Title: ``Methods to select for, or map QTLs for, competitive effects in plants or animals''
Speaker: Dr. Bill Muir, Department of Animal Science
Place: LILLY G126; Tuesday, 4:30pm

Abstract

Passive competition among plants or animals occurs as a result of limited resources, such as nutrients, space, light, and water, and results in reduced growth per individual. In addition, active competition may occur among animals for social dominance and peck order. Social interactions can result in serious injuries or death and as such also raise animal well-being concerns. Traditional selection programs to increase yield or growth necessarily results in increased competition unless resources are also increased. In the case of forestry this translates into increased space per tree, and in animals, increased feed and/or space. As a result, yield on a per acre or farm basis may not increase unless competitive effects are decreased. Traditional theories used in plant and animal breeding assume an absence of genotype-genotype interaction. However, in almost all plant or animal breeding programs, interactions (completion) occur. The consequence of which is that use of traditional selection methods may result in greatly impaired response or produce the reverse effect. Expansion of the model to include associative effects of one plant or animal on another allows development of breeding and/or genomics methods address these issues. A mixed model will be discussed in which such effects are estimable if both genetic and physical distances between individuals are known or estimable through band sharing. The results from this model allows estimation and mapping of QTLs for both direct and associative effects. Computer simulation and biological testing with Japanese quail show that in many breeding programs it is more important to reduce associative effects than to improve direct effects. Because of the complexity of such analysis, direct selection on QTL's for associative effects would be very beneficial.