Efficient computational technologies to resolve the Timetree of Life: from ancient DNA to species-rich phylogenies

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The genomes of organisms accumulate changes with the passage of time, recording the evolutionary history of species divergences and extinctions as a timepiece does. By sequencing genomes and integrating information from fossil records, scientists can reconstruct evolutionary trees and calibrate them to geological time. This molecular-clock dating approach has led to spectacular results by leveraging information from sequenced genomes, greatly enriching our understanding of the macroevolutionary process of species diversifications through time, and the possible driving factors such as major geological events and paleoclimate changes.Bayesian inference provides a flexible framework for integrating various sources of uncertainty in molecular clock dating analyses, such as uncertainties in the rate of molecular evolution over time, in the age and placement of fossils on species phylogenies, and in estimated molecular branch lengths from genomic data. However, Bayesian methods are computationally expensive as they require stochastic MCMC sampling to integrate over the uncertainties, and thus they are unable to handle the deluge of genomic data. This computational limitation is a major problem because genome-scale datasets are needed to achieve high precision in estimated evolutionary timescales, which allows the testing of precise evolutionary hypotheses that could never be addressed with the crude time estimates obtained with small molecular datasets.Our team has a track record of successfully developing Bayesian methods to infer evolutionary timescales, with our software packages, BPP and MCMCtree, being widely used by academic beneficiaries to reconstruct such timescales. The overarching aim of this proposal is to develop new models and algorithms for efficient inference of evolutionary timescales using large genome-scale datasets, and integrate these new methods into our existing software. We will develop (1) models that account for sequence errors (to accommodate DNA degradation) and integrate dated samples for analysis of ancient genomes, (2) cross-bracing calibrations to leverage information in gene duplications and horizontal gene transfer events for inferring ancient timescales, and (3) efficient MCMC sampling algorithms for analysis of species-rich phylogenomic datasets. The improved algorithms will make it possible to analyse large datasets with thousands of genomes, from the Darwin Tree of Life and Earth BioGenome projects, as well as helping reduce the carbon footprint of computational analyses.Finally, we will use our newly developed technologies to tackle three important case studies: (1) The evolution of human populations and other hominids, by integrating analysis of ancient and modern genomes within the multi-species coalescent model with introgression, (2) inferring the species-rich Tree of Life of Tetrapods (mammals, birds, crocodiles, turtles, lepidosaurs, and amphibians) in the context of three major past extinction events (end-Permian, Triassic-Jurassic, and end-Cretaceous), and the rapid global warming event during the Eocene-Palaeocene Thermal Maximum, and (3) inferring the Tree of Life of Eukaryotes, by integrating information from ancient gene duplication and horizontal gene transfer events, which will help reduce uncertainty in the timing some of the deepest speciation events in the history of Life on Earth.