Bons, E. | Search bioRxiv

bioRxiv2025

Parallel evolution of full-length genomes in a long-term evolution experiment with phage ΦX174

The study of evolution in organisms with high mutation rates requires detailed data on the genomic composition of the population. Here we report on an innovative use of high-throughput sequencing technology combined with rapid experimental evolution that allowed us to follow the genetic diversification of four independent bacteriophage populations that we evolved without actively imposing any selection pressures (in addition to those inherent in the bacterial cell environment) for 412 generations in unprecedented detail. Tracing over 80000 bacteriophage genomes, representing 884 distinct genotypes, we find that the patterns of viral diversification result in largely non-congruent genotype distributions, but also document multiple instances of parallel evolution. Unlike previous observations of parallelism in viral evolution, we do not just see the parallel evolution of mutations at single sites, but on the level of full-length genomes. Computer simulations that recapitulate our experiments in great detail show that this degree of parallelism is inconsistent with neutral evolution. We further show that the observed extent of parallel evolution biases phylodynamic analysis of migration rates, and wrongly estimates significant migration between the independent evolution lines. Our approach is applicable to many other viruses and paves the way to advanced population genetic investigations that aim to shed light on phenomena that relate to genetic linkage across the genome.

evolutionary biology↗

bioRxiv2017

Estimating the Mutational Fitness Effects Distribution during early HIV infection

The evolution of HIV during acute infection is often considered a neutral process. Recent analysis of sequencing data from this stage of infection, however, showed high levels of shared mutations between independent viral populations. This suggests that selection might play a role in the early stages of HIV infection. We adapted an existing model for random evolution during acute HIV-infection to include selection. Simulations of this model were used to fit a global mutational fitness effects distribution (MFED) to sequencing data of the env gene of individuals with acute HIV infection. Measures of sharing between viral populations were used as summary statistics to compare the data to the simulations. We confirm that evolution during acute infection is significantly different from neutral. The distribution of mutational fitness effects is best fit by distribution with a low, but significant fraction of beneficial mutations and a high fraction of deleterious mutations. While most mutations are neutral or deleterious in this model, about 5% of mutations is beneficial. These beneficial mutations will, on average, result in a small but significant increase in fitness. When assuming no epistasis, this indicates that at the moment of transmission HIV is near, but not on the fitness peak for early infection.

evolutionary biology↗