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project . 2017 - 2020 . Closed

Rooting the eukaryotic radiation with new models of gene and genome evolution

UK Research and Innovation
Funder: UK Research and InnovationProject code: NE/P00251X/1
Funded under: NERC Funder Contribution: 308,796 GBP
Status: Closed
01 Jan 2017 (Started) 14 Jul 2020 (Ended)

The origin of eukaryotes from their prokaryotic progenitors was one of the most formative transitions in the history of life, catalysing the blossoming of eukaryotic biodiversity into the astonishing range of forms we see today, from the largest organisms on our planet - blue whales, giant sequoias, fungal networks extending for miles underground - to microscopic plankton that jostle with bacteria in the world's oceans. Explaining the leap in cellular complexity during the prokaryote-to-eukaryote transition is one of the outstanding challenges in 21st-century biology. The common structure of all eukaryotic cells testifies to their shared ancestry, but our understanding of the kind of cell that ancestral eukaryote was - where it lived, what it ate, the kinds of biochemical reactions it could perform - is in disarray. Whole-genome data have enabled us to resolve the more recent divergences in eukaryotic evolution, but we still have a very poor understanding of the deeper relationships between the main groups at the base of the evolutionary tree. In particular, the root of the tree - the starting point of the eukaryotic radiation - remains mired in controversy and debate. The problem is that traditional rooting methods rely on the use of an outgroup: to find the root of the tree of mammals, for example, we might include birds in the analysis, and then use our a priori knowledge to place the root on the branch between the two groups. This approach breaks down when applied to the eukaryotic radiation: including our closest prokaryotic relatives greatly reduces the proportion of the eukaryotic genome that can be analysed, and the enormous evolutionary distance to the prokaryotic outgroup obscures the relationships among the different eukaryotic lineages. As a result, recent analyses of the eukaryotic root disagree strongly on its position, despite using similar datasets and analytical approaches. In this project, we will tackle these difficulties head-on to definitively resolve the root of the eukaryotic tree by applying new outgroup-free rooting approaches, including some pioneered by members of the project team, to the most up-to-date, representative sampling of eukaryotic genomic diversity yet assembled. We will use the resulting phylogenomic framework to map the points in evolutionary history at which the unique cellular and genomic traits of modern eukaryotes first evolved, establishing a timescale for the evolution of key eukaryotic innovations. By mapping these traits onto the tree, we will reconstruct a detailed cellular and genomic model of the ancestral eukaryote - an organism which may have lived up to two billion years ago - in order to establish its lifestyle, ecology, and metabolism, and to test hypotheses of how that founding lineage gave rise to the staggering diversity of eukaryotic life we see today. The work we are proposing is fundamental discovery science: the ultimate goal is to understand our own origins, to bring clarity to a poorly-understood period in the history of life vitally important for making sense of the biodiversity we see around us today, and in doing so to establish a new state-of-the-art for phylogenetic rooting with broad applicability to other major evolutionary transitions across the tree of life. But there is also real potential for broader socio-economic impact. Some of the groups that branch near the base of eukaryotic tree are parasitic, and so establishing how these evolved from their free-living ancestors will provide new, much-needed insights into the adaptation of eukaryotic parasites such as Trypanosoma (sleeping sickness) and Giardia to their hosts. As part of the research programme, we will host summer internships for motivated students on biohacking (DIY computational biology), providing a taste of scientific discovery and teaching the crucial computational, statistical and scientific skills needed to identify and nurture the next generation of scientific leaders.

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