Model misspecification confounds the estimation of rates and exaggerates their time dependency

Impact of the tree prior on estimating clock rates during epidemic outbreaks

Genetic sequencing data of pathogens allow one to quantify the evolutionary rate together with epidemiological dynamics using Bayesian phylodynamic methods. Such tools are particularly useful for obtaining a timely understanding of newly emerging epidemic outbreaks. During the West African Ebola virus disease epidemic, an unusually high evolutionary rate was initially estimated, promoting discussions regarding the potential danger of the strain quickly evolving into an even more dangerous virus. We show here that such high evolutionary rates are not necessarily real but can stem from methodological biases in the analyses. While most analyses of epidemic outbreak data are performed such that these biases may be present, we suggest a solution to overcome these biases in the future.

Bayesian phylogenetics aims at estimating phylogenetic trees together with evolutionary and population dynamic parameters based on genetic sequences. It has been noted that the clock rate, one of the evolutionary parameters, decreases with an increase in the sampling period of sequences. In particular, clock rates of epidemic outbreaks are often estimated to be higher compared with the long-term clock rate. Purifying selection has been suggested as a biological factor that contributes to this phenomenon, since it purges slightly deleterious mutations from a population over time. However, other factors such as methodological biases may also play a role and make a biological interpretation of results difficult. In this paper, we identify methodological biases originating from the choice of tree prior, that is, the model specifying epidemiological dynamics. With a simulation study we demonstrate that a misspecification of the tree prior can upwardly bias the inferred clock rate and that the interplay of the different models involved in the inference can be complex and nonintuitive. We also show that the choice of tree prior can influence the inference of clock rate on real-world Ebola virus (EBOV) datasets. While commonly used tree priors result in very high clock-rate estimates for sequences from the initial phase of the epidemic in Sierra Leone, tree priors allowing for population structure lead to estimates agreeing with the long-term rate for EBOV.

Comment on Rieux and Balloux: calibration from tip-dating can compromise topological accuracy and evolutionary inference

We contribute to the recent review of Rieux & Balloux, 2016, Mol. Ecol., 25, 1911 on inferences from tip-dated phylogenies by developing their discussion on the influence of population size (N_e ) under panmixia for the estimation of substitution rate (μ). We highlight how phylogenetic trees inferred with tip-dated sequences under large panmictic N_e tend to erroneously enforce an age-based coalescent pattern on the posterior distribution of trees, which in turn results in systematically inflated estimates of μ. We discuss the consequences of this and suggest how to accommodate the issue in the short term and long term.

Local Population Structure and Patterns of Western Hemisphere Dispersal for Coccidioides spp., the Fungal Cause of Valley Fever

Coccidioidomycosis (or valley fever) is a fungal disease with high morbidity and mortality that affects tens of thousands of people each year. This infection is caused by two sibling species, Coccidioides immitis and C. posadasii, which are endemic to specific arid locales throughout the Western Hemisphere, particularly the desert southwest of the United States. Recent epidemiological and population genetic data suggest that the geographic range of coccidioidomycosis is expanding, as new endemic clusters have been identified in the state of Washington, well outside the established endemic range. The genetic mechanisms and epidemiological consequences of this expansion are unknown and require better understanding of the population structure and evolutionary history of these pathogens. Here we performed multiple phylogenetic inference and population genomics analyses of 68 new and 18 previously published genomes. The results provide evidence of substantial population structure in C. posadasii and demonstrate the presence of distinct geographic clades in central and southern Arizona as well as dispersed populations in Texas, Mexico, South America, and Central America. Although a smaller number of C. immitis strains were included in the analyses, some evidence of phylogeographic structure was also detected in this species, which has been historically limited to California and Baja, Mexico. Bayesian analyses indicated that C. posadasii is the more ancient of the two species and that Arizona contains the most diverse subpopulations. We propose a southern Arizona-northern Mexico origin for C. posadasii and describe a pathway for dispersal and distribution out of this region.

Coccidioidomycosis, or valley fever, is caused by the pathogenic fungi Coccidioides posadasii and C. immitis. The fungal species and disease are primarily found in the American desert southwest, with spotted distribution throughout the Western Hemisphere. Initial molecular studies suggested a likely anthropogenic movement of C. posadasii from North America to South America. Here we comparatively analyze eighty-six genomes of the two Coccidioides species and establish local and species-wide population structures to not only clarify the earlier dispersal hypothesis but also provide evidence of likely ancestral populations and patterns of dispersal for the known subpopulations of C. posadasii.

Inferences from tip-calibrated phylogenies: a review and a practical guide

Molecular dating of phylogenetic trees is a growing discipline using sequence data to co‐estimate the timing of evolutionary events and rates of molecular evolution. All molecular‐dating methods require converting genetic divergence between sequences into absolute time. Historically, this could only be achieved by associating externally derived dates obtained from fossil or biogeographical evidence to internal nodes of the tree. In some cases, notably for fast‐evolving genomes such as viruses and some bacteria, the time span over which samples were collected may cover a significant proportion of the time since they last shared a common ancestor. This situation allows phylogenetic trees to be calibrated by associating sampling dates directly to the sequences representing the tips (terminal nodes) of the tree. The increasing availability of genomic data from ancient DNA extends the applicability of such tip‐based calibration to a variety of taxa including humans, extinct megafauna and various microorganisms which typically have a scarce fossil record. The development of statistical models accounting for heterogeneity in different aspects of the evolutionary process while accommodating very large data sets (e.g. whole genomes) has allowed using tip‐dating methods to reach inferences on divergence times, substitution rates, past demography or the age of specific mutations on a variety of spatiotemporal scales. In this review, we summarize the current state of the art of tip dating, discuss some recent applications, highlight common pitfalls and provide a ‘how to’ guide to thoroughly perform such analyses.