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Title: | Dpr-DIP matching expression in Drosophila synaptic pairs |
Author: | Morey i Ramonell, Marta |
Keywords: | Drosòfila Proteïnes Expressió gènica Drosophila Proteins Gene expression |
Issue Date: | 22-Jul-2016 |
Publisher: | Landes Bioscience |
Abstract: | Neurons form precise patterns of connections. The cellular recognition mechanisms regulating the selection of synaptic partners are poorly understood. As final mediators of cell-cell interactions, cell surface and secreted molecules (CSMs) are expected to play important roles in this process. To gain insight into how neurons discriminate synaptic partners, we profiled the transcriptomes of 7 closely related neurons forming distinct synaptic connections in discrete layers in the medulla neuropil of the fly visual system. Our sequencing data revealed that each one of these neurons expresses a unique combination of hundreds of CSMs at the onset of synapse formation. We show that 21 paralogs of the defective proboscis extension response (Dpr) family are expressed in a unique cell-type-specific fashion, consistent with the distinct connectivity pattern of each neuron profiled. Expression analysis of their cognate binding partners, the 9 members of the Dpr interacting protein (DIP) family, revealed complementary layer-specific expression in the medulla, suggestive of interactions between neurons expressing Dpr and those expressing DIP in the same layer. Through coexpression analysis and correlation to connectome data, we identify neurons expressing DIP as a subset of the synaptic partners of the neurons expressing Dpr. We propose that Dpr-DIP interactions regulate patterns of connectivity between the neurons expressing them. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1080/19336934.2016.1214784 |
It is part of: | Fly, 2016, vol. 11, num. 1, p. 19-26 |
URI: | http://hdl.handle.net/2445/112972 |
Related resource: | https://doi.org/10.1080/19336934.2016.1214784 |
ISSN: | 1933-6934 |
Appears in Collections: | Articles publicats en revistes (Genètica, Microbiologia i Estadística) |
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