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United States Department of Agriculture

Agricultural Research Service

Research Project: Genetic Improvement of Durum and Spring Wheat for Quality and Resistance to Diseases and Pests

Location: Cereal Crops Research

Title: Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array)

Author
item Wang, Shichen
item Wong, Debbie
item Forrest, Kerrie
item Allen, Alexandra
item Chao, Shiaoman
item Huang, Emma
item Maccaferri, Marco
item Salvi, Silvio
item Milner, Sara
item Cattivelli, Luigi
item Mastrangelo, Anna
item Stephen, Stuart
item Luo, Ming-cheng
item Dvorak, Jan
item Mather, Diane
item Appels, Rudi
item Dulferos, Rudi
item Brown-guedira, Gina
item Akhunova, Alina
item Feuillet, Catherine
item Salse, Jerome
item Morgante, Michele
item Pozniak, Curtis
item Wieseke, Ralf
item Plieske, Joerg
item Morell, Matthew
item Dubcovsky, Jorge
item Ganal, Martin
item Tuberosa, Roberto
item Lawley, Cindy
item Mikoulitch, Ivan
item Cavanagh, Colin
item Edwards, Keith
item Hayden, Matthew
item Akhunov, Eduard
item Whan, A
item Barker, G
item Lillemo, M
item Korol, A

Submitted to: Plant Biotechnology Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/6/2014
Publication Date: 3/1/2014
Publication URL: http://handle.nal.usda.gov/10113/59609
Citation: Wang, S., Wong, D., Forrest, K., Allen, A., Chao, S., Huang, B.E., Maccaferri, M., Salvi, S., Milner, S.G., Cattivelli, L., Mastrangelo, A.M., Whan, A., Stephen, S., Barker, G., Wieseke, R., Plieske, J., International Wheat Genome Sequencing Consortium, Lillemo, M., Mather, D., Appels, R., Dulferos, R., Brown-Guedira, G., Korol, A., Akhunova, A.R., Feuillet, C., Salse, J., Morgante, M., Pozniak, C., Luo, M.-C., Dvorak, J., Morell, M., Dubcovsky, J., Ganal, M., Tuberosa, R., Lawley, C., Mikoulitch, I., Cavanagh, C., Edwards, K.J., Hayden, M., Akhunov, E. 2014. Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnology Journal. 12:787-796.

Interpretive Summary: A resource of 90,000 DNA markers detecting genetic variations at a single nucleotide base level in the wheat genomes was developed that served as a powerful tool for various genetic and breeding applications in polyploid wheat. The objective was to evaluate the utility of this high-density DNA marker tool using the improved software algorithms to facilitate the analysis of complex datasets obtained due to polyploidy nature of the wheat genomes. Wheat samples from diverse geographic areas in the US and elsewhere in the world were surveyed. Similar levels of genetic diversity were detected in samples among different areas, demonstrating the general marker utility applied to the wheat community at large. A total of 46,362 markers were located and placed on each of the 21 wheat chromosomes, that provides road maps for studying genetic architecture underlying important agronomic traits. A protocol on the use of the improved algorithms was prepared and can guide users to correctly obtain high quality marker data for their own studies.

Technical Abstract: High-density single nucleotide polymorphism (SNP) genotyping chips are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships among individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographic origin. We utilized new density-based spatial clustering algorithms to enable high-throughput genotype calling in complex datasets obtained for polyploid wheat. We show that these model-free clustering algorithms can be successfully used for accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. The SNP assays detecting low intensity clusters provided insight into the distribution of presence-absence variation (PAV) in wheat populations and across the polyploid genome. A total of 46,362 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

Last Modified: 8/24/2016
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