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Genome and protein evolution in animals

Team Leader

Richard Copley


Research Activity

    Our group seeks to better understand the evolution of genomes in relation to the evolution of organisms. It develops bioinformatics methods that analyze the co-evolution of the regulatory sequences of the genes and the structure of the proteins that bind to these sequences. These genomic elements play
an essential role in regulation during animal development. Highlights over the course of the last contract include an analysis of the phylogentic relationships of animals (Telford et al., Pro. Biol. Sci./ Royal Society 2014) and of the macromolecular structure/function relationships in early animal evolution (Copley Genome Biol. Evol. 2016).
     The overarching goal of the group is to trace molecular innovation to gain a better understanding of early animal evolution. In the medium term, the particular area of animal evolution we seek to better understand is the nature of the last common ancestor of the cnidarians, with a special focus on the planula larva. Historically, the planula has been regarded as a key common state shared by the cnidarian and bilaterian lineages via the acoelomorph (or xenacoelomorph) flatworms. Recent phylogenetic analyses placing xenacoels as the sister-group to other bilaterian lineages have given credence to this view. With the group’s interest in cnidarians and xenacoels it represents a natural area to focus on, and presents opportunities to pursue a number of other areas of biological interest, such as the biphasic life cycles of other marine taxa.

     The group’s core expertize of genomic and proteomic analysis naturally converge at the single cell level, with the transcriptional control of components required to produce cell-type specific protein complexes. We will develop in parallel the twin approaches of cell-level transcriptional analysis and cell-type specific protein-protein and protein-DNA complexes in a structural and phylogenetic context. We will make use of strategic collaborations within the unit and elsewhere, as well as leveraging rapidly increasing publicly available datasets.

Richard Copley - 06/11/17

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