Literature DB >> 17033786

Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome.

Mona Akbari1, Peter Wenzl, Vanessa Caig, Jason Carling, Ling Xia, Shiying Yang, Grzegorz Uszynski, Volker Mohler, Anke Lehmensiek, Haydn Kuchel, Mathew J Hayden, Neil Howes, Peter Sharp, Peter Vaughan, Bill Rathmell, Eric Huttner, Andrzej Kilian.   

Abstract

Despite a substantial investment in the development of panels of single nucleotide polymorphism (SNP) markers, the simple sequence repeat (SSR) technology with a limited multiplexing capability remains a standard, even for applications requiring whole-genome information. Diversity arrays technology (DArT) types hundreds to thousands of genomic loci in parallel, as previously demonstrated in a number diploid plant species. Here we show that DArT performs similarly well for the hexaploid genome of bread wheat (Triticum aestivum L.). The methodology previously used to generate DArT fingerprints of barley also generated a large number of high-quality markers in wheat (99.8% allele-calling concordance and approximately 95% call rate). The genetic relationships among bread wheat cultivars revealed by DArT coincided with knowledge generated with other methods, and even closely related cultivars could be distinguished. To verify the Mendelian behaviour of DArT markers, we typed a set of 90 Cranbrook x Halberd doubled haploid lines for which a framework (FW) map comprising a total of 339 SSR, restriction fragment length polymorphism (RFLP) and amplified fragment length polymorphism (AFLP) markers was available. We added an equal number of DArT markers to this data set and also incorporated 71 sequence tagged microsatellite (STM) markers. A comparison of logarithm of the odds (LOD) scores, call rates and the degree of genome coverage indicated that the quality and information content of the DArT data set was comparable to that of the combined SSR/RFLP/AFLP data set of the FW map.

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Year:  2006        PMID: 17033786     DOI: 10.1007/s00122-006-0365-4

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


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