Source: IOWA STATE UNIVERSITY submitted to
MARKER ASSISTED BREEDING AND LIMITS TO GENETIC GAIN
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0217239
Grant No.
(N/A)
Project No.
IOW03614
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Jan 1, 2009
Project End Date
Dec 31, 2014
Grant Year
(N/A)
Project Director
Beavis, WI.
Recipient Organization
IOWA STATE UNIVERSITY
2229 Lincoln Way
AMES,IA 50011
Performing Department
Agronomy
Non Technical Summary
Marker Assisted Breeding (MAB) is now routinely applied to traits of corn by commercial plant breeders. We intend to apply MAB to improve Nitrogen Use Efficiency (NUE) and biomass conversion in corn that is adapted to North America Production environments. These desirable traits are not found in North American maize lines, but can be found in tropical maize. However, the desirable traits are tightly associated with undesirable traits, such as failure to flower and produce grain when grown in North America. So, in order to identify the genes responsible for these desirable traits, the tropical maize needs to be able to flower under long day length, so that it can be evaluated in North America. Therefore we will begin by identifying the photoperiod response genes and select for them in the tropical lines using MAB. As a result we will be able to evaluate the tropical lines for their useful genes, including NUE and biomass conversion, in North America. Of concern, for any artificial selection program, is the potential to exhaust useful genetic variability. The result is an inability to improve the crop through breeding because the breeding lines will reach a sub-optimal plateau from the application of too intensive selection. MAB provides both the promise of faster response to selection and more rapid erosion of genetic diversity. To ameliorate this potential problem we intend to use the tools of molecular biology to characterize genomic signatures of breeding populations that are in jeopardy of reaching sub-optimal limits and develop breeding strategies to enable migration of new genetics into the breeding lines without sacrificing the gains made by previous generations of plant breeders.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2011510104010%
2011510108015%
2021510104010%
2031510108115%
2031510108015%
2041510108015%
2062420108010%
9017310209010%
Goals / Objectives
Objective a. We will identify functional alleles and develop functional markers for nitrogen use efficiency (NUE), biomass conversion and adaptation to North American Production systems through Linkage and Linkage Disequilibrium Mapping approaches. Objective b. We will use the information to estimate breeding values and determine optimal Marker Assisted Breeding (MAB) strategies to deploy these traits in North American maize germplasm. Objective c. Because artificial selection has the potential to limit the genetic gain to sub-optimal plateaus, we will characterize genomes of elite maize breeding populations relative to the corn-belt dents and assess the role of genome structure on limiting response to selection. Objective d. Because maize has yet to show evidence of reaching a plateau in artificially selected breeding populations, we will investigate the potential for a model system to recapitulate maize breeding and learn whether theory needs to be altered for the plastic maize genome.
Project Methods
Objective a: Identify functional alleles responsible for agronomic traits in maize. To meet this objective we will develop both experimental and statistical methods. Our experimental approaches will be based on both linkage and linkage disequilibrium mapping methods. Our statistical approach will concentrate on novel methods to analyze data from combined linkage and linkage disequilibrium mapping. Objective b. Optimize Marker Assisted Breeding (MAB) strategies. Existing methods for predicting breeding values (BVs) are based on discrete experiments in which a single sample is used to predict BVs. We will develop an in silico analysis paradigm in which predicted BVs are updated continuously with additional samples. We will pursue adaptive designs in which BVs are continuously updated with each breeding generation, providing both posterior inferences about the value of genes in generation g, as well as prior information to subsequent breeding generations. We will also investigate the potential of operations research to find optimal MAB strategies. Objective c: In order to evaluate the role of selection, drift, and recombination in shaping the genomes of elite adapted maize breeding lines we will need to characterize genomes of elite maize breeding populations relative to their ancestral breeding populations. This will require saturation of the genome with informative sequence based markers; i.e., pairs of adjacent markers need to be in LD with each other in the reference breeding population. To accomplish this, we will develop a reduced genome representation technique and apply it to elite adapted maize breeding lines as well as the corn belt dent population from which they were derived. Objective d. Investigate potential of model systems to understand limits of selection in maize. In order to provide feedback for refining simulation models, to investigate MAB issues and limits to selection, we will investigate the potential of a model plant system to recapitulate adaptation and artificial selection in maize. Such a system will need the following characteristics: rapid life cycle (seed to seed in 4-6 weeks), flexible reproductive biology (ability to self and outcross), ability to grow large numbers of individuals in small areas (greenhouse flats), genetically diverse germplasm collection, sequenced genome or closely related to a species with a sequenced genome, evidence that the genome has plasticity similar to maize, availability of a high throughput genotyping chip and recognition of the species as a model or reference species.

