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Many genes have been implicated in mechanisms of long-term memory formation, but there is still much to be learnt about how the genome dynamically responds, transcriptionally, during memory formation. In this study, we used high-throughput sequencing to examine how transcriptome profiles change during visual memory formation in the bumblebee (Bombus terrestris). Expression of fifty-five genes changed immediately after bees were trained to associate reward with a single coloured chip, and the upregulated genes were predominantly genes known to be involved in signal transduction. Changes in the expression of eighty-one genes were observed four hours after learning a new colour, and the majority of these were upregulated and related to transcription and translation, which suggests that the building of new proteins may be the predominant activity four hours after training. Several of the genes identified in this study (e.g. Rab10, Shank1 and Arhgap44) are interesting candidates for further investigation of the molecular mechanisms of long-term memory formation. Our data demonstrate the dynamic gene expression changes after associative colour learning and identify genes involved in each transcriptional wave, which will be useful for future studies of gene regulation in learning and long-term memory formation.
Pubmed ID: 29323174
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Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsMulti paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
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