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Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Authors: Dandage RPapkov MGreco BMFishman DFriesen HWang KStyles EKraus OGrys BBoone CAndrews BParts LKuzmin E


Affiliations

1 Department of Biology, Concordia University, Montreal, Canada.
2 Centre for Applied Synthetic Biology, Centre for Structural and Functional Genomics, Concordia University, Montreal, Canada.
3 Department of Computer Science, University of Tartu, Tartu, Estonia.
4 The Donnelly Centre, University of Toronto, Toronto, Canada.
5 Department of Molecular Genetics, University of Toronto, Toronto, Canada.
6 Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.
7 Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK.
8 Department of Human Genetics, Rosalind & Morris Goodman Cancer Institute, McGill University, Montreal, Canada.

Description

Gene duplication is common across the tree of life, including yeast and humans, and contributes to genomic robustness. In this study, we examined changes in the subcellular localization and abundance of proteins in response to the deletion of their paralogs originating from the whole-genome duplication event, which is a largely unexplored mechanism of functional divergence. We performed a systematic single-cell imaging analysis of protein dynamics and screened subcellular redistribution of proteins, capturing their localization and abundance changes, providing insight into forces determining paralog retention. Paralogs showed dependency, whereby proteins required their paralog to maintain their native abundance or localization, more often than compensation. Network feature analysis suggested the importance of functional redundancy and rewiring of protein and genetic interactions underlying redistribution response of paralogs. Translation of non-canonical protein isoform emerged as a novel compensatory mechanism. This study provides new insights into paralog retention and evolutionary forces that shape genomes.


Links

PubMed: https://pubmed.ncbi.nlm.nih.gov/38045359/

DOI: 10.1101/2023.11.23.568466