Effect of small mapping population sizes on reliability of quantitative trait locus (QTL) mapping

Abstract

A limitation of quantitative trait loci (QTL) mapping is that accuracy of determining QTL position and effects  are largely determined by population size. Despite the importance of this concept, known as the "Beavis effect  there has generally been a lack of understanding by molecular geneticists and breeders. One possible  explanation for this may be that this concept has been explored by using computer simulations and that these  findings may not be clearly understood. In this study, we demonstrated the effect of population size on the  accuracy of determining QTL positions and effects in a simple and concise manner. Simulated data was  generated for extremely large mapping populations (n = 1000) and smaller mapping populations (n = 94 or n = 190) were obtained by random sampling. Populations were defined to segregate for either three or five QTLs with heritabilities of h² = 0.75 or h² = 0.50. When small populations were used, errors were detected in determining QTL positions, and in some cases, QTLs were not detected (that is, false negatives) especially when h² = 0.50. More importantly, R2 values were overestimated or underestimated. Composite interval  mapping was more reliable for detecting QTLs compared to simple interval mapping. These findings have  important implications for QTLs which are selected in breeding programs via marker-assisted selection.

Key words: Quantitative trait loci (QTL) mapping, Beavis effect, population size, confidence intervals, marker-assisted selection.