错义突变
表型
生物
瓶颈
遗传学
基因
计算生物学
编码区
计算机科学
嵌入式系统
作者
Jessica Lacoste,Marzieh Haghighi,Shahan Haider,Zhen‐Yuan Lin,Dmitri Segal,Carol Reno,Wesley Wei Qian,Xueting Xiong,Hamdah Shafqat Abbasi,Pearl V. Ryder,Rebecca A. Senft,Beth A. Cimini,Frederick P. Roth,Michael S. Calderwood,David E. Hill,Marc Vidal,S. Stephen Yi,Nidhi Sahni,Jian Peng,Anne‐Claude Gingras,Shantanu Singh,Anne E. Carpenter,Mikko Taipale
标识
DOI:10.1101/2023.09.05.556368
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 - largely a painstaking, customized process undertaken one or a few genes or variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,547 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 unknown significance. Our publicly available resource will likely accelerate the understanding of coding variation in human diseases.
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