2009 Annual Report
1a.Objectives (from AD-416)
This project will develop a genetic platform to identify useful variation in a high throughput fashion, and then use this platform to identify those genes and alleles that control kernel quality and tolerance to abiotic stresses. Bioinformatic tools will be developed in conjunction with the above to allow for the rapid analysis of plant germplasm diversity. Although the direct application of these approaches will be in maize and biofuel grasses, many of these genetic, statistical, and bioinformatic approaches could have broad implications for both the plant and animal genetics community at large.
Objective 1: Develop statistical, genetic, and genomic approaches for dissecting complex traits in crop plants.
Objective 2: Identify key genes and natural allelic variation for improving abiotic stress tolerance, nitrogen use efficiency, nutritional quality, and biofuel potential for maize and related grasses.
Objective 3: Development of bioinformatic tools to mine and present functional allelic variation.
1b.Approach (from AD-416)
This project will use the natural variation inherent in the maize and biofuel grass genomes for the dissection of complex traits and for the identification of superior alleles. Such discovery is important to the development of improved breeding strategies for maize, the number one production crop in the world. First, this project will develop genetic resources that allow for the rapid dissection of any complex trait to the gene level. These resources will involve the creation of germplasm, the genotyping of this germplasm, and the development of statistical analyses. Using this platform, the project will then dissect the quantitative traits of nutritional quality, nitrogen use, biofuel productivity, and aluminum tolerance. The identification of advantageous alleles could allow for marker-assisted improvement of maize’s nutrition profile for humans and animals, increased processing efficiency, lower fertilizer requirements, and better adaptation to acidic soils. Finally, this project will improve access to diversity data and analysis tools for plant breeders and geneticists. We will facilitate the use of these materials by creating analysis tools, user friendly websites, and breeder decision making tools.
In collaboration with ARS researchers at Raleigh, NC and Columbia, MO, we have characterized the largest set of mapping lines for complex trait dissection in any species (5000 diverse maize inbred lines). We have genotyped them and analyzed the biases in their production. They do a superb job of capturing genetic diversity without bias. The seed for the lines were deposited in the ARS Maize Stock Center last year, and they have been distributed to many leading groups. This genetic resource will also provide the anchor for future molecular diversity characterization in maize.
Control of flowering time is a key for the adaptation of plants to their local environments. We found that maize flowering is controlled by a moderate number of genes (50-100); each gene has a small effect. We found that interactions between genes and interactions with the environment were relatively unimportant for this trait. All together, we were able to very accurately predict flowering time with large numbers of markers.
Hybrid vigor is key to high yield and breeding efforts achieved in maize over the last century. Through studies of diversity in these 5000 lines, we found that the central region of every chromosome (near the centromere) contributes disproportionately to hybrid vigor. This suggests that suppression of recombination is a central part of hybrid vigor. It also suggests important ways that breeders could exploit the substantial genetic variation in central chromosomal regions.
Limited reshuffling of genetic diversity is key to hybrid vigor in corn. Hybrid vigor is key to high yield and breeding efforts achieved in maize over the last century. The researchers discovered that limited reshuffling of genetic diversity in certain regions of the genome is key to hybrid vigor. Because hybrid vigor is used in virtually all commercial maize and many other crops, this discovery suggests much more efficient approaches for crop improvement in the future.
Flowering time in maize is controlled by numerous genes. Appropriate flowering time is key to adaptation of maize to its local environment, and it is the main impediment to moving maize diversity between the tropical and temperate regions. Through extensive analysis of 5000 diverse varieties of maize, researchers discovered that maize flowering variation was controlled by numerous genes each with a small predictable effect. This knowledge will help permit the design of maize varieties for specific environments around the country and the world. Additionally, this will facilitate that transfer of genetic diversity from tropical maize to maize adapted to the US and vice versa.
Released Genetic Resources for Mining Maize Diversity. Maize is the most diverse crop in the world, but much of that useful genetic variation is found in maize unadapted to US agriculture. This project is working to unlock the molecular basis of this genetic variation and make it more accessible to agriculture. We have released and genetically characterized the largest set of mapping lines for complex trait dissection in any species. 5000 diverse maize inbred lines have been produced. Seed for the vast majority of lines were deposited to the ARS Maize Stock Center. This genetic resource is becoming anchor of research for dozens of research groups that determine the basis numerous agronomically important maize traits.
