Progress 08/01/06 to 07/31/09
Outputs
OUTPUTS: We have examined the effect of number of background markers on quantifying the genetic relatedness and the power of association mapping with different sample sizes. These works were conducted through computer simulations based on empirical data from two association mapping panels (maize and dog) with complex population structure and familial relatedness. We found that a relatively smaller set of SSR markers was able to provide a robust relatedness estimate for a diverse set of maize line and a set of dogs with connected pedigree, while several hundred SNPs are required for the maize sample. Sample size has larger impact on the statistical power to detect QTL with relatively small effects. We have also conducted theoretical computer simulations to investigate the usefulness of using maximum likelihood based model testing approach to evaluate the adequacy of background markers. The results showed that kinship construction with subsets of the whole marker panel and subsequent model testing with multiple phenotypic traits could provide ad hoc information on whether the number of markers is sufficient to quantify genetic relationships among individuals. We investigated a nonmetric multidimensional scaling method for controlling population structure and compared the performance with other methods for controlling for different types of genetic relationships encountered in association analyses. Our results showed that by exploiting both genotypic and phenotypic information, this two-stage dimension determination approach balances the trade-off between data fit and model complexity, thus resulting an effective reduction in false positive rate with minimum loss in statistical power. The nMDS method provides a powerful complement to other existing methods. Selective phenotyping, a strategy for sample selection, was examined with maize data. However, no significant power gain was observed for selective phenotyping of samples that retain maximum genetic diversity than random sampling, potentially due to the complex genetic relationship. We collaborated on the association mapping in teosinte and tested different models with population structure, relative kinship, and principle components. Other collaborations in maize, wheat, and perennial ryegrass have resulted with several publications or manuscripts in preparation. We completed a review paper to address some of the common questions from various research groups. Overall, all proposed objectives have been met including sample selection, relationship estimation, variance component estimation, and principle component analysis. Research findings have been presented at several national and international conferences and workshops. Several papers have been published and additional manuscripts are either in review or in preparation. We are well positioned (i.e., bridging genetics and genomics, quantitative genetics, population genetics, and statistics) to conduct further methodology research and empirical analyses of data generated from either our own group or other collaborators across various crop species. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Association mapping is now being carried out in many different plant and animal species. Given the nature of the germplasm pertinent to association studies, many questions have been raised, such as the size of an association mapping panel, the number of background markers to be scored for a robust genetic relatedness measurement, and whether SSR markers can be used for association mapping. The current project provides general guidelines to these questions and statistical methods for complex trait dissection through association mapping in a wide range of plant and animal species. Besides conducting relevant research, we were invited to review the progress and prospects of association mapping in plants. So far, we have offered consultation on genetic design and statistical analysis of association mapping to many research groups in different species, including soybean, common bean, alfalfa, grape, wheat, maize, and perennial ryegrass. The PI has delivered five invited talks at various national and international conferences and workshops. Our work in theoretical examination, empirical analysis, review and perspectives, and consultation contribute significantly to a better understanding of association mapping. With the wide spread of high throughput genomic technologies in many crop species, we expected to see even more association analyses. Insights gained from association mapping would facilitate the development of genomic-assisted plant breeding strategies. The broad impacts of the current project are exemplified by both the original research works from our group and collaboration with other groups, and the presentation and consultation we delivered to a wide range of audience.
Publications
- Yang, X.H., J.B. Yan, Y.P. Zheng, J. Yu, and J.S. Li. 2007 Reviews of association analysis of quantitative traits in plants. Acta Agronomica Sinica 33:523-530.
- Tabanao, D., J. Yu, and R. Bernardo. 2007. Multilocus epistasis, linkage, and genetic variance in breeding populations with few parents. Theoretical and Applied Genetics 115:335-342.
- Sorrells M.E., and J. Yu. 2009. Linkage disequilibrium and association mapping in the Triticeae. In C. Feuillet and G. Muehlbauer (ed.) Genetics and Genomics of the Triticeae. Springer Verlag (in press).
- Yu, J., Z. Zhang, C, Zhu, D. Tabanao, G. Pressoir, M.R. Tuinstra, S. Kresovich, R.J. Todhunter, and E.S. Buckler. 2009. Simulation appraisal of the adequacy of number of background markers for relationship estimation in association mapping. The Plant Genome (in press).
- Zhu, C., M. Gore, E.S. Buckler, and J. Yu. 2008. Status and prospects of association mapping in plants. The Plant Genome 1:5-20.
- Weber, A., R.M. Clark, L. Vaughn, J.D.J. Sanchez-Gonzalez, J. Yu, B.S. Yandell, P. Bradbury, J.F. Doebley. 2008. Major regulatory genes in maize contribute to standing variation in Teosinte (Zea mays ssp. parviglumis). Genetics 177:2349-2359.