Progress 01/01/09 to 12/31/14

Outputs
Target Audience: Quantitative geneticists, plant breeders, plant geneticists, computational biologists employed in the commercial, private non-profit and academic sectors. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? We provided education to 16 PhD students and four MS students in plant breeding, genetics and computational biology. Eight of the PhD students have graduated and are employed at academic, private non-profit and commercial research institutes. Two of the MS students have completed their theses and are employed in the commercial sector. We also designed, developed and delivered an online masters program in plant breeding. It has experienced steady growth with 55 students currently enrolled. Three students have completed the MS online program and have graduated. How have the results been disseminated to communities of interest? Over 55 peer-reviewed publications were produced during the execution of this project. Also, faculty, grad students and post docs have disseminated the results through ~ 70 posters and invited presentations. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Overall Impact: During the execution of this project we developed and evaluated novel resources for genetic improvement of maize. These resources include novel statistical methods for gene discovery in breeding populations, development of novel germplasm for discovery of genetic loci, discovery of genes responsible for Nitrogen Use Efficiency (NUE) and maize kernel development, and novel modeling approaches that assure optimal (efficient and effective) genetic improvement in plant breeding systems. While we used maize to motivate the research, the methods and modeling approaches are generally applicable to any crop genetic improvement program. We demonstrated the general utility of these methods by extending the methods and modeling to any arbitrary genetic architecture in simulated systems as well as soybean breeding populations. Objective a: We developed novel linkage analyses of functional (continuously varying) traits such as biomass accumulation and nitrogen metabolism. Linkage analyses of functional traits will enable identification of genes responsible for signaling phase changes in growth and development. We evaluated power, precision and accuracy of novel linkage disequilibrium methods for populations of multiple families consisting of progeny derived from multiple breeding crosses. These methods will allow the breeders to identify genes in populations that are routinely developed in breeding programs rather than artificial experimental populations. In the early years of the project we identified genetic resources to study NUE. We determined that NUE is determined by Nitrogen metabolism and root architecture. Using the statistical methods and the genetic resources, we identified regulatory genes (functional alleles and markers), primarily members of the ramosa gene family that affect growth, development and N metabolism and we identified specific functional alleles at the RTCN, RTH3, RUM1 AND RUL1 loci that affect root architecture. Objective b: Marker assisted breeding (MAB) has been based on development of two approaches: 1. Genomic prediction (GP) is a 'black box' statistical method that does not identify specific genes, rather whole genomes with predicted net favorable effects; 2. Identified favorable and complementary genes are 'stacked' together through planned breeding crosses. At least a dozen parametric GP methods have been developed. All assume the genetic architecture of the traits of interest are additive. We compared the methods and found that as long as the genetic architecture is additive, all parametric GP methods have similar prediction accuracies. We also found that if the genetic architecture of a trait consists of non-additive factors (dominance, epistasis, genotype by environment interactions), then prediction accuracies are poor (close to zero or negative outcomes). Because the second approach to MAB depends on power, precision and accuracy in identification of genes that will be 'stacked', we demonstrated that it is easily adapted to the underlying genetic architecture. We developed the second approach to MAB using the tools of operations research and introduced the concept that plant breeding could be treated as an engineering discipline with predictable outcomes that can be optimized. Most researchers have stated that the first approach is more efficient when there are many (>20) genes and the second is more efficient when the trait involves few (<10) genes. In the future we will assess this dogma using objective criteria. Objective c: Due to a lack of successful extramural funding we did not characterize genomes of elite maize breeding populations relative to the corn-belt dents and assess the role of genome structure on limiting response to selection. These issues are being addressed by maize sequencing projects involving other teams. We did, however assess genomic structure in soybean. We found that the genome could be divided into four distinct groups based on GC content of Long Homogeneous Genomic Regions (LHGRs). Further, we found that all known active genes (genes that respond to selection) are located in one of these categories of LHGRs. Further, this category of LHGRs is located near the ends of soybean chromosomes. The implications of this discovery on plant breeding programs is not obvious. Objective d: We evaluated several potential model systems for plant breeding based on criteria of short life cycles (<8 weeks to enable development and evaluation of at least six generations per year), ease of crossing, self compatibility, genetic diversity among lines with rapid life cycles, a sequenced reference genome, rapid and inexpensive genotyping platform. Among the four candidate species, Brassica rapa, Mimulus guttatus, Arabidopsis thaliana, Brachypodium distachyon, none meet all criteria. The technical and genotypic resources are well developed in A thaliana, however crossing among ecotypes is extremely difficult and labor intensive. On the other hand, while crossing is quite easy in B rapa and M guttatus, technical and genotypic resources are not well developed and both show evidence of self-incompatibility. B distachyon is difficult to cross and has limited technical and genotypic resources. We conclude that there are no model systems for evaluating plant breeding systems and leave it to another group to develop such a system.

