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Bioinformatic Sequence Analysis Reveals Evolutionary History of Synaptic Genes

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2025-01-09

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Xu, Mengjun. 2025. Bioinformatic Sequence Analysis Reveals Evolutionary History of Synaptic Genes. Master's thesis, Harvard University Division of Continuing Education.

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Abstract

Synapse is an innovation that occurred early in animal evolution, possibly during the very emergence of animals hundreds if not thousands of millions years ago (Südhof, 2023). Synapses were likely stitched together from pre-existing components, possibly by altering some of these components sequence features. This mini-PhD research paper (1) determined the evolutionary history of key components of synapses using sequence analyses as an approach and analyzed existing literature on the ultrastructural of synapses in evolutionarily old animals, and (2) leveraged the resulting information into a hypothesis on how synapses possibly evolved. Exploring the evolutionary roots of behavior is a key objective in the field of biology and has the potential to offer valuable insights into human disorders. Similarly for neuroscience, as my thesis director Dr. Südhof presented (2013), studying synapses (the basic computational units of the brain) was fundamentally important to understand our brain. 1970 Nobel Laureate Bernard Katz (1966) proposed that all synapses operated by the same principle, although they differed in properties. So, the key question was how the assembly of a presynaptic secretory machinery, incorporating evolutionarily older components, contribute to the evolution of synapses as a rapid mechanism for initiating the first muscle contraction? In this project, I researched on early synapse evolution, not the differences between various branches of Bilateria (which include all insects, mammals etc.) but the evolution of synapses before the Bilateria body plan emerged from Cnidaria, Placozoa, Porifera, Ctenophora and Choanoflagellata, when the nervous system was organized in nerve nets.

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Bioinformatics, Biology, Evolution, GPCR, Intelligence, Synapses, Neurosciences, Artificial intelligence, Evolution & development

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