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Methods to Detect and Associate Divergence in Cis-Regulatory Elements to Phenotypic Divergence

  • Juliana G. Roscito
  • Michael HillerEmail author
Chapter
  • 544 Downloads

Abstract

Understanding which genomic changes are responsible for morphological differences between species is a long-standing question in biology. While evolutionary theory predicts that morphology largely evolves by changing expression of important developmental genes, finding the underlying regulatory mutations is inherently difficult. Here, we discuss how the integration of comparative and functional genomics has provided valuable insights into the regulatory changes involved in morphological changes. By comparing genomes of species exhibiting differences in a morphological trait, comparative genomic methods enable the systematic detection of regulatory elements with divergence in sequence or transcription factor binding sites. To narrow this set of diverged elements down to those that likely contribute to differences in the trait of interest, one can leverage knowledge about gene function to assess which elements are associated with genes known to control the development of this trait. In addition, functional genomics can further prioritize diverged genomic regions based on overlap with experimentally determined regulatory elements that are active in tissues relevant for the trait. Further experiments can then evaluate whether sequence or binding site divergence translates into regulatory differences and affects the development of the trait. Thus, combining comparative and functional genomic approaches provide a widely applicable strategy to reveal regulatory changes contributing to morphological differences, which will enhance our understanding of how nature’s spectacular phenotypic diversity evolved.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Max Planck Institute of Molecular Cell Biology and GeneticsDresdenGermany
  2. 2.Max Planck Institute for the Physics of Complex SystemsDresdenGermany
  3. 3.Center for Systems BiologyDresdenGermany

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