@article{Warwick Vesztrocy01102025,
author = {Warwick Vesztrocy, Alex and Glover, Natasha and Thomas, Paul D. and Dessimoz, Christophe and Julca, Irene}, 
title = {Unveiling the functional fate of duplicated genes through expression profiling and structural analysis},
volume = {35}, 
number = {10}, 
pages = {2273-2284}, 
year = {2025}, 
doi = {10.1101/gr.280166.124}, 
abstract ={Gene duplication is a major evolutionary source of functional innovation. Following duplication events, gene copies (paralogs) may undergo various fates, including retention with functional modifications (such as subfunctionalization or neofunctionalization) or loss. When paralogs are retained, this results in complex orthology relationships, including one-to-many or many-to-many. In such cases, determining which one-to-one pair is more likely to have conserved functions can be challenging. It has been proposed that, following gene duplication, the copy that diverges more slowly in sequence is more likely to maintain the ancestral function—referred to here as “the least diverged ortholog (LDO) conjecture.” This study explores this conjecture, using a novel method to identify asymmetric evolution of paralogs and applying it to all gene families across the Tree of Life in the PANTHER database. Structural data for over 1 million proteins and expression data for 16 animals and 20 plants are used to investigate functional divergence following duplication. This analysis, the most comprehensive to date, reveals that, whereas the majority of paralogs display similar rates of sequence evolution, significant differences in branch lengths following gene duplication can be correlated with functional divergence. Overall, the results support the least diverged ortholog conjecture, suggesting that the least diverged ortholog tends to retain the ancestral function, whereas the most diverged ortholog (MDO) may acquire a new, potentially specialized role.}, 
URL = {http://genome.cshlp.org/content/35/10/2273.abstract}, 
eprint = {http://genome.cshlp.org/content/35/10/2273.full.pdf+html}, 
journal = {Genome Research} 
}