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Nat Commun. 2017 Mar 2;8:14613. doi: 10.1038/ncomms14613.

Evolution of complexity in the zebrafish synapse proteome.

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Molecular Physiology of the Synapse Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Sant Antoni Maria Claret 167, 08025 Barcelona, Spain.
Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Bellaterra, Spain.
Department of Biomedical Science, The Centre for Membrane Interactions and Dynamics, University of Sheffield, Western Bank, Sheffield S10 2TN, UK.
Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK.
School of Veterinary Medicine and Science, University of Nottingham. Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Proteomic Mass Spectrometry, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK.
Advanced Data Analysis Centre, University of Nottingham, Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Genes to Cognition Programme, Centre for Clinical Brain Science, University of Edinburgh, Edinburgh EH16 4SB, UK.


The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases.

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