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Predicting long-term response to selection.

¹Department of Biology, Concordia University, Montreal, Quebec, Canada. jreeve@vax2.concordia.ca

Genetical Research

|March 31, 2000

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Lande's equation accurately predicts evolutionary trait response when allele effects are normally distributed. However, leptokurtic distributions or limited loci can lead to inaccurate predictions of evolutionary trajectories.

Area of Science:

Evolutionary Biology
Quantitative Genetics
Population Genetics

Background:

Lande's equation is a cornerstone for predicting evolutionary trait responses.
Assumptions of constant genetic parameters may be violated in finite populations with changing allele frequencies.

Purpose of the Study:

To test the accuracy of Lande's equation under simulated directional selection in finite populations.
To investigate the impact of allele distribution and locus number on prediction accuracy.

Main Methods:

Stochastic simulation of finite populations with individuals having a finite number of loci.
Comparison of Lande's equation predictions with simulated evolutionary trajectories.
Examination of predictions under different allelic distribution assumptions (Gaussian vs. leptokurtic).

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Main Results:

Predictions are highly accurate when allelic effects are normally distributed, aligning with Lande's Gaussian approximation.
Leptokurtic distributions (e.g., 'house-of-cards' model) lead to underestimation of response rates and overestimation of time to equilibrium.
Finite biallelic loci limit trait divergence, potentially causing suboptimal equilibria if optimal values exceed achievable limits.

Conclusions:

The accuracy of Lande's equation is sensitive to the distribution of allelic effects and the genetic architecture of traits.
Deviations from normality in allele effects or constraints imposed by finite loci can compromise predictive power.
Understanding these limitations is crucial for accurate evolutionary predictions in empirical settings.