EvolQG - An R package for evolutionary quantitative genetics

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification.

Heritability of floral volatiles and pleiotropic responses to artificial selection in Brassica rapa

The evolution of the vast diversity of floral volatiles is little understood, although they serve fundamental functions, such as pollinator attraction and herbivore deterrence. Floral volatiles are often species specific, yet highly variable and sensitive to environmental factors. To date, nothing is known about the heritability of floral volatiles, and whether individual compounds can evolve independently or solely in concert with the whole volatile bouquet. We conducted bi-directional artificial selection on four target floral volatiles to estimate heritability and correlated pleiotropic responses in the wild turnip (Brassica rapa). The realized heritability of the four target volatiles ranged from 20% to 45%. The average narrow-sense heritability of all 13 analyzed floral volatiles was 18% based on parent-offspring regressions. There were pleiotropic effects of the selected floral volatile compounds on other constituents of the floral scent bouquet, on flowering time and on some morphological traits. We found that the whole floral scent bouquet changed, even when there was selection only on single compounds, with the overall phenotypic covariance being unaffected. Our study demonstrates that floral scent can evolve rapidly under phenotypic selection, but with additional correlated responses in traits that are not direct targets of selection.

Evolution of morphological integration in the skull of Carnivora (Mammalia): Changes in Canidae lead to increased evolutionary potential of facial traits

Morphological integration refers to the fact that different phenotypic traits of organisms are not fully independent from each other, and tend to covary to different degrees. The covariation among traits is thought to reflect properties of the species' genetic architecture and thus can have an impact on evolutionary responses. Furthermore, if morphological integration changes along the history of a group, inferences of past selection regimes might be problematic. Here, we evaluated the stability and evolution of the morphological integration of skull traits in Carnivora by using evolutionary simulations and phylogenetic comparative methods. Our results show that carnivoran species are able to respond to natural selection in a very similar way. Our comparative analyses show that the phylogenetic signal for pattern of integration is lower than that observed for morphology (trait averages), and that integration was stable throughout the evolution of the group. That notwithstanding, Canidae differed from other families by having higher integration, evolvability, flexibility, and allometric coefficients on the facial region. These changes might have allowed canids to rapidly adapt to different food sources, helping to explain not only the phenotypic diversification of the family, but also why humans were able to generate such a great diversity of dog breeds through artificial selection.

EvolQG - An R package for evolutionary quantitative genetics

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification.

Directional selection effects on patterns of phenotypic (co)variation in wild populations

Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient.

Morphometric variance, evolutionary constraints and their change through time in Late Devonian Palmatolepis conodonts

Phenotypic variation is the raw material of evolution. Standing variation can facilitate response to selection along "lines of least evolutionary resistance", but selection itself might alter the structure of the variance. Shape was quantified using 2D geometric morphometrics in Palmatolepis conodonts through the Late Devonian period. Patterns of variance were characterized along the record by the variance-covariance matrix (P-matrix) and its first axis (Pmax). The Late Frasnian was marked by environmental oscillations culminating with the Frasnian/Famennian mass extinction. A shape response was associated with these fluctuations, together with a deflection of the Pmax and the P-matrix. Thereafter, along the Famennian, Palmatolepis mean shape shifted from broad elements with a large platform to slender elements devoid of platform. This shift in shape was associated with a reorientation of Pmax and the P-matrix, due to profound changes in the functioning of the elements selecting for new types of variants. Both cases provide empirical evidences that moving adaptive optimum can reorient phenotypic variation, boosting response to environmental changes. On such time scales, the question seems thus not to be whether the P-matrix is stable, but how it is varying in response to changes in selection regimes and shifts in adaptive optimum. This article is protected by copyright. All rights reserved.