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New phylogenetic methods for inferring complex population dynamics

Final Report Summary - PHYPD (New phylogenetic methods for inferring complex population dynamics)

The field of phylogenetics is undergoing an important change over recent time. For a long time phylogenetics focussed on describing the species tree as accurate as possible. More recently there is a shift towards a functional inference of the evolutionary process itself, i.e. researchers attempt to infer what processes are most likely responsible for the particular pattern of branching observed in a given phylogeny.

Phylogenetics has traditionally been developed for macroevolution. In this context, we first assessed what process of macroevolution, in particular what aspects about speciation and extinction, can be learnt based on phylogenetic trees. While such analyses can raise hypotheses such as speciation rates may be a function of species age, we realized that in order to not only raise hypotheses but to provide strong evidence for hypotheses, we need to combine phylogenetic trees with fossil data. This may seem non-surprising, as in fact the phylogenetic trees on extant species and the fossil data from extinct species are both parts of the same macroevolutionary process, and thus both shape speciation and extinction rates. However, coherent analysis of both data sources was at its infancy when this ERC project started.

In the course of this project, we pushed modelling advances and methodological development leading to tools which can be used by molecular systematists and palaeontologists for joint data analysis. We used our insights in order to characterize speciation modes for a range of different species. We find that e.g. a frequent mode of speciation of whales and bovids seems to be anagenesis, meaning species gradually evolve into new ones.

In the last two decades, it has been recognized that the phylogenetic concept is also crucial for improving our understanding of epidemiological processes. In an epidemiological phylogeny, tips of the tree are corresponding to infected hosts (instead of extant species), and branching events correspond to transmission events (instead of speciation events). In the second part of the ERC project, we developed new tools allowing for a detailed analysis of pathogen genetic sequencing data in a phylogenetic framework. Such analysis allows rapidly quantification of the spread of epidemics. Most recently, we developed new tools to couple the analysis of the sequencing data with classic epidemiological prevalence and incidence data.

We used our methods developed prior and within this ERC to characterize the spread of Ebola spreading in West Africa in 2014. We quantified the same speed of spread as the WHO. Since both analyses were done in parallel on disjoint datasets, we had faith in the estimated number. Further, we investigated potential Diphtheria transmission between refugees coming to Europe in 2015, with the conclusion that all transmission occurred in their home countries and not in Europe, meaning public health interventions for containing transmission should be focussed to their home countries. Finally, we used the very recent methodological advances to provide insight into the epidemiology and evolution of Zika in South America, as well as for quantifying drug resistant HIV transmission and tuberculosis transmission in Switzerland.

Completion of the ERC projects deepened our understanding of macroevolutionary and epidemiological dynamics, as well as led to novel phylogenetic tools allowing us to analyse the growing amount of available data, such as next-generation sequencing data, combined with data from other fields such as paleontology or epidemiology. All tools are available within BEAST v2 and tutorials for learning to use these tools is provided via our webpage