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Background In recent years, association mapping studies have been reported for growth and wood quality traits in Eucalyptus (e.g. [1]). One problem with association studies is that they can be sensitive to the presence of population structure. The presence of population structure may generate spurious associations between markers and traits and leading to an elevated false-positive rate (e.g. [2]). Statistical approaches that account for population structure include model-based clustering [3], principal component analysis, genomic control and linear mixed model approach [4]. The mixed model of Yu et al. (2006) accounts for both major population structure, assigning individuals to subpopulations (the Q matrix), and the relatedness among individuals within and between subpopulations (the kinship (K) matrix). The mixed model approach generally performs best [2,4]. As part of the Biotech MERCOSUR project (Marcucci Poltri et al. this volume) molecular and phenotypic data from four Eucalyptus populations have been obtained: three open pollinated (OP, half-sib) progeny trials of Eucalyptus grandis from Argentina (EgrAr) and Eucalyptus globulus from Uruguay (EglUy) and Argentina (EglAr) and one clonal trial of Eucalyptus grandis from Paraguay (EgrPy). These populations differ in the underlying substructure and genetic relatedness among individuals. It is thus important to investigate the effects of population structure and kinship on the results of associations between markers and growth and wood quality traits from these Eucalyptus populations.

bmc proceedings

Effect of population structure and kinship relationships on the results of association mapping tests of growth and wood quality traits in four Eucalyptuspopulations