Complex Trait Evolution

We study the evolution of complex traits by simulating phenotypes determined by multiple loci and environmental effects. These traits harbor genetic variation, which is critical for evolution to occur. The genetic variance is often summarized in a matrix, called the G-matrix, which contains additive genetic variances and additive genetic covariances. The G-matrix describes the genetic architecture of complex traits. The Jones Lab, in collaboration with Steve Arnold (Oregon State University) and Reinhard Bürger (University of Vienna), has been using individual-based simulations to study the evolution of the genetic architecture (and other related issues).


The software we have used for our papers is freely available on GitHub. To learn more about these packages, consult our program note:

Jones, A. G., R. Bürger, and S. J. Arnold. 2018. The G-matrix simulator family: software for research and teaching. Journal of Heredity 109:825-829.


To write your own G-matrix simulation software, consult Adam Jones’ book:

C++ for Biologists: Evolutionary Models

(A free pdf is available here, or a hard copy can be purchased from Amazon)


Here is a summary of the available software packages:

G-matrix Simulator 2014: A Windows-based simulator that contains the code to produce the results reported by Jones et al. 2003, 2004 and 2012. This simulator has a graphical user interface and only works on Windows-based machines. Relevant papers:

Jones, A. G., S. J. Arnold, and R. Bürger. 2003. Stability of the G-matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift. Evolution 57:1747-1760.

Jones, A. G., S. J. Arnold, and R. Bürger. 2004. Evolution and stability of the G-matrix on a landscape with a moving optimum. Evolution 58:1639-1654.

Jones, A. G., R. Bürger, S. J. Arnold, P. A. Hohenlohe, and J. C. Uyeda. 2012. The effects of stochastic and episodic movement of the optimum on the evolution of the G-matrix and the response of the mean to selection. Journal of Evolutionary Biology 25:2210-2231.


G-matrix Home Version: This version of the simulator is similar to the 2014 version under the hood, but it has been streamlined to make it more usable in an instructional setting. This version is used in the Evolutionary Quantitative Genetics Workshop offered by Steve Arnold and Joe Felsenstein every summer.


G-matrix Command Line: A version of the simulator without a graphical user interface. The source code should compile for any operating system with a standard C++ compiler.


Local Adaptation and Epistasis: With this simulator, we explored the effects of pleiotropy and epistasis on the evolution of local adaptation. We also investigated the feasibility of detecting the loci affecting the trait in genome-wide scans of population differentiation. The results of this study are reported in the following paper:

Jones, A. G., S. J. Arnold, and R. Bürger. 2019. The effects of epistasis and pleiotropy on genome-wide scans for adaptive outlier loci. Journal of Heredity, in press.