Study of the Molecular Basis of Tame and Aggressive Behavior in the Silver Fox Model
International Collaborative Study between
The James A. Baker Institute for Animal Health, Cornell University, USA,
The Institute of Cytology and Genetics, Russian Academy of Sciences, Russia, and
Department of Biology, University of Utah, USA
Behavioral Assignment
Assignment of fox behavioral phenotypes for QTL mapping
Measurement of behavior presents several challenges, particularly in attempting to map the underlying genetic loci. Because behavior is clearly phenotypically complex, it is likely to represent a complex interaction of multiple genetic loci and environmental factors. To identify genes responsible for behavioral variation, it is first highly desirable to identify, among the wide spectrum of behavioral expression, those specific, independent, and presumably simpler aspects that can be measured objectively and quantitatively, and can be demonstrated to be inherited.
To these ends, we developed a high-resolution, objective, quantitative method for behavioral evaluation of fox populations selected for segregating differences in behavior. A comprehensive primary set of objective measures was developed for scoring the physical manifestations of fox behaviorr from videotapes, where they could be monitored simply by their presence or absence. Traits were selected to describe specific fox actions, location in the cage and time spent there, body postures, positions of particular parts of the body, and sounds. Traits requiring subjective interpretation of animal actions (for example “Fox is afraid” or “Fox demonstrates submissive behavior”) were avoided. Initially, traits were tested for informativeness, and the number of factors was reduced to 50 by eliminating traits that either failed to distinguish among the reference populations, or were redundant. Statistical analysis, including principal-components analysis (PCA), was used to dissect out the independent, resegregating traits underlying the phenotypic variation expressed in these multiple correlated observations. List of traits will be available apon publication.
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