The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms...

A simulation study investigating relative errors and sampling variances of reduced rank estimates of genetic covariance functions from random regression analyses estimating the leading principal components only, is presented. The example considered pertains to covariance functions for growth of beef cattle. It is demonstrated that the leading principal components are estimated most accurately, ...

The evolutionary trajectories of reproductive systems, including both male and female multiple mating and hence polygyny and polyandry, are expected to depend on the additive genetic variances and covariances in and among components of male reproductive success achieved through different reproductive tactics. However, genetic covariances among key components of male reproductive success have no...

Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ong...

One specific hypothesis explaining the evolution of extra-pair reproduction (EPR) by socially monogamous females is that EPR is under indirect selection because extra-pair offspring (EPO) sired by extra-pair males have higher additive genetic value for fitness than the within-pair offspring (WPO) a female would have produced had she solely mated with her socially paired male. This hypothesis ha...

Although divergent natural selection is common in nature, the extent to which genetic constraints bias evolutionary trajectories in its presence remains largely unknown. Here we develop a general framework to integrate estimates of divergent selection and genetic constraints to estimate their contributions to phenotypic divergence among natural populations. We apply these methods to estimates o...

Using quantitative genetic research designs, we decomposed phenotypic variance in P300 parameters into genetic and environmental components. The twin method was used to carry out this decomposition. Event related potentials (ERPs) were measured during a visual oddball paradigm in a sample of 213 adolescent twin pairs. The presence of male and female same-sex and opposite-sex twins in the sample...

Advanced variance-covariance structures are commonly used in genetic evaluation of crops to account for micro-site variability and achieve higher accuracy of predictions to increase selection efficiency. Various genetic variance-covariance structures were explored to predict best linear unbiased genetic merits of 453 loblolly pine (Pinus taeda L.) cloned progeny tested at 16 different locations...

Eigenvalues and eigenvectors of covariance matrices are important statistics for multivariate problems in many applications, including quantitative genetics. Estimates of these quantities are subject to different types of bias. This article reviews and extends the existing theory on these biases, considering a balanced one-way classification and restricted maximum-likelihood estimation. Biases ...