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Systems-level analysis and evolution of the phototransduction network in Drosophila

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2007

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Proceedings of the National Academy of Sciences
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Landry, C. R., C. I. Castillo-Davis, A. Ogura, J. S. Liu, and D. L. Hartl. 2007. “Systems-Level Analysis and Evolution of the Phototransduction Network in Drosophila.” Proceedings of the National Academy of Sciences 104 (9) (February 20): 3283–3288. doi:10.1073/pnas.0611402104.

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Abstract

Networks of interacting genes are responsible for generating life's complexity and for mediating how organisms respond to their environment. Thus, a basic understanding of genetic variation in gene networks in natural populations is important for elucidating how changes at the genetic level map to higher levels of biological organization. Here, using the well-characterized phototransduction network in Drosophila, we analyze variation in gene expression within and between two closely related species, Drosophila melanogaster and Drosophila simulans, under different environmental conditions. Gene expression levels in the pathway are largely conserved between these two sibling species. For most genes in the network, differences in level of gene expression between species are correlated with degree of polymorphism within species. However, one gene encoding the light-induced ion channel TRPL (transient receptor potential-like) shows an excess of expression divergence relative to polymorphism, suggesting a possible role for natural selection in shaping this expression difference between species. Finally, this difference in TRPL expression likely has significant functional consequences, because it is known that a high level of rhabdomeral TRPL leads to increased sensitivity to dim background light and an increased response to a wider range of light intensities. These results provide a preliminary quantification of variation and divergence of gene expression between species in a known gene network and provide a foundation for a system-level understanding of functional and evolutionary change.

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natural selection, gene expression, network

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