- Yu, J., J.B. Holland, M.D. McMullen, and E.S. Buckler. 2008. Genetic design and statistical power of nested association mapping in maize. Genetics 138:539-551.
- Bernardo, R., and J. Yu. 2007. Prospects for genome-wide selection for quantitative traits in maize. Crop Science 47:1082-1090.
- Stich, B., J. Yu, A.E. Melchinger, H.-P. Piepho, H.F. Utz, H.P. Maurer, and E.S. Buckler. 2007. Power to detect high-order epistatic interactions in a metabolic pathway using a new mapping strategy. Genetics 176:563-570.
- Ersoz, E., J. Yu, and E.S. Buckler. 2009. Applications of linkage disequilibrium and association mapping in maize. In A.L. Kriz and B.A. Larkins (ed.) Molecular Genetic Approaches to Maize Improvement, Biotechnology in Agriculture and Forestry, Vol 63, 173-195. Springer Verlag.
- Ersoz, E., J. Yu, and E.S. Buckler. 2008. Applications of linkage disequilibrium and association mapping in crop plants. In R. Varshney and R. Tuberosa (ed.) Genomics-Assisted Crop Improvement: Vol 1: Genomics Approaches and Platforms, 97-120. Springer Verlag.
- Zhu, C., and J. Yu. 2009. Nonmetric multidimensional scaling corrects for population structure in association mapping with different sample types. 2009 International Plant and Animal Genome Conference, Jan 10-14, 2008, San Diego, CA.
- Zhu, C., M. Gore, E.S. Buckler, and J. Yu. 2008. Status and prospects of association mapping in plants. 2008 Annual ASA/CSSA/SSSA Meeting.
- Xiang, X., S. Bean, N. Ochanda, M. Tuinstra, and J. Yu. 2008. Grain quality analysis of a diverse collection in sorghum. 2008 Annual ASA/CSSA/SSSA Meeting.
- Zhang, D., G. Bai, B. Carver, J. Yu, and C. Zhu. 2008. Association mapping of wheat genes resistant to aluminum toxicity. 2008 Annual ASA/CSSA/SSSA Meeting.
- Jiang, Y., Y. Wang, S. Bian, G. Bai, and J. Yu. 2008. Toward association mapping of candidate genes with drought tolerance in perennial ryegrass. 2008 Annual ASA/CSSA/SSSA Meeting.
- Sun, G., C. Zhu, S. Yang, and J. Yu. 2008. On the R2 statistic for association mapping by mixed models, 20th Conference on Applied Statistics in Agriculture, Manhattan, KS.
- Zhu, C., G. Sun, and J. Yu. 2007. Genetic and statistical aspects of association mapping. 2007 Annual ASA/CSSA/SSSA Meeting.
- Wang, M.L., J. Erpelding, J. Yu, and G.A. Pederson. 2007. Mining genetic diversity of sweet sorghum in the US collection for biofuel production. 2007 Annual Meeting of ASPB.
- Weber, A., R. Clark, L. Vaughn, J.J. Sanchez-Gonzalez, W. Briggs, William; J. Yu, B.S. Yandell, P.J. Bradbury, K. Liu, M. McMullen, E.S. Buckler, J.F. Doebley. 2007. Association mapping in teosinte: How natural allelic variation controls phenotypic variation. 49th Annual Maize Genetics Conference. p 123.
- G. Pressoir, J. Yu, Z. Zhang, E.S. Buckler, and S. Kresovich. 2007. The genetics of complex traits. 49th Annual Maize Genetics Conference. p 138.
- Yu, J., R. Bernardo, E.S. Buckler. 2007. Mixed model in genomic mapping and genome-wide selection. 19th Conference on Applied Statistics in Agriculture, Manhattan, KS. Yu, J., D. Tabanao, Z. Zhang, G. Pressoir, S. Kresovich, and E. Buckler. 2007. Experimental design in association mapping with diverse germplasm. Plant and Animal Genome XV Conference, San Diego, California.
- Harjes, C.E., J. Yu, J. Holland, M.M. Goodman, M.D. McMullen, T. Rocheford, E.S. Buckler. 2007. Improving the potential contribution of QTL to applied breeding programs with diversity based high resolution quantitative trait dissection. Plant and Animal Genome XV Conference, San Diego, California.
- Yu, J., D. Tabanao, Z. Zhang, G. Pressoir, S. Kresovich, and E. Buckler. 2006. Association mapping with diverse germplasm. 2006 Annual ASA/CSSA/SSSA Meeting.
