Population structure in cultivated lettuce and its impact on association mapping

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Abstract

The association mapping technique is a useful tool for detecting markers linked to the genes underlying the variation of a trait among elite cultivars. To avoid false-positive results due to unrecognized population structure in the analyzed set of individuals, the subpopulations need to be identified. Fifty-four lettuce (Lactuca sativa L.) cultivars representing five horticultural types important in North America, together with six accessions from two wild species (Lactuca saligna L. and Lactuca serriola L.), were assayed for polymorphism with target region amplified polymorphism (TRAP) marker loci. The model-based clustering approach recognized three main subpopulations in cultivated lettuce that are well separated from wild species. Although the clustering based on molecular markers was generally in good agreement with horticultural types, some cultivars were classified differently or showed mixed origin. The effect of population structure on association mapping was tested on four traits with strong or weak correlation to the lettuce horticultural type and monogenic or polygenic mode of inheritance. Traits that were strongly correlated with lettuce types displayed many false-positive results when population structure was ignored, but the spurious associations disappeared when estimates of population structure or relative kinship (both based on molecular markers) were included in the statistical model. Using of horticultural types as covariate was not sufficient to control for spurious associations in the monogenic trait with strong correlation to lettuce types. The best approach to avoid spurious associations in lettuce association studies is to assess relatedness of accessions with molecular markers and to include this information into the statistical model.

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APA

Simko, I., & Hu, J. (2008). Population structure in cultivated lettuce and its impact on association mapping. Journal of the American Society for Horticultural Science, 133(1), 61–68. https://doi.org/10.21273/jashs.133.1.61

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