James Schnable, assistant professor of agronomy and horticulture, co-authored a study published in the Aug. 18 issue of the journal Science. His research focuses on methods to combine genomic data from different grain crops — like corn, sorghum, and millet — to make it easier to figure out the function of genes in individual crops.
After assembling an atlas of messenger RNAs and proteins that dictate gene expression and regulation in corn, the study found that computational networks, designed to predict gene relations and functions, differ substantially when accounting for only RNAs or proteins. The authors further concluded that integrating RNA- and protein-based data can greatly improve the predictive power of gene regulation networks.
“My particular contribution to this science paper was the discovery that, using data from both corn and sorghum, we could accurately predict which genes in corn would produce RNA and protein, and which would produce only RNA, something we couldn't do as accurately using just data from corn,” Schnable said.
Schnable conducted the study with researchers from the University of California, San Diego; Iowa State University; the Salk Institute for Biological Studies; and the Howard Hughes Medical Institute. For more information on the study, see the journal publication in AAAS Science Magazine at http://science.sciencemag.org/content/353/6301/814.
See also Nebraska Today – Achievements at http://news.unl.edu/newsrooms/today/article/achievements-honors-awards-publications-for-aug-19.
More details at: http://agronomy.unl.edu/news/schnable-co-authors-study-gene-regulation-networks