Publications

  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Li, M., X. Liu, P. Bradbury, J. Yu, Y.-M. Zhang, R.J. Todhunter, E.S. Buckler, and Z. Zhang. 2014. Enrichment of statistical power for genome-wide association studies. BMC Biology 12:73.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Wang, M.l. M. Cole, B. Tonnis, D. Pinnow, Z. Xin, J. Davis, Y.-C. Hung, J. Yu, G.A. Pederson, G. Eggleston. 2014. Comparison of stem damage and carbohydrate composition in the stem juice between sugarcane and sweet sorghum harvested before and after late fall frost. Journal of Sustainable Bioenergy Systems 4:161-174.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Zhang, D., R.L. Bowden, J. Yu, B.F. Carver, G. Bai. 2014. Association analysis of stem rust resistance in U.S. winter wheat. PLoS One: 9:e103747.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Thompson, A.M., J.E. Crants, P.S. Schnable, J. Yu, M.C.P. Timmermans, N.M. Springer, M.J. Scanlon, G.J. Muehlbauer. 2014. Genetic control of maize shoot apical meristem Architecture G3: Genes, Genomes, Genetics 114:011940.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Li, L., S.R. Eichten, R. Shimizu, K. Petsch, C.T. Yeh, W. Wu, A.M. Chettoor, S.A. Givan, R.A. Cole, J.E. Fowler, M.M.S. Evans, M.J. Scanlon, J. Yu, P.S. Schnable, M.C.P. Timmermans, N.M. Springer, G.J. Muehlbauer. 2014. Genome-wide discovery and characterization of maize long non-coding RNAs. Genome Biology 15:R40.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Narayanan, S., R.M. Aiken, P.V. Prasad, Z. Xin, G. Paul, and J. Yu. 2014. A simple quantitative model to predict leaf area index in sorghum. Agronomy Journal 106:219-226.
  • Type: Book Chapters Status: Published Year Published: 2014 Citation: Sukumaran, S., and J. Yu. 2014. Association mapping of genetic resources: Achievements and future perspectives. In: R. Tuberosa et al. (ed.) Genomics of Plant Genetic Resources, Vol. 1, 207-235.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: L�bberstedt, T. (2014) Bioenergie aus Maisrestpflanzen  Mit Pyrolyse aus trockener Biomasse Kraftstoff herstellen. Mais 01/2014:29-31.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Liu, H., Qin, C., Chen, Z., Zuo, T., Yang, X., Zhou, H., Xu, M., Shen, Y., Lin, H., He, X., Zhang, Y., Li, L., Ding, H., L�bberstedt, T., Zhang, Z., Pan, G. (2014) Identification of miRNAs and their target genes in developing maize ears by deep sequencing. BMC Genomics 15:25.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Chen, Y., Blanco, M., Ji, Q., Frei, U.K., L�bberstedt, T. (2014) Extensive genetic diversity and low linkage disequilibrium within the Bm3 locus in Germplasm Enhancement of Maize populations. Plant Science 221-222: 69-80.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Jeffrey, B., Kuzhiyil, N., Rover, M., Brown, R.C., Lamkey, K.R., Nettleton, D., L�bberstedt, T. (2014) Significant variation for bio-oil compounds after Pyrolysis/Gas Chromatography-Mass Spectrometry of cobs and stover among five near-isogenic brown-midrib hybrids in maize. BioEnergy Research 7:693-701.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Kumar, B.T.N., Abdel-Ghani, A.H., Pace, J., Reyes-Matamoros, J., Hochholdinger, F., L�bberstedt, T. (2014) Association analysis of single nucleotide polymorphisms in candidate genes with root traits in maize (Zea mays L.) seedlings. Plant Science 224:9-19.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Ding, H., Qin, C., Gao, J., Chen, Z., Liu, H., Leng, P., Lin, H., Shen, Y., Zhao, M., Zhou, S., Lan, H., Rong, T., L�bberstedt, T., Zhang, Z., Pan, G. (2014) Heterosis in early maize ear inflorescence development: A genome-wide transcription analysis for two maize inbred line pairs and their hybrids. International Journal of Molecular Sciences 15:13892-13915.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Pace, J., Lee, N., Naik, H.S., Ganapathysubramanian, B., L�bberstedt, T. (2014) Analysis of maize (Zea mays L.) seedling roots with a new high-throughput tool to connect seedling roots to adult roots. PLoS ONE 9(9): e108255.
  • Type: Journal Articles Status: Accepted Year Published: 2015 Citation: Arias Aguirre, A., Studer, B., Do Canto, J., Frei, U.K., L�bberstedt, T. Self-incompatibility in autotetraploids: a proof of concept using High Resolution Melting-based markers. Plant Breeding (in press).
  • Type: Journal Articles Status: Accepted Year Published: 2015 Citation: Wu, Y., Frei, U.K., Liu, H., L�bberstedt, T. Combining genomic selection and doubled haploid technology may increase efficiency of maize breeding. In: Recent Developments in Biotechnology Vol. 2: Plant Biotechnology, Studium Press, J.N. Govil (ed.) (in press).
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Howard, R, AL Carriquiry, WD Beavis (2014). Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures. Genetics: G3(Bethesda) 11:1027-46. doi: 10.1534/g3.114.010298.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Leveraging genomics and phenomics for a better understanding of genotype-phenotype relationship. Center for Sorghum Improvement, Kansas State University, Nov. 10, 2014, Manhattan, KS.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Challenges of G x E and how to overcome them. Integrating Genotypes and Phenotypes to Improve Crops for Challenging Environments, C1-Symposium, Long Beach, CA, Nov. 4, 2014 ASA-CSSA-SSSA meeting.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Emerging and long-standing questions in plant genetics and breeding. Department of Agronomy and Plant Genetics, University of Minnesota, Oct. 14, 2014, St. Paul, MN.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Quantitative perspectives in gene cloning, genotype by environment interaction, and germplasm enhancement. Interdepartmental Plant Group seminar series, Sept. 8, 2014, Columbia, MO.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Genomic selection and model prediction as an integrated breeding strategy. Northwest Agriculture and Forestry University, Jun. 30, 2014, Yangling, Shaanxi, China.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Can we make a dent in genotype by environment interaction in this high throughput era? International Workshop on Engineered Crops, Iowa State University, Apr. 28-29, 2014, Des Moines, IA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Significance of quantitative genetics in the era of high throughput genotyping and phenotyping, Plant Breeding and Genetics Symposium, University of Nebraska-Lincoln, Apr. 1, 2014, Lincoln, NE.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. The significance of quantitative genetics in the high throughput era. Workshop at Center of Maize Improvement, China Agricultural University, Mar. 18-19, 2014, Beijing, China.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yu, J. Parallel evolution of alleles, genes, chromosomes, and genomes. Interdepartmental Plant Biology Program, Iowa State University, Feb. 19, 2014, Ames, IA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Beavis, WD (2014) Using next-gen sequencing technologies for predicting the best parents for the next generation. Second Plant Genomics Congress. St. Louis, MO.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Beavis, WD. (2014) Transforming Plant Breeding into an Engineering Discipline Workshop. Annual Meeting of North American Plant Breeders. Minneapolis, MN.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Beavis, WD. (2014). Transforming plant breeding from art to an engineering discipline. Sustainability Genetics and Future Cultivars Workshop. Phytopath Soc Meetings. Minneapolis, MN.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Beavis, WD. and L Wang (2014) Opportunity for Emergent Disciplines at the Interface of Engineering and Plant Science. International Workshop on Computationally Engineered Plants. Des Moines, Iowa.
  • Type: Websites Status: Published Year Published: 2014 Citation: SoyNAM.org


Progress 01/01/13 to 09/30/13

Outputs
Target Audience: Plant breeders, plant geneticists, and quantitative geneticists in both public and commercial sectors. Changes/Problems: Added a 4th faculty member to the project: Dr. Jianming Yu. What opportunities for training and professional development has the project provided? One graduate student completed her MS and has accepted a position with a commercial breeding company. Three graduate students completed their PhDs and began working for a research foundation, a commercial breeding company and a commercial information technology company. Currently, we are supporting two post-docs and 13 graduate students with extramural funding from federal funding agencies, commercial breeding companies, and commodity boards. An agreement with Sichuan Agricultural University is supporting cross-cultural education of four PhD graduate students in plant breeding. Over 50 graduate students are enrolled in the online MS in Plant Breeding program. Curricula developed for this program provided the basis of a project proposal to the Bill and Melinda Gates Foundation for development and delivery of applied learning modules for Plant Breeding MS degree programs at African Universities. How have the results been disseminated to communities of interest? Twelve presentations and posters at scientific meetings and twenty five publications in a wide array of scientific journals. What do you plan to do during the next reporting period to accomplish the goals? File appropriate IP for genetic discoveries for Nitrogen Use Efficiency, Biomass and Grain Yield for maize and soybean and Optimal gene stacking methods and Genomic Selection.

