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Department of Biology

Gene Discovery for Improved Iron Nutrition in Maize

The micronutrient iron (Fe) is essential for photosynthesis, respiration, and many other processes, but Fe is only sparingly soluble in aqueous solution, making adequate acquisition by plants a serious challenge. Fe is a limiting factor for plant growth on approximately 30% of the world's arable lands. Furthermore, iron is highly reactive and, if over-accumulated, can cause cellular damage.

Harnessing Chemical Ecology to Address Agricultural Pest and Pollinator Priorities

Many bee pollinators are in decline, and exposure to diseases has been implicated as one of the potential causes Novel work in my lab found that consuming sunflower pollen dramatically reduced bumble bee infection by a gut pathogen. These are exciting results, but at this point we have established this effect only in the lab, with a single sunflower variety, one bumble bee species, and one pathogen species.

Programmed Cell Death in Grass Flower Development and Evolution Leveraging Basic Research into Rational Crop Design

This proposal is about programmed cell death and sex determination in maize and the grass family. Programmed cell death is best defined as genetically encoded, actively controlled cellular suicide. Programmed cell death is of fundamental importance in plant development. For example, xylem cells undergo programmed cell death and create an interconnected network of hollow tubes essential for water transport.

Genome-wide Association Mapping of Bio-fuel Traits in the Energy Crop Model, Brachypodium Distachyon

Here, we propose to use a model grass species, Brachypodium distachyon, to initiate discoveries that can help realize the potential of plant-based renewable energy sources. With the research proposed, we will be discovering the extent of natural variation in traits relevant to biofuel production and identifying candidate loci controlling these variable traits. Our use of natural diversity to identify phenotypes that lead to greater fuel efficiency, and to ultimately identify genes underlying desirable feedstock traits, will aid in the development of optimal plant feedstocks for biofuel.

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