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Reversions mask the contribution of adaptive evolution in microbiomes.

Paul A TorrilloTami D Lieberman
Published in: bioRxiv : the preprint server for biology (2023)
When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by d N /d S , the normalized ratio of nonsynonymous to synonymous mutations. This dependence on mutational distance, and thus time, has been proposed to arise from the inefficiency of purifying selection at removing weakly deleterious mutations. Here, we revisit this assumption in light of abundant genomes from gut microbiomes and show that a model of weak purifying selection that fits the data leads to problematic mutation accumulation. We propose an alternative model to explain the timescale dependence of d N /d S , in which constantly changing environmental pressures select for revertants of previously adaptive mutations. Reversions that sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we fit the adaptive reversion model to d N /d S decay curves and obtain estimates of local adaptation that are realistic in the context of bacterial genomes. These results argue for interpreting low values of d N /d S with caution, as they may emerge even when adaptive sweeps are frequent. This work reframes an old observation in bacterial evolution, illustrates the potential of mutation reversions to shape genomic landscapes over time, and highlights the need for additional research on bacterial genomic evolution on short time scales.
Keyphrases
  • machine learning
  • copy number
  • gene expression
  • risk assessment
  • electronic health record
  • human health
  • big data
  • mass spectrometry
  • deep learning