A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes.
Bottom Line: However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time.While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models.After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes.
Affiliation: Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.Show MeSH
Mentions: We first applied interval mapping by Haley–Knott regression (Haley and Knott 1992), considering each time point individually. The results are displayed in Figure 1, with the x-axis representing genomic position and the y-axis representing time, and so each horizontal slice is a genome scan for one time point. We plot a signed LOD score, with the sign representing the estimated direction of the QTL effect: Red indicates that lines with the Cvi allele had a higher phenotype average than the lines with the Ler allele; blue indicates that lines with the Ler allele had a higher phenotype average than the lines with the Cvi allele.
Affiliation: Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.