Presenter Information

Elizabeth BrooksFollow

Presentation Title

ModEDI: Extensible Models of Evolution with Developmental Interactions

Presentation Type

Lightning Session

Abstract

Quantitative genetics is the study of complex biological traits, or traits controlled by more than one gene. A primary goal of quantitative genetic studies is the development of computational models for predicting the evolution of physical traits in response to selection. The majority of models for analyzing the evolution of multiple traits employ a constant genetic variance-covariance matrix (G-matrix) to describe the distribution of genetic variation. While G-matrix based models provide a reasonable approximation of short term evolution, they may not sufficiently capture all important associations between traits. This is due to the fact that nonlinear interactions between developmental factors underlying the production of traits can result in dramatic changes in genetic variances and covariances during the process of evolution. To further investigating this important issue, we have developed an object-oriented code base, Models of Evolution with Developmental Interactions (ModEDI). Our code base implements a powerful, general mathematical and conceptual framework developed by Sean Rice. This framework utilizes a phenotypic landscape to explicitly incorporate the effects of development on heritable phenotypic variation. With our program, users are able to develop custom simulations for analyzing the evolution of multiple physical traits, while allowing for interactions between overlapping sets of developmental factors. Initial results from simulations performed with ModEDI indicate that developmental interactions may substantially alter evolutionary trajectories.

Start Date

10-5-2018 3:55 PM

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May 10th, 3:55 PM

ModEDI: Extensible Models of Evolution with Developmental Interactions

Quantitative genetics is the study of complex biological traits, or traits controlled by more than one gene. A primary goal of quantitative genetic studies is the development of computational models for predicting the evolution of physical traits in response to selection. The majority of models for analyzing the evolution of multiple traits employ a constant genetic variance-covariance matrix (G-matrix) to describe the distribution of genetic variation. While G-matrix based models provide a reasonable approximation of short term evolution, they may not sufficiently capture all important associations between traits. This is due to the fact that nonlinear interactions between developmental factors underlying the production of traits can result in dramatic changes in genetic variances and covariances during the process of evolution. To further investigating this important issue, we have developed an object-oriented code base, Models of Evolution with Developmental Interactions (ModEDI). Our code base implements a powerful, general mathematical and conceptual framework developed by Sean Rice. This framework utilizes a phenotypic landscape to explicitly incorporate the effects of development on heritable phenotypic variation. With our program, users are able to develop custom simulations for analyzing the evolution of multiple physical traits, while allowing for interactions between overlapping sets of developmental factors. Initial results from simulations performed with ModEDI indicate that developmental interactions may substantially alter evolutionary trajectories.