Eric H Lyons

Eric H Lyons

Associate Professor, Plant Science
Associate Professor, Agricultural-Biosystems Engineering
Advisor, CALS' Office of the Assoc Dean - Research for Cyber Initiatives in Agricultural / Life - Vet Science
Associate Professor, Genetics - GIDP
Associate Professor, BIO5 Institute
Primary Department
Department Affiliations
Contact
(520) 626-5070

Research Interest

Eric Lyons, PhD is an assistant professor at the University of Arizona School of Plant Sciences. Dr. Lyons is internationally known for his work in understanding the evolution, structure, and dynamics of genomes. Core to his research activities is the development of software systems for managing and analyzing genomic data and cyberinfrastructure for the life sciences.Dr. Lyons has published over 30 original research papers and 5 book chapters, many in collaboration with investigators from around the world. He is a frequent presenter at national and international meetings, and has been invited to teach workshops on the analysis of genomic data to plant, vertebrate, invertebrate, microbe, and health researchers.Prior to joining the faculty in the School of Plant Sciences, Dr. Lyons worked with the iPlant Collaborative developing cyberinfrastructure, and managing its scientific activities. In addition, he spent five years working in industry at biotech, pharmaceutical, and software companies. Dr. Lyons’ core software system for managing and analyzing genomic data is called CoGe, and is available for use at http://genomevolution.org

Publications

Haug-Baltzell, A., Jarvis, E. D., McCarthy, F. M., & Lyons, E. (2015). Identification of dopamine receptors across the extant avian family tree and analysis with other clades uncovers a polyploid expansion among vertebrates. Frontiers in neuroscience, 9.
Devisetty, U. K., Kennedy, K., Sarando, P., Merchant, N., & Lyons, E. (2016). Bringing your tools to CyVerse Discovery Environment using Docker. F1000Research, 5.
Joyce, B. L., Haug-Baltzell, A. K., Hulvey, J. P., McCarthy, F., Devisetty, U. K., & Lyons, E. (2017). Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms. Journal of visualized experiments: JoVE.
Hofberger, J. A., Lyons, E., Edger, P. P., Pires, J. C., & Schranz, M. E. (2013). Whole Genome and Tandem Duplicate Retention Facilitated Glucosinolate Pathway Diversification in the Mustard Family. Genome biology and evolution, 5(11), 2155--2173.
Lyons, E., Freeling, M., Kustu, S., & Inwood, W. (2011). Using genomic sequencing for classical genetics in E. coli K12. PloS one, 6(2), e16717.

We here develop computational methods to facilitate use of 454 whole genome shotgun sequencing to identify mutations in Escherichia coli K12. We had Roche sequence eight related strains derived as spontaneous mutants in a background without a whole genome sequence. They provided difference tables based on assembling each genome to reference strain E. coli MG1655 (NC_000913). Due to the evolutionary distance to MG1655, these contained a large number of both false negatives and positives. By manual analysis of the dataset, we detected all the known mutations (24 at nine locations) and identified and genetically confirmed new mutations necessary and sufficient for the phenotypes we had selected in four strains. We then had Roche assemble contigs de novo, which we further assembled to full-length pseudomolecules based on synteny with MG1655. This hybrid method facilitated detection of insertion mutations and allowed annotation from MG1655. After removing one genome with less than the optimal 20- to 30-fold sequence coverage, we identified 544 putative polymorphisms that included all of the known and selected mutations apart from insertions. Finally, we detected seven new mutations in a total of only 41 candidates by comparing single genomes to composite data for the remaining six and using a ranking system to penalize homopolymer sequencing and misassembly errors. An additional benefit of the analysis is a table of differences between MG1655 and a physiologically robust E. coli wild-type strain NCM3722. Both projects were greatly facilitated by use of comparative genomics tools in the CoGe software package (http://genomevolution.org/).