A quantitative trait locus analysis of personality in wild bighorn sheep

Ecology and Evolution

J. Poissant¹  D. Réale²  J.G.A. Martin³  M. Festa-Bianchet⁴ 

[1] Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK;Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, Québec, Canada;Department of Ecology and Evolutionary Biology, University of California – Los Angeles, Los Angeles, California;Département de Biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada

关键词: Animal model;    behavioral syndrome;    boldness;    docility;    heritability;    temperament;   

DOI  :  10.1002/ece3.468

来源: Wiley

【 摘 要 】

Abstract

Personality, the presence of persistent behav105 ioral differences among individuals over time or contexts, potentially has important ecological and evolutionary consequences. However, a lack of knowledge about its genetic architecture limits our ability to understand its origin, evolution, and maintenance. Here, we report on a genome-wide quantitative trait locus (QTL) analysis for two personality traits, docility and boldness, in free-living female bighorn sheep from Ram Mountain, Alberta, Canada. Our variance component linkage analysis based on 238 microsatellite loci genotyped in 310 pedigreed individuals identified suggestive docility and boldness QTL on sheep chromosome 2 and 6, respectively. A lack of QTL overlap indicated that genetic covariance between traits was not modulated by pleiotropic effects at a major locus and may instead result from linkage disequilibrium or pleiotropic effects at QTL of small effects. To our knowledge, this study represents the first attempt to dissect the genetic architecture of personality in a free-living wildlife population, an important step toward understanding the link between molecular genetic variation in personality and fitness and the evolutionary processes maintaining this variation.

【 授权许可】

CC BY   
© 2013 The Authors. Ecology and Evolution published by Blackwell Publishing Ltd.

Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.