Abstract
Whole-genome duplication (WGD) events are common across various organisms; however, the retention and evolution of WGD paralogs is not fully understood. Quantitative measure of protein redistribution in response to the deletion of their WGD paralog provides insight into sources of gene retention. Here, we describe PARPAL (PARalog Protein Redistribution using Abundance and Localization in Yeast), a web database that houses results of high-content screening and deep learning neural network analysis of the redistribution of 164 proteins reflecting how their subcellular localization and protein abundance change in response to their paralog deletion in the budding yeast, Saccharomyces cerevisiae. We interrogated a total of 82 paralog pairs in 2 genetic backgrounds for a total of ∼3,500 micrographs of ∼460,000 cells. For example, Skn7-Hms2 exhibited dependent redistribution, and Cue1-Cue4 showed compensatory redistribution response. PARPAL also links to other studies on trigenic interactions, protein-protein interactions and protein abundance. PARPAL is available at https://parpal.c3g-app.sd4h.ca and is a valuable resource for the yeast community interested in understanding the retention and evolution of paralogs and can help researchers to investigate protein dynamics of paralogs in other organisms.