Measurement of Segregating Behaviors in Experimental Silver Fox Pedigrees
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Strains of silver foxes, selectively bred at the Institute of Cytology and Genetics of the Russian Academy of Sciences, are a well established, novel model for studying the genetic basis of behavior, and the processes involved in canine domestication. Here we describe a method to measure fox behavior as quantitative phenotypes which distinguish populations and resegregate in experimental pedigrees. We defined 50 binary observations that nonredundantly and accurately distinguished behaviors in reference populations and cross-bred pedigrees. Principal-component analysis dissected out the independent elements underlying these behaviors. PC1 accounted for >44% of the total variance in measured traits. This system clearly distinguished tame foxes from aggressive and wildtype foxes. F1 foxes yield intermediate values that extend into the ranges of both the tame and aggressive foxes, while the scores of the backcross generation resegregate. These measures can thus be used for QTL mapping to explore the genetic basis of tame and aggressive behavior in foxes, which should provide new insights into the mechanisms of mammalian behavior and canine domestication.
KeywordsCanidae Vulpes vulpes Interspecies tameness Attack Domestication
We are indebted to Irina V. Pivovarova and Grigory A. Temnykh, two observers of fox behavior from videotapes. We are grateful to Gordon Lark for help and advise. We thank Simon Kizhner for editorial assistance in construction of the fox video library, Tatyana Semenova, Vasiliy Ivaykin, Vera Vladimirova, Tatyana Konovalova, and all the animal keepers at the ICG experimental farm for research assistance; to Sarah Pinkney for help in developing the scoring assay. Research was supported by NIH grants MH069688, EY06855, EY13729, an NIH FIRCA grant # RO3 TW007056 awarded to the University of Utah, grants # 05-04-4837 of the Russian Fund for Basic Research, Program of the Russian Academy of Sciences: “Biodiversity and Genome Dynamics,” and Cornell University VERGE Initiative.
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