scholarly journals The Origin of Additive Genetic Variance Driven by Positive Selection

2020 ◽  
Vol 37 (8) ◽  
pp. 2300-2308
Author(s):  
Li Liu ◽  
Yayu Wang ◽  
Di Zhang ◽  
Zhuoxin Chen ◽  
Xiaoshu Chen ◽  
...  
Keyword(s):  
Natural Selection ◽  
Positive Selection ◽  
Fundamental Theorem ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Adaptive Divergence ◽  
Population Admixture ◽  
Simple Explanation ◽  
Additive Variance ◽  
Fisher’S Fundamental Theorem

Abstract Fisher’s fundamental theorem of natural selection predicts no additive variance of fitness in a natural population. Consistently, studies in a variety of wild populations show virtually no narrow-sense heritability (h2) for traits important to fitness. However, counterexamples are occasionally reported, calling for a deeper understanding on the evolution of additive variance. In this study, we propose adaptive divergence followed by population admixture as a source of the additive genetic variance of evolutionarily important traits. We experimentally tested the hypothesis by examining a panel of ∼1,000 yeast segregants produced by a hybrid of two yeast strains that experienced adaptive divergence. We measured >400 yeast cell morphological traits and found a strong positive correlation between h2 and evolutionary importance. Because adaptive divergence followed by population admixture could happen constantly, particularly in species with wide geographic distribution and strong migratory capacity (e.g., humans), the finding reconciles the observation of abundant additive variances in evolutionarily important traits with Fisher’s fundamental theorem of natural selection. Importantly, the revealed role of positive selection in promoting rather than depleting additive variance suggests a simple explanation for why additive genetic variance can be dominant in a population despite the ubiquitous between-gene epistasis observed in functional assays.

scholarly journals The source of additive genetic variance of evolutionarily important traits

2019 ◽  
Author(s):  
Li Liu ◽  
Yayu Wang ◽  
Di Zhang ◽  
Xiaoshu Chen ◽  
Zhijian Su ◽  
...  
Keyword(s):  
Natural Selection ◽  
Fundamental Theorem ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Adaptive Divergence ◽  
Population Admixture ◽  
Strong Positive Correlation ◽  
Narrow Sense Heritability ◽  
Additive Variance ◽  
Fisher’S Fundamental Theorem

AbstractFisher’s fundamental theorem of natural selection predicts no additive variance of fitness in a natural population. Consistently, observations in a variety of wild populations show virtually no narrow-sense heritability (h2) for traits important to fitness. However, counterexamples are occasionally reported, calling for a deeper understanding on the evolution of additive variance. In this study we propose adaptive divergence followed by population admixture as a source of the additive genetic variance of evolutionarily important traits. We experimentally tested the hypothesis by examining a panel of ~1,000 yeast segregants produced by a hybrid of two yeast strains that experienced adaptive divergence. We measured over 400 yeast cell morphological traits and found a strong positive correlation between h2 and evolutionary importance. Because adaptive divergence followed by population admixture could happen constantly, particularly in some species such as humans, the finding reconciles the observation of abundant additive variances in evolutionarily important traits with Fisher’s fundamental theorem of natural selection. It also suggests natural selection may effectively promote rather than suppress additive genetic variance in species with wide geographic distribution and strong migratory capacity.

scholarly journals Joint phenotypes, evolutionary conflict and the fundamental theorem of natural selection

2014 ◽  
Vol 369 (1642) ◽  
pp. 20130423 ◽  
Author(s):  
David C. Queller
Keyword(s):  
Natural Selection ◽  
Species Interactions ◽  
Fundamental Theorem ◽  
Genetic Variance ◽  
Inclusive Fitness ◽  
Evolutionary Conflict ◽  
Mean Fitness ◽  
The Mean ◽  
Multiple Species ◽  
Fisher’S Fundamental Theorem

Multiple organisms can sometimes affect a common phenotype. For example, the portion of a leaf eaten by an insect is a joint phenotype of the plant and insect and the amount of food obtained by an offspring can be a joint trait with its mother. Here, I describe the evolution of joint phenotypes in quantitative genetic terms. A joint phenotype for multiple species evolves as the sum of additive genetic variances in each species, weighted by the selection on each species. Selective conflict between the interactants occurs when selection takes opposite signs on the joint phenotype. The mean fitness of a population changes not just through its own genetic variance but also through the genetic variance for its fitness that resides in other species, an update of Fisher's fundamental theorem of natural selection. Some similar results, using inclusive fitness, apply to within-species interactions. The models provide a framework for understanding evolutionary conflicts at all levels.

