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CAREER: Integrating Forward and Reverse Genetic Approaches to Identify the Genomic Basis of Plant-Microbiome Interactions in Legumes

NSF

open

About This Grant

Plants grow in close co-association with an incredible diversity and abundance of microorganisms, known as the microbiome. Advances in sequencing technology over the past 15 years have allowed for the unprecedented investigation of microbiomes giving rise to an entirely new field of research. It is now clear that nearly every conceivable plant interaction with the environment is mediated, to some extent, through interactions with the microbiome. For this reason, there is profound scientific interest and financial investment aimed at harnessing plant-microbiomes to improve agriculture to achieve greater food security and environmental sustainability. However, these efforts are severely limited as the genomic mechanisms that control plant-microbiome interactions are largely unknown – information that is essential for enabling plant breeding to enhance agricultural microbiomes. This project aims to fill this knowledge gap by identifying the genetic mechanisms that control plant-microbiome interactions in the model legume Medicago truncatula. The legume, or bean, family is the second most agriculturally important crop family. This project will leverage the extensive resources available in Medicago to map the genetic basis of microbiome variation and validate the functional significance of candidate genes that are identified. Additionally, this work will examine connections between known plant-microbe symbiosis genes and interactions with the broader microbiome. This project will also provide research training for high school science teachers from Chicago Public Schools and develop novel teaching modules based on this research that will be implemented in the classroom and broadly disseminated to the science education community. Plant-microbiome interactions play key roles in environmental stress tolerance; however, the mechanisms that control these interactions remain poorly understood. While much remains unknown about the genetic underpinnings of the overall plant microbiome, there is a considerable body of literature from decades of research interrogating the mechanisms controlling symbiotic interactions with arbuscular mycorrhizal fungi (AMF) and between legumes and nitrogen-fixing bacteria (rhizobia). Several of the common AMF and rhizobial symbiosis genes are conserved across plant evolution, even in non-symbiotic species, which has raised the hypothesis that symbiosis genes may also play a role in controlling interactions with the broader microbiome. This project integrates forward and reverse genetic approaches to investigate this hypothesis and fill key knowledge gaps regarding genomic mechanisms that shape the microbiome of legumes. This work leverages resources available for the model legume Medicago by conducting genome-wide association studies of microbiome interactions and examination of the impacts of knock-out mutants for AMF and rhizobial symbiosis genes on the microbiome. This work will greatly advance our understanding of plant microbiome genetics and will serve as a guide for future plant breeding efforts to improve agriculture. Additionally, training high school science teachers and developing novel curricular materials are a major goal of this project. Modern science education standards emphasize teaching the practice of doing science though inquiry-based pedagogical approaches. Achieving this can be challenging for teachers without having had experience conducting research. Moreover, new teaching modules are needed that are aligned with modern standards. Project outcomes will be disseminated broadly through publications and long-term, through public data repositories. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Focus Areas

education

Eligibility

universitynonprofitsmall business

How to Apply

Funding Range

Up to $603K

Deadline

2030-02-28

Complexity
Medium
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