I obtained a BS degree in botany at Obafemi Awolowo University, a MS degree in genetics at University of Ibadan, and a PhD in genetics at Clemson University. Following postdoctoral positions at Clemson University and NC State University, and an appointment as a Research Assistant Professor, I joined the Department of Entomology and Plant Pathology at the University of Tennessee, Knoxville.

By integrating quantitative genetics and the more recent genomic technologies, my goal is to understand the genetic and molecular mechanisms underlying important agronomic traits, particularly complex diseases in plants. My research interest focuses on understanding how multi-way plant-pathogen-microbe interactions modulate plant diseases and defense response pathways. To achieve this at the systems level, I am developing new methods and bioinformatic tools to aid integration of multi-omic datasets.

My research focuses on dissecting genome structure and function to better understand:

1. Complex plant-pathogen-microbe interactions within the context of agricultural systems. Studies aim to capture naturally occurring metagenomic communities and validate specific interactions with synthetic communities. Pathogens interact with both host plants and host-associated microbial community; hence the study of complex diseases can benefit from modeling these interactions to better model disease incidence and severity. We are currently focusing on Fusarium ear and stalk rot and identifying biocontrol and beneficial microbes that are well adapted to the host.
2. How the host-associated metagenome impacts variation in agronomic traits and partition this variation between host and microbial genetic components. This is aimed to improve accuracy and precision for identifying host genetic factors and genomic predictions.
3. Genetic factors underlying traits and their application for modern crop improvement strategies.

To facilitate translational genomics for crop breeding in a high-throughput and streamlined manner, I am optimizing and developing genomic tools and resources that include:

1. An inexpensive quantitative reduced representation sequencing protocol for genomes and metagenomes. This assay allows for fast turnaround time with generating and computationally processing big data that fits time requirement of breeding programs.
2. Integrating hierarchical shotgun sequencing and femto-scale sequencing for high-quality and haplotype-resolved genome assemblies.
3. Completely automated and user-friendly computational tools/pipelines for empirically based next-generation sequence data quality filtering, variant calling, and metagenomic profiling.

At the core of my teaching philosophy is an enthusiasm to not only perpetuate knowledge and inspire eagerness for learning, but to also teach independent critical listening and thinking. I hope to motivate and nurture the atmosphere of ownership and involvement by providing information in formats that accommodate differences in learning styles.

EPP 633 – Statistical Genetics and Genomics
EPP 504 – Statistical Genetics and Genomics (Lab)