Theorems of Natural Selection: Results of Price, Fisher, and Robertson

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Natural Selection ◽  
Fundamental Theorem ◽  
Selection Response ◽  
Relative Fitness ◽  
Additive Variance ◽  
Change In The Mean ◽  
Important Exception ◽  
The Mean ◽  
The Cost ◽  
Fisher’S Fundamental Theorem

This chapter reviews a number of “theorems” of natural selection. These include exact results (true mathematical theorems): the Robertson-Price identity, Price's general expression for any form of selection response, and the Fisher-Price-Ewens version of Fisher's fundamental theorem. Their generality comes as the cost of usually being very difficult to apply. An important exception is the Robertson-Price identity, which expresses the within-generation change in the mean of a trait as its covariance with relative fitness. This chapter also examines three classic approximations: Fisher's fundamental theorem for the behavior of mean population fitness, and Robertson's secondary theorem and the breeder's equation for the expected response in a trait under selection, showing both how these results are connected and the error given by the various approximations. Finally, the chapter examines the connection between the additive variance of a trait and its correlation with fitness.

Adding Dynamical Sufficiency to Fisher’s Fundamental Theorem of Natural Selection

2011 ◽  
Author(s):  
Philip J. Gerrish ◽  
Paul D. Sniegowski ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
Ch. Tsitouras ◽  
...  
Keyword(s):  
Natural Selection ◽  
Fundamental Theorem ◽  
Fisher’S Fundamental Theorem

scholarly journals The Price equation and reproductive value

2020 ◽  
Vol 375 (1797) ◽  
pp. 20190356 ◽  
Author(s):  
Alan Grafen
Keyword(s):  
Natural Selection ◽  
Fundamental Theorem ◽  
Structured Populations ◽  
Reproductive Value ◽  
Price Equation ◽  
Class Structure ◽  
Theme Issue ◽  
Starting Point ◽  
Important Idea ◽  
Fisher’S Fundamental Theorem

The Price equation is widely recognized as capturing conceptually important properties of natural selection, and is often used to derive versions of Fisher’s fundamental theorem of natural selection, the secondary theorems of natural selection and other significant results. However, class structure is not usually incorporated into these arguments. From the starting point of Fisher’s original connection between fitness and reproductive value, a principled way of incorporating reproductive value and structured populations into the Price equation is explained, with its implications for precise meanings of (two distinct kinds of) reproductive value and of fitness. Once the Price equation applies to structured populations, then the other equations follow. The fundamental theorem itself has a special place among these equations, not only because it always incorporated class structure (and its method is followed for general class structures), but also because that is the result that justifies the important idea that these equations identify the effect of natural selection. The precise definitions of reproductive value and fitness have striking and unexpected features. However, a theoretical challenge emerges from the articulation of Fisher’s structure: is it possible to retain the ecological properties of fitness as well as its evolutionary out-of-equilibrium properties? This article is part of the theme issue ‘Fifty years of the Price equation’.

scholarly journals Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution

2019 ◽  
Vol 110 (4) ◽  
pp. 383-395 ◽  
Author(s):  
Timothée Bonnet ◽  
Michael B Morrissey ◽  
Loeske E B Kruuk
Keyword(s):  
Natural Selection ◽  
Animal Models ◽  
Normal Distribution ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Relative Fitness ◽  
Parameter Estimates ◽  
Log Normal ◽  
Change In Mean ◽  
Log Normal Distribution

AbstractAdditive genetic variance in relative fitness (σA2(w)) is arguably the most important evolutionary parameter in a population because, by Fisher’s fundamental theorem of natural selection (FTNS; Fisher RA. 1930. The genetical theory of natural selection. 1st ed. Oxford: Clarendon Press), it represents the rate of adaptive evolution. However, to date, there are few estimates of σA2(w) in natural populations. Moreover, most of the available estimates rely on Gaussian assumptions inappropriate for fitness data, with unclear consequences. “Generalized linear animal models” (GLAMs) tend to be more appropriate for fitness data, but they estimate parameters on a transformed (“latent”) scale that is not directly interpretable for inferences on the data scale. Here we exploit the latest theoretical developments to clarify how best to estimate quantitative genetic parameters for fitness. Specifically, we use computer simulations to confirm a recently developed analog of the FTNS in the case when expected fitness follows a log-normal distribution. In this situation, the additive genetic variance in absolute fitness on the latent log-scale (σA2(l)) equals (σA2(w)) on the data scale, which is the rate of adaptation within a generation. However, due to inheritance distortion, the change in mean relative fitness between generations exceeds σA2(l) and equals (exp⁡(σA2(l))−1). We illustrate why the heritability of fitness is generally low and is not a good measure of the rate of adaptation. Finally, we explore how well the relevant parameters can be estimated by animal models, comparing Gaussian models with Poisson GLAMs. Our results illustrate 1) the correspondence between quantitative genetics and population dynamics encapsulated in the FTNS and its log-normal-analog and 2) the appropriate interpretation of GLAM parameter estimates.

