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Banse, P.

Publications and source records attributed to Banse, P..

2 recordsLinked to original sources

Aevol-9: A simulation platform to decipher the evolution of genome architecture

Aevol is a forward-in-time simulator of genome architecture. It simulates a population of individuals, each with an explicit genome whose sequence and architecture can be modified by various mutational operators, including substitutions, indels, and large-scale chromosomal rearrangements. This enables performing in silico experiments to decipher the effects of evolutionary conditions (e.g. population size, selection strength, mutation rates, and biases) on genome organization.

evolutionary biology↗

Structural mutations set an equilibrium non-coding genome fraction

Non-coding genome size evolution is poorly understood. While some fraction of non-coding DNA has arguably a regulatory function, a large part does not seem to have a detectable impact on any phenotypic trait. The abundance of non-functional DNA in genomes, observed across the Tree of Life, challenges a purely adaptationist explanation. Several non-adaptive theories have been proposed to explain its presence and identify its determinants, emphasizing either the mutational processes or the mutational hazard entailed by non-coding and non-functional DNA. However, those theories have not yet been integrated into a single framework, and the exact nature of the mutational hazard is not yet fully understood. In this work, we propose a simple mathematical model of genome size evolution. The model shows how the non-coding fraction of the genome is shaped by two factors: unavoidable biases in the neutrality of the different mutation types (adding base pairs is more likely to be neutral than removing some), and the robustness selection imposed by the mere existence of structural mutations (larger genomes are more prone to double-strand breaks that can initiate structural mutations, imposing a second-order selection on robustness). Together, these two factors ensure the existence of an equilibrium non-coding fraction. We show that this equilibrium depends solely on mutation biases and the product of population size and mutation rate.

evolutionary biology↗