Virus EvolutionEvolutionary BiologyPeer-reviewed journal article
Substantial Deceleration of Adaptation of HIV-1 Within 1,500 Generations in an Experimental Evolution: A Genomic Perspective
Ali MovasatiiD, Christine Leemann, Kathrin NeumanniD, Rongfeng Chen, Lygeri SakellaridiiD, Karin Jutta MetzneriD, Roland R. RegoesiD
Abstract
Numerous experimental evolution studies have suggested that adaptation rate of microbial populations evolving in stable environments decline over time. Despite the generality of this phenomenon across different domains of life, the timing and magnitude of decline in adaptation can vary greatly based on the idiosyncrasies of the biological system. To investigate the characteristics of adaptation deceleration in a fast-evolving virus, we propagated HIV-1 in two human T-cell lines (MT-2 and MT-4) for approximately 4.8 years and tracked its genome evolution through next-generation sequencing. The curated sequencing data covering the whole-genome can be accessed and explored via LTEEviz, an interactive web application. Time-resolved sequencing data uncovered that despite constant fixation rate of 0.085 (MT-2) and 0.042 (MT-4) mutations per generation, the fixation kinetics of adaptive mutations changed considerably over time. The rate of fixation of adaptive parallel mutations decreased by 44% per 300 generations, while their conferred fitness gain decreased by 27% (MT-2) and 18% (MT-4) per every added adaptive mutation in their genetic background. The early and substantial deceleration of adaptation in our HIV-1 populations can, at least in part, be explained by diminishing gains of adaptive mutations. Furthermore, we identified genomic patterns consistent with a hard selective sweep that occurred in one population later in the experiment. Together, our results confirm that HIV-1 genomic evolution is characterized by a swift and substantial deceleration of adaptation, while also revealing that episodes of positive selection can occur beyond the initial adaptive phase.
- organism: human
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- Citations
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- FWCI
- 0.00
- Field percentile
- top 30%
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