Ontogenetic patterns in heritable variation for body size: using random regression models in a wild ungulate population.
Body size is an important determinant of fitness in many organisms. While size will typically change over the lifetime of an individual, heritable components of phenotypic variance may also show ontogenetic variation. We estimated genetic (additive and maternal) and environmental covariance structures for a size trait (June weight) measured over the first 5 years of life in a natural population of bighorn sheep Ovis canadensis. We also assessed the utility of random regression models for estimating these structures. Additive genetic variance was found for June weight, with heritability increasing over ontogeny because of declining environmental variance. This pattern, mirrored at the phenotypic level, likely reflects viability selection acting on early size traits. Maternal genetic effects were significant at ages 0 and 1, having important evolutionary implications for early weight, but declined with age being negligible by age 2. Strong positive genetic correlations between age-specific traits suggest that selection on June weight at any age will likely induce positively correlated responses across ontogeny. Random regression modeling yielded similar results to traditional methods. However, by facilitating more efficient data use where phenotypic sampling is incomplete, random regression should allow better estimation of genetic (co)variances for size and growth traits in natural populations.
Wilson
Alastair J
AJ
Institute of Evolutionary Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT, United Kingdom. alastair.wilson@ed.ac.uk
Kruuk
Loeske E B
LE
Coltman
David W
DW
D000375:Aging / Q000502:physiology; D000416:Alberta; D000818:Animals; D000835:Animals, Wild / Q000235:genetics*; D001188:Artiodactyla; D049628:Body Size / Q000235:genetics*; D001835:Body Weight; D019143:Evolution, Molecular; D005260:Female; D014644:Genetic Variation; D008425:Maternal Behavior; D008957:Models, Genetic; D020412:Multifactorial Inheritance; D012044:Regression Analysis; D012756:Sheep / Q000235:genetics*