Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

Abundant Genetic Variation plus Strong Selection = Multivariate Genetic Constraints: A Geometric View of Adaptation

Evolutionary biology has struggled to explain the coexistence of two basic observations: Genetic variation is found in almost all traits in the presence of strong natural and sexual selection in natural populations. These two observations are in direct conflict as such selection should deplete genetic variation. Furthermore, the presence of genetic variation in a trait, and selection acting on that trait, is often not sufficient for the trait to respond to selection. Here, we bring together geometric perspectives on mutation, selection, and genetic variation and show how the perceived incompatibility between these two observations is a consequence of taking a trait-by-trait approach to the multivariate problem of genetic variation and selection. We conclude that the simultaneous presence of widespead genetic variation in, and strong selection on, individual traits indicates that substantial multivariate genetic constraints are likely to be present in natural populations

The diversification of mate preferences by natural and sexual selection

The evolution of sexual display traits or preferences for them in response to divergent natural selection will alter sexual selection within populations, yet the role of sexual selection in ecological speciation has received little empirical attention. We evolved 12 populations of Drosophila serrata in a two-way factorial design to investigate the roles of natural and sexual selection in the evolution of female mate preferences for male cuticular hydrocarbons (CHCs). Mate preferences weakened in populations evolving under natural selection alone, implying a cost in the absence of their expression. Comparison of the vectors of linear sexual selection revealed that the populations diverged in the combination of male CHCs that females found most attractive, although this was not significant using a mixed modelling approach. Changes in preference direction tended to evolve when natural and sexual selection were unconstrained, suggesting that both processes may be the key to initial stages of ecological speciation. Determining the generality of this result will require data from various species across a range of novel environments

A tale of two matrices: Multivariate approaches in evolutionary biology

Two symmetric matrices underlie our understanding of microevolutionary change. The first is the matrix of nonlinear selection gradients (gamma) which describes the individual fitness surface. The second is the genetic variance-covariance matrix (G) that influences the multivariate response to selection. A common approach to the empirical analysis of these matrices is the element-by-element testing of significance, and subsequent biological interpretation of pattern based on these univariate and bivariate parameters. Here, I show why this approach is likely to misrepresent the genetic basis of quantitative traits, and the selection acting on them in many cases. Diagonalization of square matrices is a fundamental aspect of many of the multivariate statistical techniques used by biologists. Applying this, and other related approaches, to the analysis of the structure of gamma and G matrices, gives greater insight into the form and strength of nonlinear selection, and the availability of genetic variance for multiple traits

Predator-induced phenotypic plasticity in tadpoles: extension or innovation?

Phenotypic plasticity, the ability of a trait to change as a function of the environment, is central to many ideas in evolutionary biology. A special case of phenotypic plasticity observed in many organisms is mediated by their natural predators. Here, we used a predator-prey system of dragonfly larvae and tadpoles to determine if predator-mediated phenotypic plasticity provides a novel way of surviving in the presence of predators (an innovation) or if it represents a simple extension of the way noninduced tadpoles survive predation. Tadpoles of Limnodynastes peronii were raised in the presence and absence of predation, which then entered a survival experiment. Induced morphological traits, primarily tail height and tail muscle height, were found to be under selection, indicating that predator-mediated phenotypic plasticity may be adaptive. Although predator-induced animals survived better, the multivariate linear selection gradients were similar between the two tadpole groups, suggesting that predator-mediated phenotypic plasticity is an extension of existing survival strategies. In addition, nonlinear selection gradients indicated a cost of predator-induced plasticity that may limit the ability of phenotypic plasticity to enhance survival in the presence of predators