I joined the Entomology and Plant Pathology Department in January of 2014. My research program is focused on solving the bioinformatic challenges of building and integrating large plant genomic datasets, especially those from hardwood trees. I also specialize in comparative genomics, particularly transferring and applying the in-depth knowledge base available for commodity crop plants to understanding the evolution and genomic structure of woody tree species. My group builds and maintains the Hardwood Genomics Database, which provides tools for scientists to query, download and explore genomic datasets from forest trees. The website is built on Tripal, an open-source, custom, flexible, modular software package for genetic and genomic database construction, co-developed by the Staton lab and with a number of other plant genomic database groups.

My position also encompasses bioinformatics support for UTIA research programs. I am availble to consult or participate on projects with faculty, staff and students with genomic or transcriptomic data sets. Please email if you are interested in learning more about these collaborative opportunities.

I work with a variety of DNA and RNA high throughput sequencing datasets derived from plant species. I focus on using computational tools to extract the genetic and molecular underpinnings of plant phenotypes and their response to stress. I have a broad range of collaborators and interests with new datasets arriving frequently. Currently, I am working on

• Scaffolding and annotation of a reference genome sequence for Castanaea mollissima (Chinese Chestnut) and analysis of structural and functional genome evolution across wood rosid species, including peach, oak, walnut and chestnut.
• Responses of different Vaccinium species to neutral and acid soil pH, using transcriptome profiling of roots from blueberry plants grown in varying pH exposures
• Investigation of various bioinformatic tools and pipelines for processing polyploid plant RNASeq data sets
• Genetic control of dormancy, including the transition from endodormancy to ecodormancy and the loci controlling the heritability of low chill or high chill phenotypes, using transcriptome profiling and genetic associations in apricot and peach
• Soybean rhizosphere microbe interactions – using 16S and ITS sequencing to profile how soybeans structure their root microbiomes and examining how root exudates, abiotic stress and agricultural inputs such as fungicide perturb this system

Beyond generating the data for hardwood tree and other plant genomes, I also build public data dissemination portals. I build and maintain the hardwood genomics web portal, which provides tools for scientists to query, download and explore genomic datasets from many hardwood tree species. New funding has recently been secured to expand the site to encompass more species and data types, to focus on phenotypic and germplasm data, and to tag all data with ontologies, thereby increasing the utility of the existing sequence and mapping data sets for breeders and biologists.

TreeSnap is a mobile app that enables interested citizens to report the location and health information about trees of interest to scientists. From urban areas to the forest, we encourage the app users to identify trees of interest (such as American chestnut, native ash trees, native hemlock trees) and to take photosand answer questions about the tree’s health.  The app is available on iOS and Android, and members of the public are being trained in the app through in-person educational events as well as through online platforms. There is also a TreeSnap website for users to explore maps and tree reports from around the world. The web also offers a sophisticated set of online tools for scientists to filter, sort and track the trees reported by citizens, increasing the utility of the data provided and helping scientists to use the data in their research programs.

Value Proposition:The discipline of bioinformatics is one of the most effective and promising tools for generating biological research discoveries, but it requires robust training in order to apply the principles correctly.This course will provide students with bioinformatic skills for processing and understanding of large datasets such as genome and transcriptome sequences, gene and protein expression measurements, and heritable genomic variations. These skills will enhance student’s research efficiency and scope and, long-term, will position students to be more effective and competitive in the technology-driven biomedical and agricultural science industries.

EPP 622 Bioinformatic Applications

This course focuses on fundamental bioinformatics concepts, principles and techniques with a focus on the application of bioinformatics to problems in agriculture. The laboratory practical is taught within a LINUX computational environment where students will gain basic skills in bash and python scripting and construct open-source software workflows to analyze genomic data.