Dataset Information

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

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.

SUBMITTER: Landry CR

PROVIDER: S-EPMC1805570 | biostudies-literature | 2007 Feb

REPOSITORIES: biostudies-literature

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

Landry Christian R CR Castillo-Davis Cristian I CI Ogura Atsushi A Liu Jun S JS Hartl Daniel L DL

Proceedings of the National Academy of Sciences of the United States of America 20070220 9

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 spec ...[more]

PMID: 17360639

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Project description:Background Simulating DNA evolution has been done through coevolution-agnostic probabilistic frameworks for the past 3 decades. The most common implementation is by using the converse of the probabilistic approach used to infer phylogenies which, in the simplest form, simulates a single sequence at a time. However, biological systems are multi-genic, and gene products can affect each other’s evolutionary paths through coevolution. These crucial evolutionary dynamics still remain to be simulated, and we believe that modelling them can lead to profound insights for comparative genomics. Results Here we present CastNet, a genome evolution simulator that assumes each genome is a collection of genes with constantly evolving regulatory interactions in between them. The regulatory interactions produce a phenotype in the form of gene expression profiles, upon which fitness is calculated. A genetic algorithm is then used to evolve a population of such entities through a user-defined phylogeny. Importantly, the regulatory mutations are a response to sequence mutations, thus making a 1–1 relationship between the rate of evolution of sequences and of regulatory parameters. This is, to our knowledge, the first time the evolution of sequences and regulation have been explicitly linked in a simulation, despite there being a multitude of sequence evolution simulators, and a handful of models to simulate Gene Regulatory Network (GRN) evolution. In our test runs, we see a coevolutionary signal among genes that are active in the GRN, and neutral evolution in genes that are not included in the network, showing that selective pressures imposed on the regulatory output of the genes are reflected in their sequences. Conclusion We believe that CastNet represents a substantial step for developing new tools to study genome evolution, and more broadly, coevolutionary webs and complex evolving systems. This simulator also provides a new framework to study molecular evolution where sequence coevolution has a leading role. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-023-05366-1.

Dataset Information

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

Publications

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

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