Impacts
What was accomplished under these goals? In 2013, research project results from 2012 were published in 25 peer-reviewed manuscripts. Current research activities being conducted by CRIS personnel include assessments of genomic selection methods, gene stacking methods, genetic discoveries for nitrogen use efficiency, genetic discoveries in biomass and grain yield for maize and soybean as well as elucidating the global signaling and metabolic networks for maturity and flowering in Arabidopsis. Twenty-five peer reviewed research publications by 2.75 research faculty represents a significant number of discoveries for future development of cultivars adapted to changes in climate and management practices that will affect production agriculture in the near future. These also represent tangible contributions by MS and PhD graduates who are now actively contributing to advancements in genetic improvement and information technologies in the commercial, non-profit and academic sectors of the economy. The online MS in plant breeding is enabling working professionals to advance their careers and will enable African faculty to develop their own graduate curricula. ISU Plant Breeding is becoming an attractive site for continuing education by visiting scientists; we hosted five in 2013.

Publications

  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Abdel-Ghani, A., L�bberstedt, T. (2013) Parent selection  usefulness and prediction of hybrid performance. In: Diagnostics in Plant Breeding, L�bberstedt, T. and Varshney R. Eds., Springer, pp. 349-368.
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Brazauskas, G., Pasakinskiene, I., L�bberstedt, T. (2013) Estimation of temporal allele frequency changes in ryegrass populations selected for axillary tiller development. In: Breeding strategies for sustainable forage and turf grass improvement. Barth, S. and Milbourne, D. Eds., Springer, pp. 81-89.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Brazauskas, G., Xing, Y., Studer, B., Frei, U.K., L�bberstedt, T. (2013) Identification of genomic loci associated with crown rust resistance in perennial ryegrass (Lolium perenne L.) using divergently selected populations. Plant Science 208:34-41.
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Brenner, E.A., Beavis, W.D., Andersen, J.R., L�bberstedt, T. (2013) Prospects and limitations for development and application of functional markers in plants. In: Diagnostics in Plant Breeding, L�bberstedt, T. and Varshney R. Eds., Springer, pp. 329-348.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Guo, B, D Wang, Z Guo, WD Beavis (2013). Family-based association mapping in crop species. Theor Appl Genet 126:1419-1430.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Jansen, C., de Leon, N. Ruff, L., L�bberstedt, T. (2013) Mapping quantitative trait loci for cob architectural and biomass related traits in recombinant IBM inbred lines in maize. BioEnergy Research 6:903-916.
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Jeffrey, B., L�bberstedt, T. (2013) Molecular breeding for bioenergy traits and map based cloning of genes controlling them. Compendium of Bioenergy Plants: Corn (in print, electronic or web-based form), S. Goldman (ed.), Science Publishers/Taylor & Francis/CRC PRESS, Boca Raton, FL, USA, 198-215.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Li, C., M. Chen, S. Chao, J. Yu, and G. Bai. 2013. Identification of a novel gene, H34, in wheat using recombinant inbred lines and single nucleotide polymorphism markers. Theoretical and Applied Genetics 126:2065-2071.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Li, L., K. Petsch, R. Shimizu, S. Liu, W.W. Xu, K. Ying, J. Yu, M.J. Scanlon, P.S. Schnable, M.C.P. Timmermans, N.M. Springer, and G.J. Muehlbauer. 2013. Mendelian and non-Mendelian regulation of gene expression in the maize shoot apex. PLoS Genetics 9: e1003202.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Liu, S., S.K. Sehgal, J. Li, M. Lin, H.N. Trick, J. Yu, B.S. Gill, and G. Bai. 2013. Cloning and characterization of a critical regulator for pre-harvest sprouting in wheat. Genetics 195:263-273.
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: L�bberstedt, T. (2013) Diagnostics in plant breeding. In: Diagnostics in Plant Breeding, L�bberstedt, T. and Varshney R. Eds., Springer, pp. 3-10.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Lukman, R., Afifuddin, A., L�bberstedt, T. (2013) Unraveling the genetic diversity of maize downy mildew in Indonesia. J Plant Pathology and Microbiology 4:162.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Meade, KA, M Cooper, WD Beavis (2013). Modeling biomass accumulation in maize kernels. Field Crops Research 151:92100 http://dx.doi.org/10.1016/j.fcr.2013.07.014
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Morris G.P., D.H. Rhodes, Z. Brenton, P. Ramu, V.M. Thayil, S. Deshpande, C.T. Hash, C. Acharya, S.E. Mitchell, E.S. Buckler, J. Yu, and S. Kresovich. 2013. Dissecting genome-wide association signals for loss-of-function phenotypes in sorghum flavonoid pigmentation traits. G3 3:2085-2094.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Narayanan S., R.M. Aiken, P.V.V. Prasad, Z. Xin, and J. Yu. 2013. Water and radiation use efficiencies in sorghum. Agronomy Journal 105:649-656.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Pfeifer, M., Mayer, K., Asp, T., Martis, M., L�bberstedt, T., Frei, U.K., Studer, B. (2013) The Lolium genome zipper  targeted use of grass genome resources for ryegrass genomics. Plant Phys. 161:571-582.
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Sukumaran, S., and J. Yu. 2014. Association mapping of genetic resources: Achievements and future perspectives. In R. Tuberosa et al. (ed.) Genomics of Plant Genetic Resources, 207-235.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Tao, Y., Jiang, L., Liu, Q., Zhang, Y., Zhang, R., Ingvardsen, C.R., Frei, U.K., Lai, J., Wang, B., L�bberstedt, T., Xu, M.L. (2013) Joint fine-mapping of Scmv1, a major locus involved in resistance to sugarcane mosaic virus (SCMV) in maize. BMC Plant Biol 13:162.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Xu, F., J. Yu, T. Tesso, F. Dowell, and D. Wang. 2013. Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: A mini-review. Applied Energy 104:801-809.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Yu, X., G. Bai, S. Liu, N. Luo, Y. Wang, D.S. Richmond, P.M. Pijut, S.A. Jackson, J. Yu, and Y. Jiang. 2013. Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions. Journal of Experimental Botany 64:1537-1551.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Yu, J., M.T. Hamblin, and M.R. Tuinstra. 2013. Association genetics strategies and resources. In A. Paterson (ed.) Genetics and Genomics of the Saccharinae. Plant Genetics and Genomics: Crops and Models 11:187-203. Springer Verlag.


