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With a training background in Plant Breeding, Quantitative Genetics, Genomics, and Statistics, my general research interests have been focused on Complex Trait Dissection, explaining phenotypic variation with molecular variation.
Specific research interests include: Association Mapping, Joint Linkage and Linkage Disequilibrium Mapping, Breeding Methodology, Marker-assisted Breeding, Genotype by Environment Interaction; Heterosis, Metabolic Control Analysis, Microarray, Experiment Design, Mixed Model, QTL/eQTL mapping; Genetic Modeling and Computer Simulation.
Current Projects: Genomic Analyses of Shoot Meristem Function in Maize by National Science Foundation Plant Genome Program (2008-2012). Summary: We are conducting QTL-directed candidate-gene NAM analysis to identify natural variations related with maize leaf traits (leaf length, leaf width, and leaf angle). Nested association mapping (NAM) strategy, combining the advantages of linkage analysis (robust and low marker density demand) and association mapping (high resolution and rich allelic diversity), provides a high-resolution and cost-effective approach to dissecting the genetic architecture of complex traits. A maize NAM population comprising 5000 recombinant inbred lines (RILs) has been developed by crossing 25 diverse founders with a common parent (B73). With genotyping data from 1106 B73 common-parent-specific (CPS) SNPs across 5000 RILs, about 100 QTLs related with three leaf traits (i.e., leaf length, leaf width, and upper leaf angle) were mapped by multi-population linkage analysis. Based on the genomic sequence of B73, we plan to select 200 candidate genes with purported function in leaf shape, shoot apical meristem, cell growth, and phytohormone biosynthesis, from the mapped QTL-peak regions. The target DNA of the chosen genes will be enriched by a custom hybridization-mediated microarray method for 25 founders and the resulting fragments will be deeply sequenced by a next generation sequencing platform to identify candidate gene SNPs. Information of the candidate gene SNPs will then be projected to each RIL from founder alleles based on CPS SNPs. Final association analysis will be performed across 5000 RILs to identify genes underlying the natural variation of the maize leaf traits.
Genetic and Statistical Aspects of Association Mapping by the National Research Initiative (NRI) Plant Genome Program of the USDA-CSREES (2006-2009). Summary: Vast amounts of currently available genome information have not been fully utilized to significantly improve plant breeding. While this failure is attributable, in part, to the success of existing breeding methods, much of our genome resources go untapped due to poor connections linking genomic technology and breeding methodology. Association mapping holds great promise for the dissection of complex traits. However, little effort has been made to develop robust methods of association mapping in plant species when compared to the well developed methods in linkage analysis. We propose to develop genetic and statistical methods for dissecting complex agronomic and physiological traits, as well as design improved genomic-aided selection strategies for plant breeding. Comprehensive computer modeling and information-driven methodology development will be conducted with data from association studies in multiple crop species. Ultimately, new insights gained from the dissection of complex traits will not only facilitate future dissection, but also help to develop new genomic-aided breeding methods for crop improvement.
The Sorghum Translational Genomics Program: Mining Genomic Diversity for Sorghum Improvement by Targeted Excellence program of Kansas State University (2007-2010). Summary: The Sorghum Translational Genomics Program, in concert with the Center for Sorghum Improvement at K-State, will create a deep set of genomically characterized sorghum germplasm resources, identify candidate genes for key economic traits, and build a bioinformatics core and WWW portal for the statistical analysis and archiving of data and the dissemination of results and analytical tools. We will identify 250,000 SNPs in eight sorghum lines representing much of the genetic diversity in the species; assay the full set on 22 parents, and assay a subset of 1536 on a 350-line Diversity Panel and 800 lines developed for “association mapping”. All this material will be evaluated for grain quality, drought tolerance, and biofuel traits.
Sorghum Genomics for Bioenergy Summary: Sorghum has been strategically positioned as one of the twelve “dedicated” bioenergy crops by DOE due to its superior water-use efficiency and adaptation to various abiotic stresses. Among all seven biomass crops recommended by DOE for Kansas, sorghum is the only crop for which the existing research capacity and the production system can be readily adapted for the new biomass-related research and production. Research in sorghums biomass production has been limited in the past. Sweet sorghum produces sugar-rich stalks and has a high biomass potential. The sugar extracted from stalk juice can be fermented for ethanol production. Alternatively, the biomass potential of sweet sorghum can be realized in hybrids for dry matter production by crossing it with non-sweet type. We have assembled a sweet sorghum panel of 280 lines. Together with collaborators (Wang and Erpelding, USDA-ARS), we are conducting field evaluation of this diverse collection for Brix, biomass, and a suite of agronomy traits at Manhattan and Puerto Rico. We plan to fingerprint the sweet diversity panel with 100 SSR markers. The data will be used for genetic structure analysis of sweet sorghum, and will be combined with data from the general sorghum diversity panel to infer the origin of sweetness. This will provide critical germplasm information for genetic improvement of sorghum biomass through selection, introgression, and hybrid development. |
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