• DocumentCode
    2319747
  • Title

    Evolution in silico of genes with multiple regulatory modules on the example of the Drosophila segmentation gene hunchback

  • Author

    Spirov, Alexander V. ; Holloway, David M.

  • Author_Institution
    Comput. Sci. & CEWIT, SUNY, Stony Brook, NY, USA
  • fYear
    2012
  • fDate
    9-12 May 2012
  • Firstpage
    244
  • Lastpage
    251
  • Abstract
    We use in silico evolution to study the generation of gene regulatory structures. A particular area of interest in evolutionary development (evo-devo) is the correspondence between gene regulatory sequences on the DNA (cis-regulatory modules, CRMs) and the spatial expression of the genes. We use computation to investigate the incorporation of new CRMs into the genome. Simulations allow us to characterize different cases of CRM to spatial pattern correspondence. Many of these cases are seen in biological examples; our simulations indicate relative advantages of the different scenarios. We find that, in the absence of specific constraints on the CRM-pattern correspondence, CRMs controlling multiple spatial domains tend to evolve very quickly. Genes constrained to a one-to-one CRM-pattern domain correspondence evolve more slowly. Of these, systems in which pattern domains appear in a particular order in evolution, as in insect segmentation mechanisms, take the longest time in in silico evolutionary searches. For biological cases of this type, it is likely that other selective advantages outweigh the time costs.
  • Keywords
    DNA; biology computing; evolution (biological); genetics; molecular biophysics; molecular configurations; zoology; CRM-spatial pattern correspondence; DNA; Drosophila segmentation gene hunchback; cis-regulatory modules; evolutionary development; gene regulatory sequences; gene regulatory structure generation; gene spatial expression; in silico gene evolution; insect segmentation mechanisms; multiple regulatory modules; Biological system modeling; Customer relationship management; DNA; Embryo; Evolution (biology); Organizations; co-linearity principle; computational gene design; gene evolution in silico; gene expression domains; genes with multiple regulatory modules; segmentation patterning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2012 IEEE Symposium on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4673-1190-8
  • Type

    conf

  • DOI
    10.1109/CIBCB.2012.6217237
  • Filename
    6217237