Progress 01/01/12 to 12/31/12

Outputs
OUTPUTS: Six graduate students completed their PhDs and have assumed positions. A second generation of graduate students (see participants) were recruited. Collaborative agreements with Pioneer, Syngenta, University of Illinois (UIUC) and Sichuan Agricultural University (SAU) were established. A soyNAM project consisting of 5600 RILs derived from 40 crosses was grown in Ames and nine other locations across maturity zone 3 from Nebraska to Pennsylvania. A project database and website for soyNAM was developed as part of a 3-tier architecture. First year data have been loaded and preliminary data are being analyzed. Lubberstedt coordinated development of an interdisciplinary team to work on nitrogen use efficiency (NUE), which succeeded in attracting internal funding from the Plant Sciences Institute, and is actively seeking external funding. The IBM Syn10 population was genotyped by sequencing at SAU. Genetic association analyses have been extended to novel genotype panels including the Ames panel, a panel developed by the GEM project (USDA), and a CIMMYT panel. A Maximum likelihood method was developed and applied to guanine-cytosine (GC) content data from Long Homologous Genomic Regions in soybean. The method revealed that GC content of these regions was best modeled as a mixture of four distributions, where one of the distributions was significantly associated with functional genes and transposable elements. Parameter estimates of nonlinear functions used to model maize kernel biomass and moisture accumulation were associated with segregating genomic regions. Candidate genes within these regions were identified. The accuracy of all known parametric and non-parametric genomic prediction methods were compared for traits consisting of simple additive or complex epistatic architectures. Non-parametric methods outperform parametric methods when the underlying genetic architecture is based on epistasis. Novel methods for normalizing next-gen gene expression data were developed and used to identify allele specific expression in hybrids and alternative splicing of transcripts in both inbreds and hybrids. A hydroponic system was evaluated for NUE studies in Brassica rapa and Arabidopsis. Regulation of salts and impact on growth were issues that emerged in the third generation of breeding for this short life-span model species. The hydroponic system has been donated to an undergraduate teaching lab. Progress on development of whole genome genotyping and resequencing technologies for Mimulus guttata, Brassica rapa and Arabidopsis have not reached a point where costs will support multiple generations of genomic selection per year. We have decided to discontinue development of the model systems for evaluating GS in plant breeding until such costs are commensurate with funding. Research findings have been reported at conferences and in peer-reviewed publications. PARTICIPANTS: Constantin Jansen, graduate student: fine mapping (financing by this USDA project from 8/2010 on). Bharath K. T. Narayana, graduate student (PhD): Candidate gene based association mapping for NUE and associated in maize. Jenaro Reyes Matamoros (Research Professor at Benemerita Universidad Autonoma de Puebla): Candidate gene based association mapping for root traits in maize. Adel Abdel-Ghani (Fulbright Postdoctoral Fellow, Mu'tah University, Jordan): Candidate gene based association mapping for NUE and associated in maize. Kendra A Meade, pre-doctoral Fellow: Lab manager and research on development of data analysis methods for dynamic traits. Reka Howard, graduate student (PhD): Development of non-parametric methods for Genomic Selection in plant breeding. Shreyartha Muhkarjee, graduate student (PhD): Development of bioinformatics methods for analyses of gene expression experiments. Chris J Meyer, undergraduate: Development of model plant systems for evaluation of novel breeding methods and evaluation of NUE. Jenna Woody, graduate student (PhD): Sequence analysis of the soybean genome. Franco Asoro, graduate student (PhD): Evaluation of genomic selection in Avena sativa. Danielle Dykema, graduate student (MS): Evaluation of genomic construction in Arabidopsis. Dawn Gibson, graduate student (MS): Analysis of soyNAM for yield and associated traits. Collaborations: John Sawyer (ISU), Lizhi Wang (ISU), Randy Shoemaker (USDA-ARS, Ames), Plant Introduction Station (USDA-ARS, Ames), Frank Hochholdinger (University of Tubingen, Germany), Steve Moose, Martin Bohn and Brian Diers (University of Illinois), James Specht (Universtiy of Nebraska); Pioneer, Dow, Syngenta. TARGET AUDIENCES: Plant physiologists, plant geneticists, plant breeders and quantitative geneticists in both public and private sectors have benefited from research findings reported at conferences and in publications. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
All PhD graduates are actively contributing to advancements in genetic improvement as plant scientists in the commercial, non-profit and academic sectors. Genotyped IBM Syn10 is enabling a detailed genetic analysis of NUE related traits in maize. Demonstrated the capability of identifying genetic regulators of dynamic (continuously changing) traits and filed IP on the candidate genes responsible for growth and development of maize kernels. Recognition that long homogeneous genome regions (LHGRs) fall within four classes based on GC content and that one of the classes is significantly associated with functional genes and transposable elements will enable more effective and efficient map-based cloning. SoyNAM database will enable all collaborators to conduct data analyses on combined and subsets of data. Recognition that non-parametric methods are best for genome prediction when genetic architectures are based on epistasis will enable plant breeders to select among data analysis methods for genetic improvement.

