是一种生物信息学.

背景情况:

双重重复序列构成了人体基因组的8%左右.
这些重复与50多种神经退行性疾病有关.
目前用于表征重复扩张的方法资源密集,缺乏高分辨率的基因型调用.

研究的目的:

开发一种高分辨率,具有成本效益的基因型测定方法.
介绍HMMSTR,一个新的基于序列的复制号呼叫器,用于并列重复.
为了能够准确地描述与疾病相关的重复位置.

主要方法:

开发一个多重化,向的纳米孔测序面板.
实现HMMSTR,一个基于序列的并联重复复制号呼叫器.
将面板和HMMSTR应用于来自患者的样本.

主要成果:

在精度方面,HMMSTR的性能优于现有的基于信号和序列的调用器,特别是在异构的区域和低读取覆盖率的情况下.
目标小组在与疾病相关的地区实现了高平均覆盖率 (>150x).
在患者样本中成功描述已知和可疑的重复扩张.
在此前未关联的并列重复位点中识别出意想不到的扩展基.

结论:

开发的基因型鉴定方法是可扩展的,简单的,灵活的,准确的.
这种方法对神经退行性疾病的诊断应用具有重大潜力.
这些工具有助于调查疾病中重复扩张的同时发生.

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