2010 Annual Report
1a.Objectives (from AD-416)
Our overall goal is to determine the genetic foundation for morphological and compositional characteristics that enhance agronomic performance and quality of maize grain and stover. We will also develop new tools for measuring economically important traits in maize. For the next five-year research cycle we will:
Objective 1: Identify key morphological phenotypes and the underlying genes and/or genetic systems that have contributed to improvement in grain yield and other important agronomic phenotypes in maize.
Objective 2: Develop new tools for evaluating and identifying maize varieties with superior properties for bioenergy production.
Objective 3: Identify key physiological and biochemical phenotypes and the underlying genetic systems that have contributed to improvement in methionine content and bioenergy potential.
1b.Approach (from AD-416)
Objective 1: We will map genomic regions and attempt to identify candidate genes for morphological phenotypes that may have changed in response to selection for agronomic performance in the Iowa Stiff Stalk Synthetic population. We will focus on three morphological phenotypes, silking-anthesis interval, leaf angle, and number of ears per plant. We will determine the magnitude of selection response for these traits in Iowa Stiff Stalk Synthetic population and determine if any of these are correlated to agronomic traits in the base population. We will then use advanced cycles of selection and the base population to generate a genetic mapping experiment to determine how many regions and what magnitude of effects those regions have for the morphological traits. We will use all of the information collected to determine if response to selection for agronomic traits can be explained by indirect response for morphological characters.
Objective 2: One method of production of biofuel from plant material involves fermentation, which is dependant on the production of sugars from the plant material. We will develop methods for screening varieties for their ability to produce sugars in small scale processes that mimic current methods being used for production of ethanol. Sugars will be quantified using bacterial biosensor strains we will develop using bacterial genes known to respond to sugar levels.
Objective 3: We will characterize the genetic mechanism controlling production of methionine by biochemical analysis of populations selected for high and low methionine. In addition, we will determine if different genetic mechanisms controlling methionine levels are complimentary by combining them genetically and determining the methionine levels in the different genetic combinations.
We made significant progress for Objective 3. Preliminary analysis of adaptation to high plant density in Iowa Stiff Stalk Synthetic populations suggests a recessive inheritance pattern for some key phenotypes that are indicative of adaptation to high plant density. If the recessive-inheritance hypothesis holds, this knowledge will lead to more effective breeding programs that will improve the performance of unadapted germplasm at high plant density. For Objective 2, we analyzed phenolic compounds that influence ethanol production as well as nutritional quality and resistance to insects in grain tissues of several maize genotypes. Related to this objective, we analyzed stover from maize accessions developed by the ARS Germplasm Enhancement of Maize Project and experimental commercial varieties.
Characterized agronomic and starch traits of opaque-2 maize. Opaque-2 maize has long been known to have superior grain nutritional value, however its starch is not fully uncharacterized. Furthermore, corn-belt adapted elite opaqe-2 varieties are lacking. We characterized agronomic traits of improved opaque-2 maize adapted to Iowa and starch traits of several opaque-2 varieties. We learned opaque-2 maize has unique starch traits that may make it a superior feedstock for biofuel use.
We identified optimal analytical approaches to analyzing multi-environment maize-yield trials with variable data quality across environments. Multi-environment trials are very costly to the seed industry so choosing the best approach to make maximal use of expensive data is a critical economic decision. We provided straightforward guidelines for choosing the best approach to select superior lines from these studies based on analysis of 12 years of yield-trial data.
Identified germplasm with improved amino acid balance. The nutritional quality of corn is limited by its poor amino acid balance. Germplasm was evaluated and varieties with improved amino acid balance were identified. This germplasm will be valuable to maize breeders interested in improving amino acid balance, facilitating development of maize with better feed quality.
Hasjim, J., Srichuwong, S., Scott, M.P., Jane, J. 2009. Kernel Composition, Starch Structure, and Enzyme Digestibility of Opaque-2 Maize and Quality Protein Maize. Journal of Agricultural and Food Chemistry. 57:2049-2055.
Scott, M.P., Peterson, J.M., Hallauer, A.R. 2010. Evaluation of Combining Ability and Grain Quality of Quality Protein Maize Derived from U.S. Public Inbred Lines. Maydica. 54:449-456.
Flint Garcia, S.A., Bodnar, A., Scott, M.P. 2009. Wide Variability in Seed Characteristics, Kernel Quality, and Zein Profiles Among Diverse Maize Inbreds, Landraces, and Teosinte. Theoretical and Applied Genetics. 119:1129-1142.
So, Y., Edwards, J.W. 2009. A Comparison of Mixed-Model Analyses of the Iowa Crop Performance Test for Corn. Crop Science. 49:1593-1601.
Gutierrez-Rojas, A., Betran, J., Scott, M.P., Atta, H., Menz, M. 2010. Quantitative Trait Loci for Endosperm Modification and Amino Acid Contents in Quality Protein Maize. Crop Science. 50:870-879.