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Abstract Plasmodium species causing malaria in humans are not monophyletic, sharing common ancestors with nonhuman primate parasites. Plasmodium gonderi is one of the few known Plasmodium species infecting African old-world monkeys that are not found in apes. This study reports a de novo assembled P. gonderi genome with complete chromosomes. The P. gonderi genome shares codon usage, syntenic blocks, and other characteristics with the human parasites Plasmodium ovale s.l. and Plasmodium malariae, also of African origin, and the human parasite Plasmodium vivax and species found in nonhuman primates from Southeast Asia. Using phylogenetically aware methods, newly identified syntenic blocks were found enriched with conserved metabolic genes. Regions outside those blocks harbored genes encoding proteins involved in the vertebrate host-Plasmodium relationship undergoing faster evolution. Such genome architecture may have facilitated colonizing vertebrate hosts. Phylogenomic analyses estimated the common ancestor between P. vivax and an African ape parasite P. vivax-like, within the Asian nonhuman primates parasites clade. Time estimates incorporating P. gonderi placed the P. vivax and P. vivax-like common ancestor in the late Pleistocene, a time of active migration of hominids between Africa and Asia. Thus, phylogenomic and time-tree analyses are consistent with an Asian origin for P. vivax and an introduction of P. vivax-like into Africa. Unlike other studies, time estimates for the clade with Plasmodium falciparum, the most lethal human malaria parasite, coincide with their host species radiation, African hominids. Overall, the newly assembled genome presented here has the quality to support comparative genomic investigations in Plasmodium. 

Abstract Confidence intervals (CIs) depict the statistical uncertainty surrounding evolutionary divergence time estimates. They capture variance contributed by the finite number of sequences and sites used in the alignment, deviations of evolutionary rates from a strict molecular clock in a phylogeny, and uncertainty associated with clock calibrations. Reliable tests of biological hypotheses demand reliable CIs. However, current non-Bayesian methods may produce unreliable CIs because they do not incorporate rate variation among lineages and interactions among clock calibrations properly. Here, we present a new analytical method to calculate CIs of divergence times estimated using the RelTime method, along with an approach to utilize multiple calibration uncertainty densities in dating analyses. Empirical data analyses showed that the new methods produce CIs that overlap with Bayesian highest posterior density intervals. In the analysis of computer-simulated data, we found that RelTime CIs show excellent average coverage probabilities, that is, the actual time is contained within the CIs with a 94% probability. These developments will encourage broader use of computationally efficient RelTime approaches in molecular dating analyses and biological hypothesis testing. 

Abstract Simultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra‐ and interspecies samples (mixed samples). As a result, the phylogenetic trees contain interspecies, interpopulation and within‐population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter‐ and intraspecies branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior on Bayesian divergence time estimates by analysing computer‐simulated data sets. We also examined the effect of the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non‐Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyse data sets containing both populations and species variation when its computational efficiency is needed.