Chips and tags suggest plant-environment interactions differ for two alpine Pachycladon species

Evolutionary Transcriptomics and Proteomics: Insight into Plant Adaptation

Comparative transcriptomics and proteomics (T&P) have brought biological insight into development, gene function, and physiological stress responses. However, RNA-seq and high-throughput proteomics remain underutilised in studies of plant adaptation. These methodologies have created discovery tools with the potential to significantly advance our understanding of adaptive diversification. We outline experimental recommendations for their application. We discuss analysis models and approaches that accelerate the identification of adaptive gene sets and integrate transcriptome, proteome, phenotypic, and environmental data. Finally, we encourage widespread uptake and future developments in T&P that will advance our understanding of evolution and adaptation.

Efficient Recycled Algorithms for Quantitative Trait Models on Phylogenies

We present an efficient and flexible method for computing likelihoods for phenotypic traits on a phylogeny. The method does not resort to Monte Carlo computation but instead blends Felsenstein’s discrete character pruning algorithm with methods for numerical quadrature. It is not limited to Gaussian models and adapts readily to model uncertainty in the observed trait values. We demonstrate the framework by developing efficient algorithms for likelihood calculation and ancestral state reconstruction under Wright’s threshold model, applying our methods to a data set of trait data for extrafloral nectaries across a phylogeny of 839 Fabales species.