2011 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 on all of our objectives. For objective one data collected over the course of the year allowed us to further clarify the physiological mechanisms by which corn responds to high plant density. Objective two was completed by characterization of mutants involved in lignin biosynthesis in maize and additional work was carried out that resulted in identification of germplasm suitable for lignocellulosic ethanol production. Objective three was advanced by evaluation of maize with high methionine content that will facilitate development of maize for poultry feed. Additional work related to this objective was carried out to understand the genetic control of grain hardness, an important trait for feed and ethanol production.
New breeding strategy developed for improving corn yields. Selecting corn that yields well while being grown in high plant densities has been largely responsible for the advances in corn production. Understanding traits that allow plants to grow effectively in high density situations will facilitate rapid improvement of corn hybrids. ARS scientists in Ames, Iowa, characterized key traits, such as leaf angle and anthesis-silking interval, that allow plants to grow efficiently at high plant density. Based on these results, the scientists developed an improved breeding strategy. This strategy provides a new tool for plant breeders to use on future projects related to improving yield, resulting in higher yielding corn for producers.
Edwards, J.W. 2010. Testcross Response to Four Cycles of Half-sib and S2 Recurrent Selection in the BS13 Maize (Zea mays L.) Population. Crop Science. 50:1840-1847.
Hoffman, P.C., Esser, N.M., Shaver, R.D., Coblentz, W.K., Scott, M.P., Bodnar, A.L., Schmidt, R.J., Charley, B.C. 2011. Influence of ensiling time and inoculation on alteration of the starch-protein matrix in high-moisture corn. Journal of Dairy Science. 94:2465-2474.
Ali, F., Scott, M.P., Bakht, J., Chen, Y., Lubberstedt, T. 2010. Identification of novel brown-midrib genes in maize by tests of allelism. Plant Breeding. 129:724-726.
Paraman, I., Moeller, L., Scott, M.P., Wang, K., Glatz, C., Johnson, L. 2010. Utilizing protein-lean co-products from corn containing recombinant pharmaceutical proteins for ethanol production. Journal of Agricultural and Food Chemistry. 58(19):10419-10425.
So, Y., Edwards, J.W. 2011. Predictive ability assessment of linear mixed models in multienvironment trials in corn (Zea mays L). Crop Science. 51:542-552.
Yi, G., Moran Lauter, A., Scott, M.P., Becraft, P.W. 2011. The thick aleurone1 mutant defines a negative regulation of maize aleurone fate that functions downstream of dek1. Development. DOI: 10.1104/pp.111.177725.