Publications

  • Abdel-Ghani, A., Kumar, B.T., Montomares, J.R., Gonzalez-Portilla, P., Jansen, C., San Martin, J.P., Lee, M., Lubberstedt, T. (2013) Genotypic variation for root traits of maize inbred lines grown under contrasting nitrogen conditions. Euphytica 189:123-133
  • Arias, A., Studer, B., Frei, U.K., Lubberstedt, T. (2012) Prospects for hybrid breeding in bioenergy grasses. BioEnergy Research 5:10-19
  • Arias, A., Frei, U.K., Wollenweber, B., Lubberstedt, T. (2012) A tool for estimation of pollen compatibility in a digenic gametophytic self incompatibility system in autotetraploids species. BMC Bioinformatics 13:125
  • Asoro, FG, M Newell, P Scott, WD Beavis, JL Jannink,(2012) Genomewide Association Study for Beta-glucan Content in North American Elite Oat. Crop Science (doi:10.2135/cropsci2012.01.0039)
  • Brenner, E.A., Blanco, M., Gardner, C., Lubberstedt, T. (2012) Genotypic and phenotypic characterization of Germplasm Enhancement in Maize doubled haploid lines for cell wall digestibility. Mol. Breeding 30:1001-1016
  • Kumar, B.T., Abdel-Ghani, A., Hochholdinger, F., Montomares, J.R, Lubberstedt, T. (2012) Genotypic variation for root architectural traits in maize (Zea mays L.) inbred lines. Plant Breeding 131:465-478
  • Lubberstedt, T., Asp, T. (2012) A transcriptome map of perennial ryegrass (Lolium perenne L.). BMC Genomics 13:140 [Highly Accessed]
  • Lubberstedt, T.., Frei, U.K. (2012) Application of doubled haploids for target gene fixation in backcross programs. Plant Breeding 131:449-452
  • Newell, MA, FG Asoro, MP Scott, PJ White, WD Beavis, and JLuc Jannink (2012) Genome-Wide Association Study for Oat (Avena sativa L.) Beta-Glucan using Germplasm of Worldwide Origin. Theoretical and Applied Genetics (DOI 10.1007/s00122-012-1945-0).
  • Studer, B., Byrne, S., Nielsen, R., Panitz, F., Bendixen, C., Islam, M.S., Pfeiffer, M., Lubberstedt, T., Asp, T. (2012) A transcriptome map of perennial ryegrass (Lolium perenne L.). BMC Genomics 13:140
  • Brenner, E.A., Salazar, A.M., Zabotina, O., Lubberstedt, T. (2012) Characterization of European forage maize lines for stover composition and associations with polymorphisms within O-methyltransferase genes. Plant Sci. 185:281-287
  • Chen, Y., Liu, H., Ali, F., Scott, P.M., Ji, Q., Frei, U.K., Lubberstedt, T. (2012) Bm6 - A novel brown midrib gene in maize was mapped to a 180 kb region in maize. Theor. Appl. Genet. 125:1223-1235
  • Jansen, C., Lubberstedt, T. (2012) Turning corn cobs into a valuable feedstock. BioEnergy Research 5:20-31
  • Jones, R., Reinot, T., Frei, U.K., Tseng, Y., Lubberstedt, T., McClelland, J., (2012) Selection of Haploid Maize Kernels from Hybrid Kernels for Plant Breeding Using Near Infrared Spectroscopy and SIMCA Analysis. Applied Spectroscopy 66:110-119
  • Woody, J.L., Beavis, WD, Shoemaker, R.C. (2012). Large homogeneous genome regions (isochors) in soybean (Glycine max (L.) Merr.. Front. Plant Genetics and Genomics. Doi: 10.3389/fgene.2012.00098.
  • Zhao, X., Tan, G., Xing, Y., Wei, L., Lubberstedt, T., Xu, M.L. (2012) Marker-assisted introgression of qHSR1 to improve maize resistance to head smut. Mol. Breed. 30:1077-1088.


Progress 01/01/11 to 12/31/11

Outputs
OUTPUTS: 1. 74 association study (AS) lines were grown at high and low N sites at to determine the nitrogen usage efficiency response. 2. Genotypic variation for root architecture traits among AS lines grown in water was studied using the paper roll method. Significant variation for root architecture was found in the AS panel. 3. Young root characteristics of AS lines grown under different levels of N was measured using the paper roll method. Significant genotypic variation for root architecture was found in the AS panel. 4. Allele re-sequencing of candidate root genes RTCN, RTH3, RUM1 and RUL1 was carried out in the AS lines. SNPs, haplotype structure and linkage disequilibrium was studied at the candidate root gene loci. 5. Gene based association analysis was carried between the SNP's identified in the root genes and root traits measured in young maize seedlings. Significant associations were found between root gene SNPs and root traits. Fewer significant associations were detected between root genes SNPs and root traits of AS lines grown under different levels of N. 6. Kernel biomass and moisture of 140 testcrossed recombinant inbred lines and six check hybrids were evaluated at ~ 25 timepoints in three field replicates. 7. Data from the hybrids were used to develop functional models representing the complex phenotypes of biomass accumulation and moisture content. 8. Differences among the functional curves indicate that genetic variability exists for rate of growth and final kernel weight. 9. Non-parametric Genomic Selection methods were developed using a reproducing Kernel Hilbert Space with different bandwidth selection techniques for plant breeding population structures. The methods were evaluated for accuracy using simulated data sets in a blind experiment. 10. Genotypic variability in transcript expression in developing ear shoots was evaluated in a generation means experiment designed for controlling non-genetic variation under field conditions. Highly significant genotypic variation was detected in over 25% of the 30,208 expressed genes. A significant proportion of these were associated with genotypic variation in kernels per row and grain weight per ear. 11. A preliminary assessment of an operations research approach to genetic improvement, known as genome construction, was compared with genomic selection for Genetic Gain. 12. Three model species were evaluated and appropriate growth conditions assessed. Self-incompatibility issues as well as flowering delays in both species were addressed. 13. Hydroponics was used to assess the phenotypic effects of nitrogen deprivation in different Brassica rapa inbreds derived from a random-mated population. Appropriate nutrient levels for growth of Brassica rapa in hydroponic growth conditions were determined, and an analysis of the optimal nitrogen levels for differentiating inbred lines was determined. Results for all 13 activities have been disseminated through publications, posters and presentations. PARTICIPANTS: Bharath K. T. Narayana, graduate student (PhD): Candidate gene based association mapping for NUE and associated in maize. Jenaro Reyes Matamoros (Research Professor at Benemerita Universidad Autonoma de Puebla): Candidate gene based association mapping for root traits in maize. Adel Abdel-Ghani (Fulbright Postdoctoral Fellow, Mu'tah University, Jordan): Candidate gene based association mapping for NUE and associated in maize. Kendra A Meade, pre-doctoral Fellow: Lab manager and research on development of functional mapping methods. Reka Howard, graduate student (PhD): Development of non-parametric methods for Genomic Selection in plant breeding population structures. Shreyartha Muhkarjee, graduate student (PhD): Development of bioinformatics methods for analyses of gene expression experiments. Chris J Meyer, undergraduate: Development of model plant systems for evaluation of novel breeding methods and evaluation of NUE. TARGET AUDIENCES: The use of operations research for genetic improvement through genome construction was reported to and recognized by the Keck Foundation as a transformative approach to genetic improvement. Keck requested a phase 1 proposal, which we intend to implement with Arabidopsis as a model to demonstrate proof of concept. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
1. Identification of genetic causes for the association between root architecture and Nitrogen Use Efficiency suggests that reductions in N can be achieved by focusing N applications on the appropriate rooting zones in the soil profile, thus reducing input costs for farmers and excessive N runoff in downstream water uses. 2. By representing complex traits as non-linear functions we will be able to identify genes for many complex traits that have here-to-fore been avoided. We are developing this methodology to identify genetic variants that control growth of seeds, but it can also be applied to any biological tissue including human tumors. Identification of the genetic growth regulators will eventually provide the ability to regulate growth. In the case of seeds, it will be possible to extend growth or induce early maturity depending upon forecasts of growing seasons. 3. Development of the non-parametric methods for Genome Selection will improve the accuracy of Genomic Selection in plant population structures. Accuracy is defined as the similarity between predicted and actual outcomes. With a high accuracy, it will not be necessary to continue the trial and error approach to genetic improvement of plants, thus enabling the plant breeder to screen very large numbers of plants without having to field test any but those with the most desirable predicted values. 4. Generation means analysis of gene expression in developing ears and their correlations with ear phenotypes suggests that inbreds and hybrids differ primarily due to differences in energy metabolism. This observation supports a recently proposed theory for heterosis and inbreeding depression. If confirmed it will result in better predictions of which hybrids should be made to maximize productivity. 5. Genome construction was recognized by the Keck Foundation as a transformative approach to genetic improvement and asked for a phase 1 proposal, which we intend to implement with a model species to demonstrate proof of concept in a time frame of a few years rather than the current decades currently required for multiple generations of plant breeding. Genome construction will likely replace genomic selection in the long term because it takes into account multiple competing objectives for genetic improvement.

