Is evolution predictable? Quantitative genetics under complex genotype‐phenotype maps

Milocco, Lisandro; Salazar‐Ciudad, Isaac

doi:10.1111/evo.13907

Cited by 38 publications

(21 citation statements)

References 63 publications

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“…Mapping multidimensional fitness functions will involve extensive observational and experimental work guided by organismal-level theory such as dynamic energy budget models [51] and combined with the community ecological theory of species interactions [52,53]. The nonlinearity of the genotype-phenotype map presents an additional challenge to applying quantitative genetics models to evolutionary rescue [54]. Future studies that transplant populations and manipulate environmental conditions will help probe the tails of fitness functions, which can be fitted by nonparametric functions instead of assuming quadratics [55].…”

Section: Discussionmentioning

confidence: 99%

Ecological limits to evolutionary rescue

Klausmeier

Osmond

Kremer

et al. 2020

Phil. Trans. R. Soc. B

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Environments change, for both natural and anthropogenic reasons, which can threaten species persistence. Evolutionary adaptation is a potentially powerful mechanism to allow species to persist in these changing environments. To determine the conditions under which adaptation will prevent extinction (evolutionary rescue), classic quantitative genetics models have assumed a constantly changing environment. They predict that species traits will track a moving environmental optimum with a lag that approaches a constant. If fitness is negative at this lag, the species will go extinct. There have been many elaborations of these models incorporating increased genetic realism. Here, we review and explore the consequences of four ecological complications: non-quadratic fitness functions, interacting density- and trait-dependence, species interactions and fundamental limits to adaptation. We show that non-quadratic fitness functions can result in evolutionary tipping points and existential crises, as can the interaction between density- and trait-dependent mortality. We then review the literature on how interspecific interactions affect adaptation and persistence. Finally, we suggest an alternative theoretical framework that considers bounded environmental change and fundamental limits to adaptation. A research programme that combines theory and experiments and integrates across organizational scales will be needed to predict whether adaptation will prevent species extinction in changing environments. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

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Section: Discussionmentioning

confidence: 99%

Ecological limits to evolutionary rescue

Klausmeier

Osmond

Kremer

et al. 2020

Phil. Trans. R. Soc. B

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“…to use the previous, simpler models as null hypotheses. This approach has recently been used to show that some quantitative population genetics models of phenotypic evolution perform poorly near large discontinuities of the genotype–phenotype map [ 74 ]. A second possibility is to exploit bioinformatic and statistical tools developed for the analysis of ‘real’ genomes, such as multiple sequence alignments and phylogenetic trees (and conversely, the validity of these tools can be tested with evolutionary models [ 75 ]).…”

Section: Discussionmentioning

confidence: 99%

Modelling the evolution of novelty: a review

Colizzi

Hogeweg

Vroomans

2022

Essays in Biochemistry

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Evolution has been an inventive process since its inception, about 4 billion years ago. It has generated an astounding diversity of novel mechanisms and structures for adaptation to the environment, for competition and cooperation, and for organisation of the internal and external dynamics of the organism. How does this novelty come about? Evolution builds with the tools available, and on top of what it has already built – therefore, much novelty consists in repurposing old functions in a different context. In the process, the tools themselves evolve, allowing yet more novelty to arise. Despite evolutionary novelty being the most striking observable of evolution, it is not accounted for in classical evolutionary theory. Nevertheless, mathematical and computational models that illustrate mechanisms of evolutionary innovation have been developed. In the present review, we present and compare several examples of computational evo–devo models that capture two aspects of novelty: ‘between-level novelty’ and ‘constructive novelty.’ Novelty can evolve between predefined levels of organisation to dynamically transcode biological information across these levels – as occurs during development. Constructive novelty instead generates a level of biological organisation by exploiting the lower level as an informational scaffold to open a new space of possibilities – an example being the evolution of multicellularity. We propose that the field of computational evo–devo is well-poised to reveal many more exciting mechanisms for the evolution of novelty. A broader theory of evolutionary novelty may well be attainable in the near future.

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“…In such dynamic models, robustness to various disturbances appear as an emergent property of the model complexity, caused by regulatory feedbacks, that cannot be easily deduced from the model parameters. Although the potential palette of relevant dynamic models is large and could include morphological development models (Milocco and Salazar-Ciudad, 2020), RNA folding models (Wagner and Stadler, 1999), or metabolic models (Nijhout et al, 2019), evolutionary biologists have often considered gene regulatory network models as a good compromise between complexity and numerical tractability for studying the evolution of canalization and robustness (Kauffman, 1969;Wagner, 1994;Smolen et al, 2000;Le Cunff and Pakdaman, 2012).…”

Section: Introductionmentioning

confidence: 99%

Gene network robustness as a multivariate character

Rouzic¹

2022

Peer Community Journal

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Robustness to genetic or environmental disturbances is often considered as a key property of living systems. Yet, in spite of being discussed since the 1950s, how robustness emerges from the complexity of genetic architectures and how it evolves still remains unclear. In particular, whether or not robustness is independent to various sources of perturbations conditions the range of adaptive scenarios that can be considered. For instance, selection for robustness to heritable mutations is likely to be modest and indirect, and its evolution might result from indirect selection on a pleiotropically-related character (e.g., homeostasis). Here, I propose to treat various robustness measurements as quantitative characters, and study theoretically, by individual-based simulations, their propensity to evolve independently. Based on a simple evolutionary model of a gene regulatory network, I showed that five measurements of the robustness of gene expression to genetic or non-genetic disturbances were substantially correlated. Yet, robustness was mutationally variable in several dimensions, and robustness components could evolve differentially under direct selection pressure. Therefore, the fact that the sensitivity of gene expression to mutations and environmental factors rely on the same gene networks does not preclude distinct evolutionary histories of robustness components.

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Is evolution predictable? Quantitative genetics under complex genotype‐phenotype maps

Cited by 38 publications

References 63 publications

Ecological limits to evolutionary rescue

Ecological limits to evolutionary rescue

Modelling the evolution of novelty: a review

Gene network robustness as a multivariate character

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