生物
遗传学
计算生物学
编码(社会科学)
数学
统计
作者
Jessica Lacoste,Marzieh Haghighi,Shahan Haider,C. Reno,Zhen‐Yuan Lin,Dmitri Segal,Wesley Wei Qian,Xueting Xiong,Tanisha Teelucksingh,Esteban A. Miglietta,Hamdah Shafqat Abbasi,Pearl V. Ryder,Rebecca A. Senft,Beth A. Cimini,Ryan R. Murray,Chantal Nyirakanani,Tong Hao,Gregory G McClain,Frederick P. Roth,Michael A. Calderwood
出处
期刊:Cell
[Cell Press]
日期:2024-09-30
卷期号:187 (23): 6725-6741.e13
被引量:10
标识
DOI:10.1016/j.cell.2024.09.003
摘要
Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease causing. This creates a new bottleneck: determining the functional impact of each variant-typically a painstaking, customized process undertaken one or a few genes and variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,448 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of uncertain significance. Our publicly available resource extends our understanding of coding variation in human diseases.
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