Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity
Alon Kaufman,
Gideon Dror,
Isaac Meilijson and
Eytan Ruppin
PLOS Computational Biology, 2006, vol. 2, issue 12, 1-7
Abstract:
The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations.Synopsis: The study of the genetic basis of the formation of neural connections in the nervous system (synaptogenesis) has been at the forefront of recent investigations in neuroscience. With the advancement of molecular biology research, many small-scale studies have identified specific genes and mechanisms involved in axon guidance and synaptogenesis. The nematode C. elegans provides an exciting opportunity to approach these issues in a computational large-scale manner. Its synaptic connectivity network has been identified, and, combined with information from gene expression studies, we now have neuronal connectivity and gene expression signatures for most of its neurons. Analyzing this data, Kaufman and colleagues show that the expression signature of a neuron carries significant information about its synaptic connectivity and can predict its neural targets in a statistically significant manner. The current study is the first, to our knowledge, to rigorously quantify and measure this relation. It identifies a putative list of genes that specify the neurons' connections which nicely conforms with the existing literature and leads to interesting new predictions.
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:0020167
DOI: 10.1371/journal.pcbi.0020167
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