The evaluation of evolutionary models on large phylogenetic trees is computationally difficult, but new developments done in our group significantly improved the efficiency of these methods. This was done by introducing new parallelisation strategies to calculate posterior probabilities through Markov chain Monte Carlo (Meyer et al. Bioinfo; https://doi.org/10.1093/bioinformatics/btw712) or by optimizing the likelihood calculations (Meyer et al. PASC; https://doi.org/10.1145/3093172.3093231). Combined with the development of new ways to simplify the calculation of models of codon evolution (e.g. Davydov et al. Bioinfo; https://doi.org/10.1093/bioinformatics/btw632), the approaches that we propose enable the analyses of large scale genomic data within a phylogenetic context.
We have been also actively developing the first genomic resources for several non-model organisms (e.g. plants like Gesneriaceae; Serrano et al. 2017 Appl Plant Sci; http://dx.doi.org/10.3732/apps.1600135) or clownfishes (Marcionetti et al. Mol Ecol Res; to appear in 2018) and these resources will be used to model and analyse the genetic basis of adaptation and speciation.