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Alastair J Wilson

Publications and source records attributed to Alastair J Wilson.

4 recordsLinked to original sources

Ontogeny of additive and maternal genetic effects: lessons from domestic mammals.

Evolution of size and growth depends on heritable variation arising from additive and maternal genetic effects. Levels of heritable (and nonheritable) variation might change over ontogeny, increasing through "variance compounding" or decreasing through "compensatory growth." We test for these processes using a meta-analysis of age-specific weight traits in domestic ungulates. Generally, mean standardized variance components decrease with age, consistent with compensatory growth. Phenotypic convergence among adult sheep occurs through decreasing environmental and maternal genetic variation. Maternal variation similarly declines in cattle. Maternal genetic effects are thus reduced with age (both in absolute and relative terms). Significant trends in heritability (decreasing in cattle, increasing in sheep) result from declining maternal and environmental components rather than from changing additive variation. There was no evidence for increasing standardized variance components. Any compounding must therefore be masked by more important compensatory processes. While extrapolation of these patterns to processes in natural population is difficult, our results highlight the inadequacy of assuming constancy in genetic parameters over ontogeny. Negative covariance between direct and maternal genetic effects was common. Negative correlations with additive and maternal genetic variances indicate that antagonistic pleiotropy (between additive and maternal genetic effects) may maintain genetic variance and limit responses to selection.

Aging↗

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.

Aging↗

The potential costs of accounting for genotypic errors in molecular parentage analyses.

Genotypic errors, whether due to mutation or laboratory error, can cause the genotypes of parents and their offspring to appear inconsistent with Mendelian inheritance. As a result, molecular parentage analyses are expected to benefit when allowances are made for the presence of genotypic errors. However, a cost of allowing for genotypic errors might also be expected under some analytical conditions, primarily because parentage analyses that assume nonzero genotypic error rates can neither assign nor exclude parentage with certainty. The goal of this work was therefore to determine whether or not such costs might be important under conditions relevant to parentage analyses, particularly in natural populations. Simulation results indicate that the costs may often outweigh the benefits of accounting for nonzero error rates, except in situations where data are available for many marker loci. Consequently, the most powerful approach to handling genotypic errors in parentage analyses might be to apply likelihood equations with error rates set to values substantially lower than the rates at which genotypic errors occur. When applying molecular parentage analyses to natural populations, we advocate an increased consideration of optimal strategies for handling genotypic errors. Currently available software packages contain procedures that can be used for this purpose.

Computer Simulation↗

Selection on mothers and offspring: whose phenotype is it and does it matter?

Reproductive and early life-history traits can be considered aspects of either offspring or maternal phenotype, and their evolution will therefore depend on selection operating through offspring and maternal components of fitness. Furthermore, selection at these levels may be antagonistic, with optimal offspring and maternal fitness occurring at different phenotypic values. We examined selection regimes on the correlated traits of birth weight, birth date, and litter size in Soay sheep (Ovis aries) using data from a long-term study of a free-living population on the archipelago of St. Kilda, Scotland. We tested the hypothesis that selective constraints on the evolution of the multivariate phenotype arise through antagonistic selection, either acting at offspring and maternal levels, or on correlated aspects of phenotype. All three traits were found to be under selection through variance in short-term and lifetime measures of fitness. Analysis of lifetime fitness revealed strong positive directional selection on birth weight and weaker selection for increased birth date at both levels. However, there was also evidence for stabilizing selection on these traits at the maternal level, with reduced fitness at high phenotypic values indicating lower phenotypic optima for mothers than for offspring. Additionally, antagonistic selection was found on litter size. From the offspring's point of view it is better to be born a singleton, whereas maternal fitness increases with average litter size. The decreased fitness of twins is caused by their reduced birth weight; therefore, this antagonistic selection likely results from trade-offs between litter size and birth weight that have different optimal resolutions with respect to offspring and maternal fitness. Our results highlight how selection regimes may vary depending on the assignment of reproductive and early life-history traits to either offspring or maternal phenotype.

Animals↗