Synthetic analyses of phenotypic selection in natural populations: lessons, limitations and future directions

Kingsolver, Joel G.; Diamond, Sarah E.; Siepielski, Adam M.; Carlson, Stephanie M.

doi:10.1007/s10682-012-9563-5

Cited by 247 publications

(372 citation statements)

References 82 publications

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“…Nonlinear relationships are often observed or hypothesized in natural populations, typically as "fitness profiles" between trait values and fitness (Lande and Arnold 1983;Falconer and Mackay 1996;Kingsolver et al 2001Kingsolver et al , 2012. If the optimum phenotype is intermediate, there would be a negative covariance between V E and fitness, such that families with small variance would contribute more survivors, and correspondingly families with a large variance would have an advantage with disruptive or strong directional selection (Hill and Zhang 2004;Mulder et al 2007).…”

Section: Phenotypic Variability and Fitness In Natural Populationsmentioning

confidence: 99%

“…Kingsolver et al (2001Kingsolver et al ( , 2012, however, reviewed selection gradients estimated in a range of natural populations and found that in only a few studies negative quadratic regression coefficients (b 2 ) were actually obtained, indicating that strong stabilizing selection is rarely detected. The value obtained here for the piglet data implies very weak stabilizing selection.…”

Section: Phenotypic Variability and Fitness In Natural Populationsmentioning

confidence: 99%

“…They also showed that phenotypic relationships were often more linear than the genetic relationships due to dilution with environmental covariance. Nonlinear relationships might also be expected when one of the traits, for example fitness, has an optimum value (Lande and Arnold 1983;Falconer and Mackay 1996;Kingsolver et al 2001Kingsolver et al , 2012. Such nonlinear relationships are often observed or hypothesized in natural populations, typically as "fitness profiles" between trait values and fitness (e.g., Falconer and Mackay 1996) that show whether phenotypes on one side of the distribution (directional), in the middle (stabilizing), or at extremes (disruptive) have highest fitness.…”

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Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

2015

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There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others.KEYWORDS genetics of environmental variance; optimum trait; fitness; complex traits; mass selection I N the classic model of quantitative genetics, the phenotype is assumed to be the sum of an effectively infinite number of genes and environmental effects; i.e., P ¼ G þ E (Falconer and Mackay 1996; Lynch and Walsh 1998). The phenotypic variance is the sum of the genetic (V G ) and environmental (V E ) variance. It is assumed that the environmental variance is homogeneous across genotypes, but recently there is evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its V E ; is under genetic control (Hill and Mulder 2010). This might be expressed as genetic heterogeneity in the withinindividual variance of a trait with repeat measurements, such as weight of individual piglets in a litter or total litter weight across parities, or as a difference in within-family variance for traits such as juvenile body weight expressed once.The median genetic coefficient of variation for V E (GCV VE ¼ s Av =V E ; where s Av is additive genetic variance in V E ) is 0.3 based on a review of 14 studies with estimates of genetic variance in V E primarily on livestock populations (Hill and Mulder 2010). This indicates that V E could be increased or decreased by 30% if changed by one genetic standard deviation. These analyses were mainly based on genetic analysis...

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Section: Phenotypic Variability and Fitness In Natural Populationsmentioning

confidence: 99%

Section: Phenotypic Variability and Fitness In Natural Populationsmentioning

confidence: 99%

mentioning

confidence: 99%

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Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

2015

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“…Although most theoretical work assumes V s $ 20, empirical estimates of this parameter are lower (median = 5) (Kingsolver et al 2001(Kingsolver et al , 2012Johnson and Barton 2005), so we fixed V s = 5 to fit Equation (5) to the data. Maximum-likelihood optimization was conducted using the NLMIXED procedure in SAS (v. 9.3) (SAS Institute 2011).…”

Section: Tests Of Mutation-selection Balance Theorymentioning

confidence: 99%

Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata

2015

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How new mutations contribute to genetic variation is a key question in biology. Although the evolutionary fate of an allele is largely determined by its heterozygous effect, most estimates of mutational variance and mutational effects derive from highly inbred lines, where new mutations are present in homozygous form. In an attempt to overcome this limitation, middle-class neighborhood (MCN) experiments have been used to assess the fitness effect of new mutations in heterozygous form. However, because MCN populations harbor substantial standing genetic variance, estimates of mutational variance have not typically been available from such experiments. Here we employ a modification of the animal model to analyze data from 22 generations of Drosophila serrata bred in an MCN design. Mutational heritability, measured for eight cuticular hydrocarbons, 10 wing-shape traits, and wing size in this outbred genetic background, ranged from 0.0006 to 0.006 (with one exception), a similar range to that reported from studies employing inbred lines. Simultaneously partitioning the additive and mutational variance in the same outbred population allowed us to quantitatively test the ability of mutation-selection balance models to explain the observed levels of additive and mutational genetic variance. The Gaussian allelic approximation and house-of-cards models, which assume real stabilizing selection on single traits, both overestimated the genetic variance maintained at equilibrium, but the house-of-cards model was a closer fit to the data. This analytical approach has the potential to be broadly applied, expanding our understanding of the dynamics of genetic variance in natural populations.

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“…Since Lande and Arnold's 1983 seminal paper "The measurement of selection on correlated characters", hundreds of evolutionary biologists have measured phenotypic selection in wild populations (Kingsolver et al 2012). These microevolutionary studies aim to understand the process of adaptive evolution, by regressing variation in putatively adaptive traits against measurements of fitness.…”

Section: # Springer Science+business Media New York 2014mentioning

confidence: 99%

New Synthesis: The Evolutionary Ecology of Floral Volatiles

Parachnowitsch

2014

J Chem Ecol

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Synthetic analyses of phenotypic selection in natural populations: lessons, limitations and future directions

Cited by 247 publications

References 82 publications

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata

New Synthesis: The Evolutionary Ecology of Floral Volatiles

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