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Stripe rust resistance pyramids in barley Public Deposited

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  • Genetic resistance is the most appropriate way to control diseases in crop plants. Resistance can be described as qualitative (involving a gene-for-gene system) or quantitative (with continuous distribution of disease levels). The relationships between different types of resistance remain obscure, as does the genetics of quantitative traits. The use of quantitative trait locus (QTL) analysis tools for dissecting such traits has raised concerns regarding bias in QTL estimation and lack of QTL validation. We report data for barley (Hordeum vulgare L. subsp. vulgare) and barley stripe rust (BSR, caused by Puccinia striformis f.sp. hordei) that contribute to understand the relationships between different types of disease resistance, and of the utility of QTL analysis tools for studying and manipulating the genetic determinants of complex traits. BSR is an important disease of barley. Using QTL mapping and logistic regression we mapped BSR seedling resistance QTL on chromosomes 5(1H) and 6(6H) in the cultivar Shyri that showed complementary gene action. We also mapped one qualitative BSR resistance gene on chromosome 1(7H) in the accession C110587 (BSTR1). We developed a pyramid of previously mapped BSR resistance QTL alleles on chromosomes 4(4H) (QTL4), 5(IH) (QTL5) and 7(5H) (QTL7), and pyramids of BSTR1 with QTL4 and QTL5 (two populations), and of BSTR1 with QTL5 (one population). These populations provided independent estimates of QTL effects and interactions. The results validated QTL effect estimates for the three QTL in the first resistance gene pyramid and for QTL4 and QTL5 in the other three pyramids. These studies confirmed the additivity of the QTL effects and the limited importance of QTL x QTL interactions. The original QTL estimates were biased. QTL estimates obtained from the first resistance gene pyramid provided better estimates of QTL effects. These studies also validated the coincidental seedling resistance effects on QTL4 and QTL5 as well as the statistical procedure used for their estimation. The presence of a resistance allele from C110587 precluded the detection of significant QTL effects, but in the absence of the qualitative resistance gene, they lead to resistance. Our results suggest that QTL analysis can help to understand and manipulate genes underlying quantitative traits of biological and economical importance.
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