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进化拯救越过适应景观。

Evolutionary Rescue over a Fitness Landscape.

机构信息

Institut des Sciences de l'Evolution de Montpellier (ISEM), Université de Montpellier, Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), École Pratique des Hautes Études (EPHE), 34095 Montpellier, France

Centre d'Ecologie Fonctionnelle et Evolutive (CEFE) Unité Mixte de Recherche (UMR) 5175, CNRS, Université de Montpellier, Université Paul-Valéry Montpellier, EPHE, 34293 Montpellier, CEDEX 5, France.

出版信息

Genetics. 2018 May;209(1):265-279. doi: 10.1534/genetics.118.300908. Epub 2018 Mar 13.

Abstract

Evolutionary rescue describes a situation where adaptive evolution prevents the extinction of a population facing a stressing environment. Models of evolutionary rescue could in principle be used to predict the level of stress beyond which extinction becomes likely for species of conservation concern, or, conversely, the treatment levels most likely to limit the emergence of resistant pests or pathogens. Stress levels are known to affect both the rate of population decline (demographic effect) and the speed of adaptation (evolutionary effect), but the latter aspect has received less attention. Here, we address this issue using Fisher's geometric model of adaptation. In this model, the fitness effects of mutations depend both on the genotype and the environment in which they arise. In particular, the model introduces a dependence between the level of stress, the proportion of rescue mutants, and their costs before the onset of stress. We obtain analytic results under a strong-selection-weak-mutation regime, which we compare to simulations. We show that the effect of the environment on evolutionary rescue can be summarized into a single composite parameter quantifying the effective stress level, which is amenable to empirical measurement. We describe a narrow characteristic stress window over which the rescue probability drops from very likely to very unlikely as the level of stress increases. This drop is sharper than in previous models, as a result of the decreasing proportion of stress-resistant mutations as stress increases. We discuss how to test these predictions with rescue experiments across gradients of stress.

摘要

进化拯救描述了一种情况,即适应性进化可以防止面临压力环境的种群灭绝。进化拯救模型原则上可以用于预测物种保护关注的压力水平,超过这个水平,物种灭绝的可能性就会增加;或者相反,预测最有可能限制抗药性害虫或病原体出现的处理水平。压力水平已知会影响种群减少的速度(人口效应)和适应的速度(进化效应),但后者受到的关注较少。在这里,我们使用 Fisher 的适应几何模型来解决这个问题。在这个模型中,突变的适应度效应既取决于基因型,也取决于它们出现的环境。特别是,该模型在压力开始之前引入了压力水平、拯救突变体的比例及其成本之间的依赖性。我们在强选择-弱突变的条件下得到了解析结果,并将其与模拟结果进行了比较。我们表明,环境对进化拯救的影响可以概括为一个单一的综合参数,量化有效压力水平,这是可以通过经验测量的。我们描述了一个狭窄的特征压力窗口,在这个窗口内,随着压力水平的增加,拯救的可能性从很有可能迅速下降到几乎不可能。由于随着压力的增加,抗压力突变体的比例下降,因此这种下降比以前的模型更为明显。我们讨论了如何通过在压力梯度上进行拯救实验来检验这些预测。

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本文引用的文献

1
WHEN DOES EVOLUTION BY NATURAL SELECTION PREVENT EXTINCTION?
Evolution. 1995 Feb;49(1):201-207. doi: 10.1111/j.1558-5646.1995.tb05971.x.
2
EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS.
Evolution. 1995 Feb;49(1):151-163. doi: 10.1111/j.1558-5646.1995.tb05967.x.
3
Epistasis and the Evolution of Antimicrobial Resistance.
Front Microbiol. 2017 Feb 17;8:246. doi: 10.3389/fmicb.2017.00246. eCollection 2017.
4
Soft Selective Sweeps in Evolutionary Rescue.
Genetics. 2017 Apr;205(4):1573-1586. doi: 10.1534/genetics.116.191478. Epub 2017 Feb 17.
5
Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients.
Evolution. 2017 Jan;71(1):23-37. doi: 10.1111/evo.13111. Epub 2016 Nov 29.
6
The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation.
Genetics. 2016 Dec;204(4):1541-1558. doi: 10.1534/genetics.116.187385. Epub 2016 Oct 21.
7
Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?
PLoS Comput Biol. 2016 Jan 28;12(1):e1004689. doi: 10.1371/journal.pcbi.1004689. eCollection 2016 Jan.
8
The Utility of Fisher's Geometric Model in Evolutionary Genetics.
Annu Rev Ecol Evol Syst. 2014 Nov 1;45:179-201. doi: 10.1146/annurev-ecolsys-120213-091846.
9
The Role of Recombination in Evolutionary Rescue.
Genetics. 2016 Feb;202(2):721-32. doi: 10.1534/genetics.115.180299. Epub 2015 Dec 1.
10
The fitness effect of mutations across environments: Fisher's geometrical model with multiple optima.
Evolution. 2015 Jun;69(6):1433-1447. doi: 10.1111/evo.12671. Epub 2015 Jun 10.

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