Biology subjects

Adami, C.

Publications and source records attributed to Adami, C..

5 recordsLinked to original sources

bioRxiv2024

Reduced selection during sweeps lead to adaptive momentum on rugged landscapes

AbstractEvolutionary theory seeks to explain the remarkable diversity and adaptability of life on Earth. Current theory offers substantial explanatory power, but it overlooks important transient dynamics that are prominent only when populations are outside equilibrium, such as during selective sweeps. We identify a dynamic that we call "adaptive momentum" whereby lineages with a selective advantage can temporarily sustain more deleterious mutations. This reduction in the strength of purifying selection allows populations to explore fitness valleys that are usually too costly to enter, potentially leading to the discovery of otherwise inaccessible fitness peaks. Using mathematical and agent-based simulations, we demonstrate adaptive momentum and show how periods of disequilibrium become windows of enhanced adaptation. Genetic exploration can occur during these windows without requiring mechanisms such as changing environments or complex landscapes. Adaptive momentum provides a simple potential explanation for bursts of rapid evolution observed in nature, including in pathogens such as SARS-CoV-2 and cancers. (152 words)

evolutionary biology↗

bioRxiv2019

Mechanism of perceived duration in artificial brains suggests new model of attentional entrainment

While cognitive theory has advanced several candidate frameworks to explain attentional entrainment, the neural basis for the temporal allocation of attention is unknown. Here we present a new model of attentional entrainment that is guided by empirical evidence obtained using a cohort of 50 artificial brains. These brains were evolved in silico to perform a duration judgement task similar to one where human subjects perform duration judgements in auditory oddball paradigms1. We found that the artificial brains display psychometric characteristics remarkably similar to those of human listeners, and also exhibit similar patterns of distortions of perception when presented with out-of-rhythm oddballs. A detailed analysis of mechanisms behind the duration distortion in the artificial brains suggests that their attention peaks at the end of the tone, which is inconsistent with previous attentional entrainment models. Instead, our extended model of entrainment emphasises increased attention to those aspects of the stimulus that the brain expects to be highly informative.

neuroscience↗

bioRxiv2019

Moderate amounts of epistasis are not evolutionarily stable in small populations

High mutation rates select for the evolution of mutational robustness where populations inhabit flat fitness peaks with little epistasis, protecting them from lethal mutagenesis. Recent evidence suggests that a different effect protects small populations from extinction via the accumulation of deleterious mutations. In drift robustness, populations tend to occupy peaks with steep flanks and positive epistasis between mutations. However, it is not known what happens when mutation rates are high and population sizes are small at the same time. Using a simple fitness model with variable epistasis, we show that the equilibrium fitness has a minimum as a function of the parameter that tunes epistasis, implying that this critical point is an unstable fixed point for evolutionary trajectories. In agent-based simulations of evolution at finite mutation rate, we demonstrate that when mutations can change epistasis, trajectories with a subcritical value of epistasis evolve to decrease epistasis, while those with supercritical initial points evolve towards higher epistasis. These two fixed points can be identified with mutational and drift robustness, respectively.

evolutionary biology↗

bioRxiv2018

Mapping the Peaks: Fitness Landscapes of the Fittest and the Flattest

BackgroundPopulations exposed to a high mutation rate harbor abundant deleterious genetic variation, leading to depressed mean fitness. This reduction in mean fitness presents an opportunity for selection to restore adaptation through the evolution of mutational robustness. In extreme cases, selection for mutational robustness can lead to \"flat\" genotypes (with low fitness but high robustness) out-competing \"fit\" genotypes with high fitness but low robustness--a phenomenon known as \"survival of the flattest\". While this effect was previously explored using the digital evolution system Avida, a complete analysis of the local fitness landscapes of \"fit\" and \"flat\" genotypes has been lacking, leading to uncertainty about the genetic basis of the survival of the flattest effect.\n\nResultsHere, we repeated the survival of the flattest study and analyzed the mutational neighborhoods of fit and flat genotypes. We found that flat genotypes, compared to the fit genotypes, had a reduced likelihood of deleterious mutations as well as an increased likelihood of neutral and, surprisingly, of lethal mutations. This trend holds for mutants one to four substitutions away from the wild-type sequence. We also found that flat genotypes have, on average, no epistasis between mutations, while fit genotypes have, on average, positive epistasis.\n\nConclusionsOur results demonstrate that the genetic causes of mutational robustness on complex fitness landscapes are multifaceted. While the traditional idea of the survival of the flattest effect emphasized the evolution of increased neutrality, others have argued for increased mutational sensitivity in response to strong mutational loads. Our results show that both increased neutrality and increased lethality can lead to the evolution of mutational robustness. Furthermore, strong negative epistasis is not required for mutational sensitivity to lead to mutational robustness. Overall, these results suggest that mutational robustness is achieved by minimizing heritable deleterious variation.

evolutionary biology↗

bioRxiv2017

Genome size and the extinction of small populations

Although extinction is ubiquitous throughout the history of life, insight into the factors that drive extinction events are often difficult to decipher. Most studies of extinction focus on inferring causal factors from past extinction events, but these studies are constrained by our inability to observe extinction events as they occur. Here, we use digital evolution to avoid these constraints and study \"extinction in action\". We focus on the role of genome size in driving population extinction, as previous work both in comparative genomics and digital evolution has shown a correlation between genome size and extinction. We find that extinctions in small populations are caused by large genome size. This relationship between genome size and extinction is due to two genetic mechanisms that increase a populations lethal mutational burden: large genome size leads to both an increased lethal mutation rate and an increased likelihood of stochastic reproduction errors and non-viability. We further show that this increased lethal mutational burden is directly due to genome expansions, as opposed to subsequent adaptation after genome expansion. These findings suggest that large genome size can enhance the extinction likelihood of small populations and may inform which natural populations are at an increased risk of extinction.

evolutionary biology↗