Buckler Iv, E.S., Esch, E., Szymaniak, J., Yates, H., Wojciech, P. 2007. Using Crossover Breakpoints in Recombinant Inbred Lines to Identify Quantitative Trait Loci Controlling the Global Recombination Frequency. Genetics. 177:1851-1858.
Buckler Iv, E.S., Hamblin, M.T., Warburton, M.L. 2008. Empirical Comparison of Simple Sequence Repeats and Single Nucleotide Polymorphisms in Assessment of Maize Diversity and Relatedness. PLoS One. 2(12):e1367.
Buckler Iv, E.S., Weber, A.L., Briggs, W.H., Rucker, J., Baltazar, B.M., Sanchez-Gonzalez, J.D., Feng, P., Doebley, J.F. 2008. The Genetic Architecture of Complex Traits in Teosinte (Zea mays ssp.parviglumis): New Evidence from Association Mapping. Genetics. 180(2):1221-1232.
Buckler Iv, E.S., Yu, J., Zhang, Z., Tabanao, D.A., Gail, P., Kresovich, S., Todhunter, R.J. 2009. Simulation appraisal of the adequacy of numbers of background markers for relationship estimation in association mapping. The Plant Genome. 2:63-77.
Buckler Iv, E.S., Gore, M. 2008. An Arabidopsis haplotype map takes root. Nature Genetics.39:1056-1057.
Buckler Iv, E.S., Gore, M., Zhu, C., Yu, J. 2009. Status and Prospects of Association Mapping in Plants. The Plant Genome. 1(1):5-20.
Canaran, P., Buckler Iv, E.S., Glaubitz, J., Stein, L., Sun, Q., Zhao, W., Ware, D. 2009. Panzea: An Update on New Content and Features. Nucleic Acids Research. 36:D1041-D1043.
Stich, B., Mohring, J., Piepho, H., Heckenberger, M., Buckler Iv, E.S., Melchinger, A.E. 2008. Comparison of Mixed-Model Approaches for Association Mapping. Genetics. 178(3):1748-1754.
Bernardo, A.N., Bradbury, P., Ma, H., Hu, S., Bowden, R.L., Buckler Iv, E.S., Bai, G. 2009. Discovery and mapping of single feature polymorphisms in wheat using affymetrix arrays. Biomed Central (BMC) Genomics. 10:251.
Mcmullen, M.D., Kresovich, S., Sanchez-Villeda, H., Bradbury, P., Li, H., Sun, Q., Flint Garcia, S.A., Thornsberry, J., Acharya, C., Bottoms, C., Brown, P., Browne, C.J., Eller, M.S., Guill, K.E., Harjes, C., Kroon, D., Lepak, N.K., Mitchell, S., Peterson, B.E., Pressoir, G., Romero, S.M., Oropeza Rosas, M., Salvo, S.A., Yates, H., Hanson, M., Jones, E., Smith, S., Glaubitz, J., Goodman, M., Ware, D., Holland, J.B., Buckler Iv, E.S. 2009. Genetic Properties of the Maize Nested Association Mapping Population. Science. 325:737-740.
Buckler Iv, E.S., Holland, J.B., Mcmullen, M.D., Kresovich, S., Acharya, C., Bradbury, P., Brown, P., Browne, C.J., Eller, M.S., Ersoz, E., Flint Garcia, S.A., Garcia, A., Glaubitz, J.C., Goodman, M., Haries, C., Guill, K.E., Kroon, D., Larsson, S., Lepak, N.K., Li, H., Mitchell, S.E., Pressoir, G., Peiffer, J., Oropeza Rosas, M., Rocheford, T., Romay, C., Romero, S., Salvo, S.A., Sanchez Villeda, H., Sun, Q., Tian, F., Upadyayula, N., Ware, D., Yates, H., Yu, J., Zhang, Z. 2009. The Genetic Architecture of Maize Flowering Time. Science. 325(5941):714-718.