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基于图像的聚合表型化揭示了多维的,疾病特异性的变体效应

Sriram Pendyala^1,2, Katie Partington^1,3, Nicholas Bradley¹

¹Department of Genome Sciences, University of Washington, Seattle, WA, USA.

bioRxiv : the preprint server for biology

|July 9, 2025

概括

变体在位测序 (VIS-seq) 捕捉了复杂的遗传变体对细胞表型的影响. 这种基于图像的方法准确地预测了变异性病原性,并揭示了遗传变化如何影响细胞结构和功能.

科学领域:

基因组学就是基因组学.
细胞生物学细胞生物学
生物信息学是一种生物信息学.

背景情况:

遗传变异通常具有复杂的表型效应,难以测量.
当前的预测模型难以捕捉变量影响的全部范围.
了解变体的功能对于诊断遗传疾病至关重要.

研究的目的:

开发一种用于测量分子和细胞表型上的变异效应的新方法.
将这种方法应用于LMNA和PTEN基因中的大量遗传变异.
建立一个框架来解决遗传变异功能的复杂性.

主要方法:

开发的变体 in situ 测序 (VIS-seq),一个聚合的,基于图像的测试.
应用VIS-seq对大约3000个LMNA和PTEN变异在不同的细胞类型.
生成高维形态配置文件以捕捉变异驱动的变化.

主要成果:

VIS-seq确定了蛋白质丰富度,局部化,活性和细胞结构的变异特异性变化.
发现了改变核形状的功能增益LMNA变体和与自闭症相关的PTEN变体与错位化.
形态特征在预测变体致病性和区分与疾病相关的变体方面实现了近乎完美的准确性.

结论:

大多数遗传变异会影响多维连续的表型,而不是通过单个测试来捕获.
VIS-seq提供了一个可扩展的框架,用于将遗传变异与细胞表型联系起来.
这种方法揭示了从分子到形态层次的变异效应的级联,有助于理解遗传疾病的复杂性.

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