Summary: Statistical phylogenetic inference plays an important role in evolutionary biology. The accuracy of phylogenetic methods relies on having suitable models of the evolutionary process. Various tools allow comparisons of candidate phylogenetic models, but assessing the absolute performance of models remains a considerable challenge. We introduce PhyloMAd, a user-friendly application for assessing the adequacy of commonly used models of nucleotide substitution and among-lineage rate variation. Our software implements a fast, likelihood-based method of model assessment that is tractable for analyses of large multi-locus datasets. PhyloMAd provides a means of informing model improvement, or selecting data to enhance the evolutionary signal in phylogenomic analyses. Availability and implementation: PhyloMAd, together with a manual, a tutorial and the source code, are freely available from the GitHub repository github.com/duchene/phylomad.

MOTIVATION: Molecular-clock methods can be used to estimate evolutionary rates and timescales from DNA sequence data. However, different genes can display different patterns of rate variation across lineages, calling for the employment of multiple clock models. Selecting the optimal clock-partitioning scheme for a multigene dataset can be computationally demanding, but clustering methods provide a feasible alternative. We investigated the performance of different clustering methods using data from chloroplast genomes and data generated by simulation. RESULTS: Our results show that mixture models provide a useful alternative to traditional partitioning algorithms. We found only a small number of distinct patterns of among-lineage rate variation among chloroplast genes, which were consistent across taxonomic scales. This suggests that the evolution of chloroplast genes has been governed by a small number of genomic pacemakers. Our study also demonstrates that clustering methods provide an efficient means of identifying clock-partitioning schemes for genome-scale datasets. AVAILABILITY AND IMPLEMENTATION: The code and data sets used in this study are available online at https://github.com/sebastianduchene/pacemaker_clustering_methods CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: In rapidly evolving pathogens, including viruses and some bacteria, genetic change can accumulate over short time-frames. Accordingly, their sampling times can be used to calibrate molecular clocks, allowing estimation of evolutionary rates. Methods for estimating rates from time-structured data vary in how they treat phylogenetic uncertainty and rate variation among lineages. We compiled 81 virus data sets and estimated nucleotide substitution rates using root-to-tip regression, least-squares dating and Bayesian inference. RESULTS: Although estimates from these three methods were often congruent, this largely relied on the choice of clock model. In particular, relaxed-clock models tended to produce higher rate estimates than methods that assume constant rates. Discrepancies in rate estimates were also associated with high among-lineage rate variation, and phylogenetic and temporal clustering. These results provide insights into the factors that affect the reliability of rate estimates from time-structured sequence data, emphasizing the importance of clock-model testing. CONTACT: [email protected] or [email protected] information: Supplementary data are available at Bioinformatics online.

UNLABELLED: Genomic evolution is shaped by a dynamic combination of mutation, selection and genetic drift. These processes lead to evolutionary rate variation across loci and among lineages. In turn, interactions between these two forms of rate variation can produce residual effects, whereby the pattern of among-lineage rate heterogeneity varies across loci. The nature of rate variation is encapsulated in the pacemaker models of genome evolution, which differ in the degree of importance assigned to residual effects: none (Universal Pacemaker), some (Multiple Pacemaker) or total (Degenerate Multiple Pacemaker). Here we use a phylogenetic method to partition the rate variation across loci, allowing comparison of these pacemaker models. Our analysis of 431 genes from 29 mammalian taxa reveals that rate variation across these genes can be explained by 13 pacemakers, consistent with the Multiple Pacemaker model. We find no evidence that these pacemakers correspond to gene function. Our results have important consequences for understanding the factors driving genomic evolution and for molecular-clock analyses. AVAILABILITY AND IMPLEMENTATION: ClockstaR-G is freely available for download from github (https://github.com/sebastianduchene/clockstarg).

Abstract Summary: Relaxed molecular clocks allow the phylogenetic estimation of evolutionary timescales even when substitution rates vary among branches. In analyses of large multigene datasets, it is often appropriate to use multiple relaxed-clock models to accommodate differing patterns of rate variation among genes. We present ClockstaR, a method for selecting the number of relaxed clocks for multigene datasets. Availability: ClockstaR is freely available for download at http://sydney.edu.au/science/biology/meep/software/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.