Wrightscape: Inferring Adaptive Landscapes from Phylogentic Trees

Abstract

Adaptive landscapes are powerful representations of the forces of natural selection and underlie much evolutionary theory. However, empirically mapping an adaptive landscape is a challenging process, relying on measurements of both trait and fitness values across a distribution of species. Meanwhile, recent advances in both laboratory and computational genetics have made accurate phylogenetic trees readily available for many species. Rather than look at species independently, we can now use their shared history and ancestry to explore questions about the adaptive landscapes on which they have evolved. We use the phylogenetic trees to take us back into the past and follow the course of evolution and speciation over time. Existing methods have only been able to address the case of a single adaptive peak, since they rely partly on an analytic technique that requires a linear selective force. Multiple adaptive peaks require nonlinear forces, and a computational paradigm shift in the approach to comparative methods. Computational tricks and high-performance computing resources enable us to explore arbitrary landscapes ‐ non-linear selection with multiple peaks.