Understanding how plants adapt to drought is critical for crop improvement in the face of rapid climate change and important for understanding the evolution of species in the wild. This project combined computational and experimental innovations to investigate the functional genomics and evolutionary ecology of drought adaptation.

We found evidence that widespread genetic loss-of-function can play an important role in the evolution of drought adaptation in plants. These findings further challenge prior assumptions about the molecular basis of adaptation with important implications for theoretical and applied genetics. Specifically, they indicate that parallel molecular evolution, which is common for genes exhibiting loss-of-function, may play a previously underappreciated role in adaptive evolution. This calls for a reconsideration of the tools used to detect genes involved in the evolution of natural populations and crops. This work presents a broadly scalable framework using whole genome sequence data to identify functionally definitive gene variants affecting phenotypes and experiencing selection. It also highlights the importance of combining population genetics with experimental validation to test hypotheses about gene functional evolution.

The results of this research inspire new opportunities in agriculture for engineering climate resilience in crops. Specifically, they suggest that targeted gene knockouts using emerging technologies may be particularly valuable for directed molecular breeding. These findings have implications for public attitudes toward genetically engineered crops, revealing that knockout mutations can be a natural source of beneficial genetic variation, in contrast to assumptions that gene knockouts are necessarily deleterious.

This work also pioneered the use of remotely sensed drought to scale up the study of the climatic drivers of plant adaptation. These investigations demonstrate the value of using allele environment associations to identify candidate loci associated with phenotypes directly. Specifically, we find that allele associations with drought timing measured using remote sensing technology strongly predict allele associations with flowering time. We also show that remotely sensed drought is an effective tool for predicting broader patterns of trait variation by applying it to test classic hypotheses about annual and perennial life history strategies in relation to drought. We find support, for the first time in a phylogenetic comparative analysis, for the classic prediction that annual species should occur in environments where droughts are frequent and predictable. Thus, this work reveals the importance of drought regimens to predict adaptive traits in plants.

The results from this work have been published in eLife, New Phytologist and the PhD dissertation of PI Monroe, with the publication in eLife receiving additional attention with a F1000Prime recommendation. This grant has also supported work included in several manuscripts currently being prepared for submission. PI Monroe presented this research at the international Evolution conference in 2017. He was also invited to give research seminars presenting work supported by this grant at Appalachian State University, Duke University, the International Rice Research Institute, Australian National University, Colorado State University, The Max Planck Institute for Developmental Biology, The Max Planck Institute for Plant Breeding, The University of Cologne, The International Center for Tropical Agriculture, and the University of California Davis.

This project resulted in undergraduate mentorship and authorship for contributions made. Additionally, while conducting this research, PI Monroe participated in an initiative called Research Mentoring to Advance Inclusivity in STEM.  This program provided training and the development of lesson plans to teach peers and their mentees about implicit bias. 

Last Modified: 08/15/2019
Modified by: J. Grey Monroe