Closing a gap
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“Even with 15 years worth of genomic research, a gap still remains between research discoveries and their application to crop improvement,” says Bill Beavis, George F. Sprague Endowed Chair and professor in the Department of Agronomy.
“When plant breeders and agronomists have a problem in the field, they do not use the results of genomics to address the problem,” says Beavis, a leading expert in bioinformatics who joined Iowa State in August, and who aims to put genomic information into the hands of those who will use it.
Beavis envisions diagnostics kits that provide growers, breeders and agronomists real-time decisions support—biomarkers that might show disease or chemical drift, for example. They'll grind up a leaf, do a chemical test and get a read on patterns on the spot. A handheld portable device will send data to a database for a diagnostics match, and the database will return information in a decision support format.
“For example, sometimes plants are sick but they don't show symptoms, yet they're spreading the disease to their neighbors,” Beavis said.
The uses for diagnostic kits will be broad. For instance, a breeder may obtain DNA-based information on plant characteristics that are not observable every year.
Beavis received his PhD in plant breeding at Iowa State. He gained extensive experience in the application of statistical genetic methods during 12 years at Pioneer Hi-Bred International, Inc. (1986-1998).
For the past 10 years, Beavis served as chief scientific officer at the National Center for Genome Resources, in Santa Fe, New Mexico, where he was the principal investigator for a variety of bioinformatics projects, including the Arabidopsis Information Resource (TAIR) and the Legume Information System (LIS). There he also identified a set of biomarkers that can be used in a handheld diagnostic kit by clinicians—a simple blood test with 45 markers that predict sepsis in patients.
Beavis is credited with recognizing the statistical anomaly whereby the genetic effects of quantitative trait loci (QTL) are overestimated when searching genomes for genes associated with desired phenotypic traits--“the Beavis Effect.”
