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QTL analysis for secondary traits in maize before and after the genomewide predictions

Breeding for secondary traits has the indirect goal of increasing the grain yield per unit of land used. Ridge regression BLUP method (rrBLUP) calculates the phenotypic effect of markers in the population. Estimates of phenotype having only a single variance component (marker effects) besides the intercept (population mean) can be calculated. Using such data for QTL analysis might provide increase in power and precision for detection of genetic factors underlying the trait. In this paper, we present the properties of QTL analysis on rrBLUP estimates compared to analysis with raw, observed data in a maize biparental population.

maize, biparental population ; stepwise regression ; genomewide predictions ; rrBLUP

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