Publications

  • Asoro F.G., M.A. Newell, W.D. Beavis, M.P. Scott and J.L. Jannink. 2011. Accuracy and training population design for genomic selection. Plant Genome 4:132-144.
  • Xu, P., L. Wang, W.D. Beavis. 2011. An optimization approach to gene stacking. European Journal of Operational Research 214:168-178.


Progress 01/01/10 to 12/31/10

Outputs
OUTPUTS: 1. In summer 2010, 80 association study (AS) lines were grown at high and low N sites provided by Pioneer Hi-Bred and at Burkey farm, ISU, to determine the nitrogen usage efficiency response. Grain yield, chlorophyll content, plant height, anthesis-silking interval measurements were taken and the data is being analyzed. 2. Young root characteristics (6, 10 and 14 day old seedlings) of 80 AS lines were measured using the paper roll method. Various root traits such as primary root length, seminal root length, lateral root length, root dry weight etc. were measured. 3. To asses and control the effect of population structure in AS lines, SNP genotyping was done using 105 ISU SNP markers covering the 10 maize chromosomes. Re-sequencing of five maize root candidate genes from 80 AS lines is in progress. 4. Manuscript on power, precision and accuracy of nested association mapping was revised, published in Genetics and highlighted by Maize Genome DB as one of the most significant manuscripts in 2010. 5. A novel computationally efficent method to associate linkage maps with physical maps was discovered, developed and published in Molecular Breeding. Raw data and results are available to the publich through the GFS Sprague Population Genetics website [http://www.agron.iastate.edu/GFSPopGen/resources.html]. 6. Results of optimization of breeding strategies using Operations Research approaches were submitted for publication at The European Journal for Operations Research and have been accepted pending minor revisions. 7. Based on a literature review and consultation with plant physiologists at Pioneer Hi-Bred, it is fairly clear that NUE in maize is most likely a function of Nitrogen demand (sink), rather than a function of uptake and transport (source). Nitrogen demand by developing maize ears was investigated using next gen sequencing of mRNA sampled from developing ears produced by a diallel of 4 inbreds and 6 generations from each of the six crosses. Of more than 30,000 transcripts that could be mapped to unique gene models in the reference genomes, approximately 11,000 were differentially expressed (FDR<0.001) among the generations within the families. Of greatest interest were regulatory genes, such as members of the ramosa family, that can affect growth and development and thus Nitrogen metabolism. A draft manuscript of these results has been developed and will be submitted to Genetics in 2011. 8. Physiological growth curves of ear development and growth on 150 doubled haploid lines have been modeled using a large number of non-linear functions. The most parsimonious models include a Gompertz function, modified to take into account unequal errors through the growing season. First derivatives of the biomass accumulation curves are most parsimonious with curves of moisture content. QTL of estimated parameters that determine inflection point and asymptote in biomass accumulation will be determined in 2011. 9. Two model systems for evaluating breeding strategies have been identified: Brassica rapa for cross pollinated crops that are self compatible, e.g., maize and Arabidopsis thaliana for self pollinated crops. PARTICIPANTS: William D Beavis, PI/PD. Coordinate project and statistical activities and mentor graduate students. Thomas Lubberstedt, Co-PI. Coordinate Experimental Activities. Michael Lee, Co-PI, conduct QTL experiments. Lizhi Wang, Dept. Industrial Engineering, Iowa State University. Mark Cooper, Pioneer Hi-Bred. Training opportunities in development of statistical methods were provided to Reka Howard, graduate student (PhD)and Kendra Meade, graduate student (PhD); development of Bioinformatic analyses were provided to Shreyartha Mukherjee, graduate student in Computational Biology (PhD); development of methods to isolate candidate genes through association mapping were provided to Bharath Narayana (PhD); application of QTL analysis methods were provided to Pedro Jose Gonzales (PhD) and Constantin Jansen (PhD). Undergraduate training in development of husbandry and breeding systems of model plant systems was provided to Chris Meyers, Brian Meyers and Hannah Cox. All graduate students participated in presentations to professional groups including Pioneer, Monsanto, Dow and Syngenta. Both graduate and undergraduate students participated in weekly team meetings. TARGET AUDIENCES: The target audiences for this project include professional groups such as commercial plant breeding organizations, maize geneticists, corn growers, agronomists, bioenergy producers, plant genomicists, mathematical modelers of biological systems, environmentalists and water quality engineers. The information and knowledge generated by the project will be communicated through professional meetings and publications as well as press releases. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
There are three impacts: 1. Identification of genetic resources for nitrogen use effiency will enable non-transgenic solutions to reduce Nitrogen applications, thus reducing non-point runoff sources of nitrogen pollution. 2. The statistical methods will enable us to identify the native genes that can be transferred to elite corn hybrids. 3. The optimization of breeding strategies will enable breeders to transfer the native genes to elite corn hybrids without transferring deleterious genes that may be resident in the non-elite resources, thus preventing "yield drag" in converting elite hybrids to be nitrogen efficient.

