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Open AccessJournal ArticleDOI

SLiM 3: Forward Genetic Simulations Beyond the Wright–Fisher Model

Benjamin C. Haller, +1 more
- 01 Mar 2019 - 
- Vol. 36, Iss: 3, pp 632-637
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TLDR
SLiM 3 is introduced, which contains two key advancements aimed at abolishing limitations in the Wright–Fisher model, and adds support for continuous space, including spatial interactions and spatial maps of environmental variables.
Abstract
With the desire to model population genetic processes under increasingly realistic scenarios, forward genetic simulations have become a critical part of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation framework is one of the most powerful and widely used tools in this area. However, its foundation in the Wright-Fisher model has been found to pose an obstacle to implementing many types of models; it is difficult to adapt the Wright-Fisher model, with its many assumptions, to modeling ecologically realistic scenarios such as explicit space, overlapping generations, individual variation in reproduction, density-dependent population regulation, individual variation in dispersal or migration, local extinction and recolonization, mating between subpopulations, age structure, fitness-based survival and hard selection, emergent sex ratios, and so forth. In response to this need, we here introduce SLiM 3, which contains two key advancements aimed at abolishing these limitations. First, the new non-Wright-Fisher or "nonWF" model type provides a much more flexible foundation that allows the easy implementation of all of the above scenarios and many more. Second, SLiM 3 adds support for continuous space, including spatial interactions and spatial maps of environmental variables. We provide a conceptual overview of these new features, and present several example models to illustrate their use.

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Citations
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Mutation bias reflects natural selection in Arabidopsis thaliana

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A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation

TL;DR: How different types of SVs affect ecological and evolutionary processes are reviewed; unifying definitions and recommendations for future studies are suggested; and a roadmap for the integration of SV's in ecoevolutionary studies is provided.
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Inferring whole-genome histories in large population datasets.

TL;DR: A new method for inferring genealogical histories from large-scale genetic data is used to characterize population structure using data from the 1000 Genomes Project, the UK Biobank and the Simons Genome Diversity Project.
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The inflated significance of neutral genetic diversity in conservation genetics

TL;DR: In this paper, the authors argue that no simple general relationship exists between neutral genetic diversity and the risk of species extinction, and instead, a better understanding of the properties of functional genetic diversity, demographic history, and ecological relationships is necessary for developing and implementing effective conservation genetic strategies.
References
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TL;DR: The nature of predation, the influence of population interactions on community structure, and Ecological applications at the level of communities and ecosystems are examined.
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Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes

TL;DR: Sparse trees and coalescence records are introduced as the key units of genealogical analysis and exact simulation of the coalescent with recombination for chromosome-sized regions over hundreds of thousands of samples is possible, and substantially faster than present-day approximate methods.
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