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mechanisms that drive weediness evolution, crop stress tolerance, and breeding improvement. You will help analyze genomic, transcriptomic, phenomic, and physiological datasets from corn, snap bean, soybean
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Genome sequencing, transcriptomics Bioinformatic analysis, Computational biology Learning Objectives: Under the guidance of a mentor, you will: Learn about food-safety research focused on bacterial
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dynamics of Salmonella within pasture-based poultry production systems by integrating phenotypic characterization, whole-genome sequencing, and transcriptomic profiling. By advancing the understanding
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, reducing agricultural productivity, grain quality, and food and feed safety. The research will integrate genome sequences, genetic variation, transcriptomic profiles, functional annotations, protein
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, and marker development. Experiences to analyze high through put data sets including short- and long-read genomic and transcriptomic data, and develop or apply related software for data mining. Familiar
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of diverse PRRSV strains causing extreme pathogenesis and disease. Transcriptomics datasets have been generated via bulk and single-cell RNA sequencing from blood and disease-affected tissues and will be
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transcriptomic and metabolomic approaches are used to investigate plant defense responses and support wheat breeding strategies aimed at improving disease resistance and maintaining grain nutritional quality
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to beet curly top virus, Rhizomania disease, and early seedling freezing stress. Develop skills in genomic, transcriptomic, proteomic, and metabolomic techniques to characterize cultivated and wild
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related to root system performance and function. Learn about transcriptomics, qPCR, sequencing, and related laboratory techniques by assisting in genomic and molecular research activities connecting