Analytical advances alleviate model misspecification in non-Brownian multivariate comparative methods.

Adams and Collyer argue that contemporary multivariate (Gaussian) phylogenetic comparative methods are prone to favouring more complex models of evolution and sometimes rotation invariance can be an issue. Here we dissect the concept of rotation invariance and point out that, depending on the understanding, this can be an issue with any method that relies on numerical instead of analytical estimation approaches. We relate this to the ongoing discussion concerning phylogenetic principal component analysis. Contrary to what Adams and Collyer found, we do not observe a bias against the simpler Brownian motion process in simulations when we use the new, improved, likelihood evaluation algorithm employed by mvSLOUCH, which allows for studying much larger phylogenies and more complex model setups.

A Cautionary Note on "A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies".

Models based on the Ornstein-Uhlenbeck process have become standard for the comparative study of adaptation. Cooper et al. (2016) have cast doubt on this practice by claiming statistical problems with fitting Ornstein-Uhlenbeck models to comparative data. Specifically, they claim that statistical tests of Brownian motion may have too high Type I error rates and that such error rates are exacerbated by measurement error. In this note, we argue that these results have little relevance to the estimation of adaptation with Ornstein-Uhlenbeck models for three reasons. First, we point out that Cooper et al. (2016) did not consider the detection of distinct optima (e.g. for different environments), and therefore did not evaluate the standard test for adaptation. Second, we show that consideration of parameter estimates, and not just statistical significance, will usually lead to correct inferences about evolutionary dynamics. Third, we show that bias due to measurement error can be corrected for by standard methods. We conclude that Cooper et al. (2016) have not identified any statistical problems specific to Ornstein-Uhlenbeck models, and that their cautions against their use in comparative analyses are unfounded and misleading. [adaptation, Ornstein-Uhlenbeck model, phylogenetic comparative method.].

Model Selection Performance in Phylogenetic Comparative Methods Under Multivariate Ornstein-Uhlenbeck Models of Trait Evolution.

The advent of fast computational algorithms for phylogenetic comparative methods allows for considering multiple hypotheses concerning the co-adaptation of traits and also for studying if it is possible to distinguish between such models based on contemporary species measurements. Here we demonstrate how one can perform a study with multiple competing hypotheses using mvSLOUCH by analyzing two data sets, one concerning feeding styles and oral morphology in ungulates, and the other concerning fruit evolution in Ferula (Apiaceae). We also perform simulations to determine if it is possible to distinguish between various adaptive hypotheses. We find that Akaike's information criterion corrected for small sample size has the ability to distinguish between most pairs of considered models. However, in some cases there seems to be bias towards Brownian motion or simpler Ornstein-Uhlenbeck models. We also find that measurement error and forcing the sign of the diagonal of the drift matrix for an Ornstein-Uhlenbeck process influences identifiability capabilities. It is a cliché that some models, despite being imperfect, are more useful than others. Nonetheless, having a much larger repertoire of models will surely lead to a better understanding of the natural world, as it will allow for dissecting in what ways they are wrong. [Adaptation; AICc; model selection; multivariate Ornstein-Uhlenbeck process; multivariate phylogenetic comparative methods; mvSLOUCH.].

Low microbiome diversity in threatened amphibians from two biodiversity hotspots.

Microbial diversity positively influences community resilience of the host microbiome. However, extinction risk factors such as habitat specialization, narrow environmental tolerances, and exposure to anthropogenic disturbance may homogenize host-associated microbial communities critical for stress responses including disease defense. In a dataset containing 43 threatened and 90 non-threatened amphibian species across two biodiversity hotspots (Brazil's Atlantic Forest and Madagascar), we found that threatened host species carried lower skin bacterial diversity, after accounting for key environmental and host factors. The consistency of our findings across continents suggests the broad scale at which low bacteriome diversity may compromise pathogen defenses in species already burdened with the threat of extinction.

Increased superfetation precedes the evolution of advanced degrees of placentotrophy in viviparous fishes of the family Poeciliidae.

The causes and consequences of the evolution of placentotrophy (post-fertilization nutrition of developing embryos of viviparous organisms by means of a maternal placenta) in non-mammalian vertebrates are still not fully understood. In particular, in the fish family Poeciliidae there is an evolutionary link between placentotrophy and superfetation (ability of females to simultaneously bear embryos at distinct developmental stages), with no conclusive evidence for which of these two traits facilitates the evolution of more advanced degrees of the other. Using a robust phylogenetic comparative method based on Ornstein-Uhlenbeck models of adaptive evolution and data from 36 poeciliid species, we detected a clear causality pattern. The evolution of extensive placentotrophy has been facilitated by the preceding evolution of more simultaneous broods. Therefore, placentas became increasingly complex as an adaptive response to evolutionary increases in the degree of superfetation. This finding represents a substantial contribution to our knowledge of the factors that have shaped placental evolution in poeciliid fishes.

In Vivo Forward Genetic Screen to Identify Novel Neuroprotective Genes in Drosophila melanogaster.

There is much to understand about the onset and progression of neurodegenerative diseases, including the underlying genes responsible. Forward genetic screening using chemical mutagens is a useful strategy for mapping mutant phenotypes to genes among Drosophila and other model organisms that share conserved cellular pathways with humans. If the mutated gene of interest is not lethal in early developmental stages of flies, a climbing assay can be conducted to screen for phenotypic indicators of decreased brain functioning, such as low climbing rates. Subsequently, secondary histological analysis of brain tissue can be performed in order to verify the neuroprotective function of the gene by scoring neurodegeneration phenotypes. Gene mapping strategies include meiotic and deficiency mapping that rely on these same assays can be followed by DNA sequencing to identify possible nucleotide changes in the gene of interest.

A multispecies coalescent model for quantitative traits.

We present a multispecies coalescent model for quantitative traits that allows for evolutionary inferences at micro- and macroevolutionary scales. A major advantage of this model is its ability to incorporate genealogical discordance underlying a quantitative trait. We show that discordance causes a decrease in the expected trait covariance between more closely related species relative to more distantly related species. If unaccounted for, this outcome can lead to an overestimation of a trait's evolutionary rate, to a decrease in its phylogenetic signal, and to errors when examining shifts in mean trait values. The number of loci controlling a quantitative trait appears to be irrelevant to all trends reported, and discordance also affected discrete, threshold traits. Our model and analyses point to the conditions under which different methods should fare better or worse, in addition to indicating current and future approaches that can mitigate the effects of discordance.