A maximum likelihood-based method for mining major genes affecting a quantitative character

In this article, we present a maximum likelihood-based analytical approach for detecting a major gene of large effect on a quantitative trait in a pro geny population derived from a mating design. Our analysis is based on a mi xed genetic model specifying both major gene and background polygenic inher itance. The likelihood of the data is formulated by combining the informati on about population behaviors of the major gene during hybridization and it s phenotypic distribution densities. The EM algorithm is implemented to obt ain maximum likelihood estimates for population and quantitative genetic pa rameters of the major locus. This approach is applied to detect an overdomi nant gene governing stein volume growth in a factorial mating design of asp en trees. It is suggested that further molecular genetic research toward ma pping single genes affecting aspen growth and production based on the same experimental data has a high probability of success.