Developing maps of fitness consequences for plant genomes

Abstract

Predicting the fitness consequences of mutations, and their concomitant impacts on molecular and cellular function as well as organismal phenotypes, is an important challenge in biology that has new relevance in an era when genomic data is readily available. The ability to construct genomewide maps of fitness consequences in plant genomes is a recent development that has profound implications for our ability to predict the fitness effects of mutations and discover functional elements. Here we highlight approaches to building fitness consequence maps to infer regions under selection. We emphasize computational methods applied primarily to the study of human disease that translate physical maps of within-species genome variation into maps of fitness effects of individual natural mutations. Maps of fitness consequences in plants, combined with traditional genetic approaches, could accelerate discovery of functional elements such as regulatory sequences in non-coding DNA and genetic polymorphisms associated with key traits, including agronomically-important traits such as yield and environmental stress responses.