BREAD: Bioenergy-Crops Resilience and Evolution Dynamics
Authors:
Qun Liu1* ([email protected], PI), Sean McSweeney1, Shinjae Yoo1, Ljiljana Paša-Tolić2, Yasuo Yoshikuni3, Christopher S. Henry4, Huimin Zhao5, Clint W. Magill6, Jeffery Dangl7
Institutions:
1Brookhaven National Laboratory; 2Pacific Northwest National Laboratory; 3Lawrence Berkeley National Laboratory; 4Argonne National Laboratory; 5University of Illinois Urbana-Champaign; 6Texas A&M University; 7University of North Carolina–Chapel Hill
Abstract
Sorghum is the second most cultivated U.S. biofuel crop and is the primary source of biodiesel production worldwide. Due to its drought resistance and fast growth of biomass as a source for ethanol production, sorghum is one of DOE’s flagship bioenergy crops. However, sorghum diseases such as anthracnose, stalk rot, downy mildew, grain mold, and leaf blight reduce the yield of sorghum biomass production.
Anthracnose alone can lead to yield losses of up to 67% in susceptible sorghum cultivars. Therefore, improving anthracnose resistance and biocontrol in sorghum directly improves its biomass production and bioeconomy.
Sorghum anthracnose disease is caused by the hemibiotrophic fungal pathogen Colletotrichum sublineola. C. sublineola produces a stunning array of virulence effector proteins and other molecules that interact and hijack plant defense systems resulting in infection and disease in sorghum. Conversely, some sorghum cultivars encode intracellular innate immune receptors called nucleotide-binding leucine-rich repeat proteins (NLRs) that recognize effectors to elicit successful immune responses. The co-evolution of sorghum and C. sublineola drives cycles of infection and immunity. This project hypothesizes that the dynamic coevolution of effectors and NLR receptors forms the basis of sorghum immunity in response to C. sublineola and other pathogen infections. A key knowledge gap is that none of C. sublineola effectors are biochemically or structurally characterized.
Also, there is a lack of mechanistic data regarding the interactions between specific NLR proteins and specific effectors. This lack of molecular understanding of sorghum–C. sublineola interactions is the biggest impediment to the rational design of resistance to anthracnose in sorghum crops and is thus the focus of this project. Leveraging the available reference genome sequences for both sorghum and C. sublineola, group members are employing comparative genomics, transcriptomics, proteomics, and metabolomics to identify C. sublineola effectors and their respective NLRs. The group is using structural biology and bioimaging to characterize the temporal and spatial NLR-effector interactions across scales from atoms to cells and plants. Subsequently, engineering and biocontrol strategies targeting the characterized NLRs or C. sublineola are used to develop resilient and sustainable bioenergy crops. This team is developing computational resources to analyze molecular interactions and genetic co-evolution of the plant–pathosystem, and foundational large natural language models to integrate and train multimodal text and imaging data for predictive understanding of pathogenicity and biocontrol.
While this project focuses on the sorghum C. sublineola system, the results will lay down a groundwork for studying plant-pathogen interactions more broadly. The research strategies and techniques developed under this project will advance scientists’ ability to rapidly respond to emerging biothreats impacting bioenergy crops and plants in unmanaged ecosystems.