PRPTree: Novel bioinformatics software for improved understanding of the temporal context of evolutionary divergence

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In the life sciences, the field of bioinformatics is concerned with compiling large databases of information on organisms - such as DNA or gene sequences - and with developing methods for analysing those databases. Because all living things are connected to each other by their common ancestry, one of the most common bioinformatics tasks is to develop an evolutionary tree or 'phylogeny' of a group of species. A phylogeny is like a family tree but traces the historical lines of descent from older to younger species rather than from parents to their offspring. Scientists reconstruct them by studying the similarities and differences among species in their DNA sequences. They then use the phylogenies to describe the probable course of evolution over millions of years, to see how species evolve and adapt, to study the ways genes and proteins evolve and to reconstruct the timings and pace of change of past events. The Principal Investigator of this project has derived a new statistical method that can potentially greatly improve our ability to estimate the dates and timings of past events of evolution on phylogenetic trees. The proposed research is to i) implement and test this new method, ii) to compile a database of the rates at which species evolve and iii) to make the new method and the database available to others as an easy-to-use bioinformatics tool. Regarding the first goal, the new method we will develop improves our ability to estimate the timings of past events of evolution by allowing investigators to measure more accurately the rate or speed with which DNA sequences acquire differences. This improved dating makes the phylogenies more useful for scientific research. In turn, improved phylogenies will allow scientists to provide better answers to questions like when did the ancestor to humans and chimpanzees live? Or when and where did the Zika or Ebola viruses emerge? The second goal of our work is to compile a database of the rates of evolution observed across a variety of species including plants, animals, bacteria and viruses. Our preliminary work suggests that some extraordinarily highly elevated rates of evolution can occur - 10 or more times the background rate. Knowledge of these rates is important for dating phylogenies, but also for understanding questions like how quickly can bacteria acquire resistance to antibiotics, or viruses outwit our immune systems or whether species can evolve fast enough to respond to climate change.Our third goal is to make our new method freely available to other researchers as a bioinformatics tool known as PRPTree. We produce a software package, as do several other groups, for inferring phylogenetic trees, and we will share our methods with those other developers.