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Progress 08/01/07 to 07/31/08
Outputs
OUTPUTS: We have examined the effect of number of background markers on quantifying the genetic relatedness and the power of association mapping with different sample sizes. These works were conducted through computer simulations based on empirical data from two association mapping panels (maize and dog) with complex population structure and familial relatedness. We have found that a relatively smaller set of SSR markers (~40) was able to provide a robust relatedness estimate for a diverse set of maize line and a set of dogs with connected pedigree, while several hundred SNPs are required. Sample size has larger impact on the statistical power to detect QTL with relatively small effects. Although SNP detection and genotyping have been routinely carried out in model species or major crops, researchers in minor corps or crops with complex genomes may still initiate association mapping study with current germplasm and genotyping techniques. We have also conducted a systematic computer simulation to investigate the usefulness of using maximum likelihood based model testing approach to evaluate the adequacy of background markers. The results, both from computer simulations and empirical data analyses, showed that kinship construction with subsets of the whole marker panel and subsequent model testing with multiple phenotypic traits could provide ad hoc information on whether the number of markers is sufficient to quantify genetic relationships among individuals. These research findings were presented at the 2006 Annual ASA/CSSA/SSSA meeting and 19th Conference on Applied Statistics in Agriculture in 2007. We have also established contacts with researchers in Fabaceae and provided consultation to various questions in genetic design, statistical analysis, and result interpretation. The project PI gave lectures at the Genomic Mapping Workshop organized by USDA-ARS-Southern Plans Area, Oct 25-26, 2006, Lubbock, TX, which was attended by 60 ARS and university scientists. The research findings will be presented at the 2007 Annual ASA/CSSA/SSSA meeting and the Plant and Animal Genome XVI Conference. Dr. Chengsong Zhu was hired as a postdoctoral research associate in Feb 2007 to continue the work. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Association mapping is now being carried out in many different plant and animal species. Given the nature of the germplasm pertinent to association studies, many questions have been raised, such as the size of an association mapping panel, the number of background markers to be scored for a robust genetic relatedness measurement, and whether SSR markers can be used for association mapping. The current project provides general guidelines to these questions and statistical methods for complex trait dissection through association mapping in a wide range of plant and animal species. Besides conducting relevant research, we are in a process of reviewing the progress and prospects of association mapping.
Publications
- 1. Bernardo, R., and J. Yu. 2007. Prospects for genome-wide selection for quantitative traits in maize. Crop Science 47:1082-1090.
- 2. Stich, B., J. Yu, A.E. Melchinger, H.-P. Piepho, H.F. Utz, H.P. Maurer, and E.S. Buckler. 2007. Power to detect high-order epistatic interactions in a metabolic pathway using a new mapping strategy. Genetics 176:563-570.
- 3. Yang, X.H., J.B. Yan, Y.P. Zheng, J. Yu, and J.S. Li. 2007 Reviews of association analysis of quantitative traits in plants. Acta Agronomica Sinica 33:523-530.
- 4. Tabanao, D., J. Yu, and R. Bernardo. 2007. Multilocus epistasis, linkage, and genetic variance in breeding populations with few parents. Theoretical and Applied Genetics 115:335-342.
- 5. Ersoz, E., J. Yu, and E.S. Buckler. 2007. Applications of linkage disequilibrium and association mapping in crop plants. In R. Varshney and R. Tuberosa (ed.) Genomics-Assisted Crop Improvement: Vol 1: Genomics Approaches and Platforms, 97-120. Springer Verlag.
- 6. M.L. Wang, J. Erpelding, J. Yu, G.A. Pederson. 2007. Mining genetic diversity of sweet sorghum in the US collection for biofuel production. 2007 Annual Meeting of ASPB.
- 7. J. Yu, R. Bernardo, E.S. Buckler. 2007. Mixed model in genomic mapping and genome-wide selection. 19th Conference on Applied Statistics in Agriculture, Manhattan, KS.
- 8. G. Pressoir, J. Yu, Z. Zhang, E.S. Buckler, and S. Kresovich. 2007. The genetics of complex traits. 49th Annual Maize Genetics Conference. p 138.
- 9. Yu, J., D. Tabanao, Z. Zhang, G. Pressoir, S. Kresovich, and E. Buckler. 2007. Experimental design in association mapping with diverse germplasm. Plant and Animal Genome XV Conference, San Diego, California.
- 10. Tabanao, D., J. Yu, and R. Bernardo. 2007. Multilocus epistasis, linkage, and genetic variance in breeding populations with few parents. Plant and Animal Genome XV Conference, San Diego, California.
- 11. Harjes, C.E., J. Yu, J. Holland, M.M. Goodman, M.D. McMullen, T. Rocheford, E.S. Buckler. 2007. Improving the potential contribution of QTL to applied breeding programs with diversity based high resolution quantitative trait dissection. Plant and Animal Genome XV Conference, San Diego, California.
- 12. Yu, J., D. Tabanao, Z. Zhang, G. Pressoir, S. Kresovich, and E. Buckler. 2006. Association mapping with diverse germplasm. 2006 Annual ASA/CSSA/SSSA Meeting.
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