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

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Show simple item record Wang, Shichen Wong, Debbie Forrest, Kerrie Allen, Alexandra Chao, Shiaoman Huang, Bevan E. Maccaferri, Marco Salvi, Silvio Milner, Sara G. Cattivelli, Luigi Mastrangelo, Anna M. Whan, Alex Stephen, Stuart Barker, Gary Wieseke, Ralf Plieske, Joerg International Wheat Genome Sequencing Consortium Lillemo, Morten Mather, Diane Appels, Rudi Dolferus, Rudy Brown-Guedira, Gina Korol, Abraham Akhunova, Alina Feuillet, Catherine Salse, Jerome Morgante, Michele Pozniak, Curtis Luo, Ming-Cheng Dvorak, Jan Morell, Matthew Dubcovsky, Jorge Ganal, Martin Tuberosa, Roberto Lawley, Cindy Mikoulitch, Ivan Cavanagh, Colin Edwards, Keith J. Hayden, Matthew Akhunov, Eduard D. 2014-10-01T18:34:34Z 2014-10-01T18:34:34Z 2014-10-01
dc.description.abstract High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between 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 geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide 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. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 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. en_US
dc.language.iso en_US en_US
dc.relation.uri en_US
dc.rights This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. en_US
dc.subject Single nucleotide polymorphism en_US
dc.subject Polyploid wheat en_US
dc.subject Wheat iSelect array en_US
dc.subject Genotyping en_US
dc.subject High-density map en_US
dc.subject Genetic diversity en_US
dc.title Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array en_US
dc.type Article (publisher version) en_US 2014 en_US
dc.citation.doi doi:10.1111/pbi.12183 en_US
dc.citation.epage 796 en_US
dc.citation.issue 6 en_US
dc.citation.jtitle Plant Biotechnology Journal en_US
dc.citation.spage 787 en_US
dc.citation.volume 12 en_US
dc.contributor.authoreid wangsc en_US
dc.contributor.authoreid akhunova en_US
dc.contributor.authoreid eakhunov en_US

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