Combining developmental, population, and comparative genomics analyses to study long term evolution of cell types


Meeting Abstract

76.3  Monday, Jan. 6 08:30  Combining developmental, population, and comparative genomics analyses to study long term evolution of cell types SIMAKOV, O.*; ROKHSAR, D.S.; ARENDT, D.; EMBL Heidelberg, Germany; UC Berkeley; EMBL Heidelberg, Germany simakov@embl.de

While most of the inferences about the ancestral metazoan or bilaterian cell type complements are based primarily on gene expression and morphological comparisons, they usually lack information about their dynamics, i.e.: micro- (intra-species environmental and population) and macro-evolutionary (e.g, inter-species genomic) variation. Here I discuss a new integrative ‘eco-evo-devo’ approach that combines comparative genomics studies of bilaterian genomes (including the first broad sampling of the lophotrochozoans), eco-transcriptomics of the natural populations and a molecular study of cell-type development of a cosmopolitan polychaete Platynereis dumerilii. In particular, using genomic and population data and taking advantage of a detailed cellular-level characterization of the foregut development in Platynereis and few other phylogenetically important species, we are in the process of mapping micro- and macro-evolutionary variation onto cell types or tissues. This allows us to identify correlates of ‘evolutionary stable’ (slow-evolving) and ‘unstable’ (fast-evolving) cell types or tissues and provides us with the first glimpse into how micro- and micro-evolutionary processes might have interacted and shaped animal evolution over the past 600 million years at the cell type level. In my presentation, I will summarize the data from the different time scales including the genomic (gene family, repeat, and linkage evolution), population (transcriptomics and metabolomics), and development (expression profiling) and describe an integrative framework for cell type evolution in a context of a comparative study of the foregut development. Such framework can be readily extended to other model systems.

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