Publications

  • Guo, B and WD Beavis. 2010. In silico Genotyping of the Maize Nested Association Mapping Population. Molecular Breeding DOI 10.1007/s11032-010-9503-4.
  • Guo, B, SA Sleper, and WD Beavis. 2010. Nested Association Mapping for Identification of Functional Markers Genetics 186:373-383.
  • Merrick, L, T Lubberstedt, K Lamkey, W Beavis, and K Moore. 2010. Toward a master of Science in Plant Breeding via Distance Education. 4th Plant Breeding Conference, Johnston, Iowa.
  • Pedro Jose Gonzalez Portilla, Constantin Jansen, Bharath K.T. Narayana, Michael Lee, and Thomas Lubberstedt. 2010. Development of functional markers for Nitrogen usage efficiency in maize. Plant Breeding Symposium, Iowa State University, Ames, Iowa.(poster)
  • Pedro Jose Gonzalez Portilla, Constantin Jansen, Bharath K.T. Narayana, Michael Lee, and Thomas Lubberstedt. 2010. Development of functional markers for Nitrogen usage efficiency in maize. 4th Annual Plant Breeding Meeting, Pioneer Hi-Bred International, Johnston, Iowa. (poster)


Progress 01/01/09 to 12/31/09

Outputs
OUTPUTS: 1. A high resolution mapping population for NUE QTL, the IBMSyn10 population consisting of 243 doubled haploid lines, was grown in summer 2009 for seed multiplication. 2. Eighty association study (AS) lines consisting of expired PVP and diverse public inbred lines were obtained from the Plant Introduction Station in Ames, IA, and multiplied in summer 2009. DNA was extracted from all AS lines. For each of the genotype-root gene combinations, PCR amplicons for five candidate genes have been produced and sequenced . 3. Power, precision and accuracy of nested association mapping to identify QTN was investigated using simulation modeling. 4. Collaborations were established with professors of operations research to approach breeding optimization using systems engineering approaches. 5. Three plant species (Mimulus guttatus, Brassica rapa, Zea mays var. short season flint germplasm) were evaluated as model systems for investigating marker assisted breeding and limits to selection. Progress in development of materials were disseminated through presentations at Pioneer Hi-Bred, the American Seed Trade Association (ASTA) the Plant and Animal Genome. Progress in evaluation of statistical methods were presented at Syngenta and submitted as a manuscript to Genetics, which has been accepted with suggested revisions. Progress in development of systems engineering approaches for genetic improvement were presented at the IEEE ASTA meetings. PARTICIPANTS: William D. Beavis, Dept. of Agronomy, Iowa State University; Michael Lee, Dept. of Agronomy, Iowa State University; Thomas Lubberstedt, Dept. of Agronomy, Iowa State University; Collaborators: Kendall R. Lamkey, Dept. of Agronomy, Iowa State University; Lizhi Wang, Dept. Industrial Engineering, Iowa State University; Mark Cooper, Pioneer Hi-Bred. Training opportunities were provided to: Reka Howard, graduate student (PhD), statistical methods; Shreyartha Mukherjee, graduate student (PhD), bioinformatics; Baohong Guo, a post-doctoral fellow, evaluation of association mapping methods; Kendra Meade, graduate student (PhD), development of high throughput phenotyping; Bharath K. T. Narayana, graduate student (MSc); candidate gene isolation and association mapping; Pedro Jose Gonzalez Portilla (PhD), graduate student, QTL mapping; Constantin Jansen, graduate student (PhD); fine mapping; Hannah Cox, undergraduate, evaluation of model plant systems; Chris Meyers, undergraduate, evaluation of model plant systems. All graduate students and post-doctoral fellows participated in presentations to professional groups including Pionner, Monsanto, Dow and Syngenta, while undergraduates participated in on-campus reports at weekly group meetings. TARGET AUDIENCES: Plant breeding professionals will benefit from knowledge of the location of NUE genes, novel statistical methods for identifying the functional markers and novel marker assisted breeding strategies. Importantly, novel methods will enable faster deployement of both native and transgenic soruces of NUE genes to producers throughout the world. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
1. Outputs 1 and 2 provided information on genetic resources for nitrogen use effiency and will enable non-transgenic solutions to reducing Nitrogen applications, thus reducing non-point runoff sources of nitrogen pollution. 2. The statistical methods developed in output 3, will enable us to identify the native genes that can be transferred to elite corn hybrids. Results indicate that nested mating designs involving several reference parents are capable of resolving functional markers with high power and accuracy, even in situations where disequilibrium among functional and non functional markers in the same genomic region has the potential to confound interpretation of results. Results will appear in a manuscript that is accepted at Genetics and is under revision. 3. The optimization of breeding strategies (from output 4) will enable breeders to transfer the native genes to elite corn hybrids without transferring deleterious genes that may be resident in the non-elite resources, thus preventing "linkage drag" in converting elite hybrids to be nitrogen efficient. 4. Short season flint varieties of Zea maize were deemed unfit as a model system because the life-cycle (seed to seed) is too long and the amount of greenhouse space required to conduct large scale experiments is too large.

Publications

  • Lubberstedt, T., Chen, Y., Brenner, E.A., Zein, I. 2009. Development and application of functional markers. 45th Annual Corn Breeders School meeting, Urbana-Champaign, p. 23-31 (oral).
  • Narayana, B.K.T., Jansen, C., Gonzalez Portilla, P.J., Mukherjee, S., Beavis, W., Lee, M. and Lubberstedt, T. 2009. Development of Functional Markers for NUE in Maize using a Candidate-gene Approach. 9th International Plant Molecular Biology Congress, St. Louis (poster).