Using natural variation to understand complex traits

A new approach to understand the molecular basis of complex traits is reported in PLoS Genetics by the Hibberd lab in collaboration with Steven Kelly.  Natural and induced variation within model organisms have been instrumental in increasing our understanding of how genes produce living organisms.  However there are many complex traits that are so ancient that within one species there is insufficient variation for the genetic basis to be investigated.  We show that deep evolutionary comparisons of gene expression can provide novel insight into the genetic mechanisms controlling biological traits. 

We developed new computational algorithms to allow us to analyze genes from plants that last shared a common ancestor around 140 million years ago. These algorithms vastly improve the accuracy with which the expression of genes from distantly related species can be compared.  Using these new approaches, the lab investigated how distantly related plants use homologous genes to control the complex trait known as C₄ photosynthesis.  This new research showed that the same key control genes known as "transcription factors" are involved in the evolution of C₄ photosynthesis in these distant relatives that evolved this trait independently.  This finding is important because species that use C₄ photosynthesis are the most productive on the planet, and there are international efforts to engineer this system into less productive crops to increase yield and contribute to Food Security.