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Whole genome duplication (WGD), the doubling of the nuclear DNA of a species, contributes to biological innovation by creating genetic redundancy. One mode of WGD is allopolyploidization, wherein each genome from two ancestral species becomes a 'subgenome' of a polyploid descendant species. The evolutionary trajectory of a duplicated gene that arises from WGD is influenced both by natural selection that may favour redundant, new or partitioned functions, and by gene silencing (pseudogenization). Here, we explored how these two phenomena varied over time and within allopolyploid genomes in several allotetraploid clawed frog species (Xenopus). Our analysis demonstrates that, across these polyploid genomes, purifying selection was greatly relaxed compared to a diploid outgroup, was asymmetric between each subgenome, and that coding regions are shorter in the subgenome with more relaxed purifying selection. As well, we found that the rate of gene loss was higher in the subgenome under weaker purifying selection and that this rate has remained relatively consistent over time after WGD. Our findings provide perspective from recently evolved vertebrates on the evolutionary forces that likely shape allopolyploid genomes on other branches of the tree of life. [ABSTRACT FROM AUTHOR]

Lateral gene transfer is an important mechanism for evolution among bacteria. Here, genome-wide gene insertion and deletion rates are modeled in a maximum-likelihood framework with the additional flexibility of modeling potential missing data. The performance of the models is illustrated using simulations and a data set on gene family phyletic patterns from Gardnerella vaginalis that includes an ancient taxon. A novel application involving pseudogenization/genome reduction magnitudes is also illustrated, using gene family data from Mycobacterium spp. Finally, an R package called indelmiss is available from the Comprehensive R Archive Network at https://cran.r-project.org/package=indelmiss, with support documentation and examples. [ABSTRACT FROM AUTHOR]

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness have received much attention in the model-based clustering literature recently, we investigate the use of a distribution that can deal with both varying tail-weight and peakedness of data. A family of parsimonious models is proposed using an eigen-decomposition of the scale matrix. A generalized expectation-maximization algorithm is presented that combines convex optimization via a minorization-maximization approach and optimization based on accelerated line search algorithms on the Stiefel manifold. Lastly, the utility of this family of models is illustrated using both toy and benchmark data. [ABSTRACT FROM AUTHOR]

Continuous-time Markov chain models with finite state space are routinely used for analysis of discrete character data on phylogenetic trees. Examples of such discrete character data include restriction sites, gene family presence/absence, intron presence/absence and gene family size data. While models with constrained substitution rate matrices have been used to good effect, more biologically realistic models have been increasingly implemented in the recent literature combining, e.g., site rate variation, site partitioning, branch-specific rates, allowing for nonstationary prior root probabilities, correcting for sampling bias, etc. to name a few. Here, a flexible and fast R package is introduced that infers evolutionary rates of discrete characters on a tree within a probabilistic framework. The package, markophylo, fits maximum-likelihood models using Markov chains on phylogenetic trees. The package is efficient, with the workhorse functions written in C++ and the interface in user-friendly R. [ABSTRACT FROM AUTHOR]