scholarly journals Evolution of genetic variance during adaptive radiation

2017 ◽  
Author(s):  
Greg M. Walter ◽  
J. David Aguirre ◽  
Mark W. Blows ◽  
Daniel Ortiz-Barrientos
Keyword(s):  
Natural Selection ◽  
Adaptive Radiation ◽  
Genetic Variance ◽  
Allelic Variation ◽  
Genetic Correlations ◽  
Leaf Traits ◽  
Adaptive Divergence ◽  
Ecotypic Differentiation ◽  
Divergent Natural Selection ◽  
Rapid Divergence

AbstractGenetic correlations between traits can bias adaptation away from optimal phenotypes and constrain the rate of evolution. If genetic correlations between traits limit adaptation to contrasting environments, rapid adaptive divergence across a heterogeneous landscape may be difficult. However, if genetic variance can evolve and align with the direction of natural selection, then abundant allelic variation can promote rapid divergence during adaptive radiation. Here, we explored adaptive divergence among ecotypes of an Australian native wildflower by quantifying divergence in multivariate phenotypes of populations that occupy four contrasting environments. We investigated differences in multivariate genetic variance underlying morphological traits and examined the alignment between divergence in phenotype and divergence in genetic variance. We found that divergence in mean multivariate phenotype has occurred along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits, and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with most of the divergence in phenotype among ecotypes associated with a change in trait combinations that had substantial levels of genetic variance in each ecotype. Overall, our results suggest that divergent natural selection acting on high levels of standing genetic variation might fuel ecotypic differentiation during the early stages of adaptive radiation.

scholarly journals Deleterious mutations, apparent stabilizing selection and the maintenance of quantitative variation.

Genetics ◽  
1992 ◽  
Vol 132 (2) ◽  
pp. 603-618 ◽  
Author(s):  
A S Kondrashov ◽  
M Turelli
Keyword(s):  
Quantitative Trait ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Pleiotropic Effects ◽  
Direct Selection ◽  
Selection Function ◽  
Stabilizing Selection ◽  
Deleterious Mutations ◽  
Additive Variance ◽  
Deleterious Alleles

Abstract Apparent stabilizing selection on a quantitative trait that is not causally connected to fitness can result from the pleiotropic effects of unconditionally deleterious mutations, because as N. Barton noted, "...individuals with extreme values of the trait will tend to carry more deleterious alleles...." We use a simple model to investigate the dependence of this apparent selection on the genomic deleterious mutation rate, U; the equilibrium distribution of K, the number of deleterious mutations per genome; and the parameters describing directional selection against deleterious mutations. Unlike previous analyses, we allow for epistatic selection against deleterious alleles. For various selection functions and realistic parameter values, the distribution of K, the distribution of breeding values for a pleiotropically affected trait, and the apparent stabilizing selection function are all nearly Gaussian. The additive genetic variance for the quantitative trait is kQa2, where k is the average number of deleterious mutations per genome, Q is the proportion of deleterious mutations that affect the trait, and a2 is the variance of pleiotropic effects for individual mutations that do affect the trait. In contrast, when the trait is measured in units of its additive standard deviation, the apparent fitness function is essentially independent of Q and a2; and beta, the intensity of selection, measured as the ratio of additive genetic variance to the "variance" of the fitness curve, is very close to s = U/k, the selection coefficient against individual deleterious mutations at equilibrium. Therefore, this model predicts appreciable apparent stabilizing selection if s exceeds about 0.03, which is consistent with various data. However, the model also predicts that beta must equal Vm/VG, the ratio of new additive variance for the trait introduced each generation by mutation to the standing additive variance. Most, although not all, estimates of this ratio imply apparent stabilizing selection weaker than generally observed. A qualitative argument suggests that even when direct selection is responsible for most of the selection observed on a character, it may be essentially irrelevant to the maintenance of variation for the character by mutation-selection balance. Simple experiments can indicate the fraction of observed stabilizing selection attributable to the pleiotropic effects of deleterious mutations.

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