2026/03/30 by Thibault Latrille, Théo Gaboriau, Nicolas Salamin · 2 voices
Earth and Planetary Sciences · Biochemistry, Genetics and Molecular Biology · #Evolution and Paleontology Studies #Evolution and Genetic Dynamics #Genomics and Phylogenetic Studies
paper · pdf · doi:10.1093/evlett/qrag015
At the species level, the evolution of traits is driven by a combination of selective and neutral forces. To disentangle these processes, different scenarios of evolution are modeled and compared. For quantitative traits under selection, the species is usually considered to track a trait optimum, and such an optimum can change along the branches of the species tree. On the other hand, neutral evolution is modeled with a trait changing randomly around the ancestral trait value along the different branches of the species tree. Regardless of the intricacy of modeling trait changes, the species tree is assumed to be known and obtained independently of the trait data analysed. Branch lengths are usually assumed to be in units proportional to time, and the tree is represented by a chronogram. The rationale is that time correlates with trait changes because of its direct connection with the number of generations that have occurred. However, since the generation time of species can also vary along the phylogenetic tree, we argue that their use introduces biases. In contrast, if the phylogenetic tree is represented by a phylogram with branch lengths in units of sequence divergence, this will account for the effect of changing generation time. In this study, we show using simulations that, for a trait evolving neutrally, the fit of a random evolution model has more support on a phylogram than on a chronogram. However, comparing models and testing different scenarios of selection using a phylogram leads to incorrect predictions. Given these results, we argue that we should use phylograms instead of chronograms when claiming that a trait is evolving under drift. Nevertheless, we support the generally accepted use of chronograms to model selection acting on a quantitative trait.