Population structure revealed by different marker types (SSR or DArT) has an impact on the results of genome-wide association mapping in European barley cultivars

I.E. Matthies, T.J.L. van Hintum, S. Weise, M.S. Röder

    Research output: Contribution to journalArticleAcademicpeer-review

    31 Citations (Scopus)

    Abstract

    Diversity arrays technology (DArT) and simple sequence repeat (SSR) markers were applied to investigate population structure, extent of linkage disequilibrium and genetic diversity (kinship) on a genome-wide level in European barley (Hordeum vulgare L.) cultivars. A set of 183 varieties could be clearly distinguished into spring and winter types and was classified into five subgroups based on 253 DArT or 22 SSR markers. Despite the fact, that the same number of groups was revealed by both marker types, it could be shown that this grouping was more distinct for the SSRs than the DArTs, when assigned to a Q-matrix by STRUCTURE. This was supported by the findings from principal coordinate analysis, where the SSRs showed a better resolution according to seasonal habit and row number than the DArTs. A considerable influence on the rate of significant associations with malting and kernel quality parameters was revealed by different marker types in this genome-wide association study using general and mixed linear models considering population structure. Fewer spurious associations were observed when population structure was based on SSR rather than on DArT markers. We therefore conclude that it is advisable to use independent marker datasets for calculating population structure and for performing the association analysis.
    Original languageEnglish
    Pages (from-to)951-966
    JournalMolecular Breeding
    Volume30
    Issue number2
    DOIs
    Publication statusPublished - 2012

    Keywords

    • different germplasm groups
    • multilocus genotype data
    • doubled-haploid progeny
    • simple sequence repeats
    • malting-quality
    • linkage disequilibrium
    • genetic diversity
    • qtl analysis
    • yield components
    • spring barley

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