Detecting Polygenic Evolution: Problems, Pitfalls, and Promises

Unraveling the genetic basis of organismal form and function remains one of the major goals of evolutionary biology. Theory has long supported a model of polygenic evolution in which quantitative traits are underpinned by many genes of small effect, but empirical methods have lacked the power to detect causative loci when effect sizes are small or moderate. We (i) review traditional approaches used for identifying the molecular basis of phenotypic traits, to highlight the inherent problems and pitfalls that bias them towards the detection of large-effect loci. We then (ii) outline the promises of recent statistical frameworks to detect polygenic signatures of trait evolution, and discuss some of the first studies in evolutionary biology employing these approaches. Lastly, we (iii) outline future directions and point to areas that still need development.

TrendsUnderstanding the genetic basis of organismal form and function is fundamental in evolutionary biology.Theoretical work supports models of polygenic evolution, but years of underpowered mapping analyses have biased the literature in favor of large-effect QTLs.The disconnect between theoretical models and empirical data is troublesome because it distorts our understanding of the molecular targets of selection.Recent methodological advancements, and improvements in statistics and experimental designs, promise a less-biased empirical evaluation of the causal variants of phenotypic evolution.Despite these advancements, the application of new methods has been slow, and empirical data powerful enough to genetically dissect polygenic traits are only starting to emerge.