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Related Experiment Video

Updated: Jun 11, 2025

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

Pervasive mislocalization of pathogenic coding variants underlying human disorders.

Jessica Lacoste¹, Marzieh Haghighi², Shahan Haider¹

¹Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.

|October 1, 2024

Summary

This summary is machine-generated.

A new high-throughput imaging platform reveals that protein mislocalization is a common consequence of disease-causing genetic variants, impacting disease severity and offering insights into variants of uncertain significance.

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Area of Science:

Genomics
Molecular Biology
Biochemistry

Background:

Thousands of disease-causing missense variants are identified through widespread sequencing.
Assessing the functional impact of each variant is a significant bottleneck in genetic research.

Purpose of the Study:

To establish a high-throughput imaging platform to assay the impact of coding variation on protein localization.
To evaluate a large number of missense variants across numerous genes and phenotypes.

Main Methods:

Development of a high-throughput imaging platform.
Assay of 3,448 missense variants from over 1,000 genes.
Analysis of protein localization patterns.

Main Results:

Mislocalization is a common consequence of coding variation, affecting approximately one-sixth of pathogenic missense variants.
Mislocalization impacts all cellular compartments and both recessive and dominant disorders.
Protein mislocalization is primarily driven by altered protein stability and membrane insertion.

Conclusions:

Protein mislocalization is a frequent outcome of pathogenic missense variants.
Mislocalization patterns provide insights into pleiotropy, disease severity, and variants of uncertain significance.
The developed platform and data offer a valuable resource for understanding coding variation in human diseases.