||Kim Lab of Computational Evolutionary Biology|
|Public Private Project1 Project2 Project3 Project4 Archive|
School of Arts and Sciences
University of Pennsylvania
A relatively under explored problem in evolution is the evolution of individual cell function. Mammalian behavior spans a fantastic range of function and ability, from complex linguistic processing, to social and sexual behavior, to simple stimulus-response. Traditional explanations of the mechanisms for this diversity include brain size, neuro-anatomy, and functional neuro-anatomy including connectivity patterns. Establishing these neuro-anatomical differences requires evolutionary differences in the genes guiding developmental processes. However, there has been little comparative studies focused on individual neuronal function in a non-developmental context. Previously, we initiated a project to understand what sequence motifs govern sub-cellular localization of mRNA to dendrites in rat neurons. Surprisingly, we found evidence that an evolutionarily novel element may partly govern dendritic localization. Furthermore, this element is abundant in the rat genome but an order of magnitude less abundant in the mouse genome. A micro-dissection and expression array survey of the mouse neurons seem to suggest that there is only 36% overlap between the homologous mRNA found in the mouse dendrites and the rat dendrites. Thus, we hypothesize that the genome-scale molecular physiology of neurons from different tissues and closely related species have broad differences and functional non-coding RNA derived from evolutionarily novel elements plays a role in establishing these differences. If true, this would have important consequences for translating animal neurobiological studies to humans and also suggest that evolutionarily novel elements such as retroviral-derived elements may be important in brain function and dysfunction. We propose to test our hypothesis using comparative single-cell localization assays, single-cell transcriptome assays, whole-transcriptome sequencing, and functional analysis.
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© 2004, J. Kim
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