Identifying single genes of large effect in quantitative traits using best linear unbiased prediction

Abstract

The recent discovery of a major gene for rapid postweaning growth has reinforced the hypothesis that other quantitative continuous traits may be influenced by single genes of large effect. However, most methods for the detection of such genes rely on the discovery of multimodality in the population frequency distribution. The complicating effects of environment and artificial selection make the identification of such genes with field-collected data a formidable problem. An index is proposed that may serve as an indicator that a major gene is segregating within a population. The index is based on the assumption that under polygenic inheritance, an offspring's deviation from the midparent average is smaller than the deviation from either parent. Whereas, for the Mendelian segregation of a major gene, the opposite would be expected. A proposed class of indices is then based on the ratio [O - .5(S + D)]k/([O - S]k/2 [O - D]k/2) where O, S and D are the additive genetic values of an offspring and its sire and dam estimated via best linear unbiased prediction. Values of the index greater than 1. would be indicative of major gene inheritance. Simulation of small populations indicates that the index is quite sensitive to the existence of segregating major genes even in the absence of multimodality of the phenotypic distribution. However, the index remains dependent on the accuracy of genetic value estimation.