4.5 Article

Integrating evo-devo with ecology for a better understanding of phenotypic evolution

Journal

BRIEFINGS IN FUNCTIONAL GENOMICS
Volume 14, Issue 6, Pages 384-395

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bfgp/elv003

Keywords

semi-aquatic bugs; evo-devo; evolutionary ecology; multidisciplinarity; functional genomics

Funding

  1. ERC-CoG grant
  2. Swiss National Foundation Early Post-Doc Mobility fellowship
  3. Universite Lyon1

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Evolutionary developmental biology (evo-devo) has provided invaluable contributions to our understanding of the mechanistic relationship between genotypic and phenotypic change. Similarly, evolutionary ecology has greatly advanced our understanding of the relationship between the phenotype and the environment. To fully understand the evolution of organismal diversity, a thorough integration of these two fields is required. This integration remains highly challenging because model systems offering a rich ecological and evolutionary background, together with the availability of developmental genetic tools and genomic resources, are scarce. In this review, we introduce the semi-aquatic bugs (Gerromorpha, Heteroptera) as original models well suited to study why and how organisms diversify. The Gerromorpha invaded water surfaces over 200 mya and diversified into a range of remarkable new forms within this new ecological habitat. We summarize the biology and evolutionary history of this group of insects and highlight a set of characters associated with the habitat change and the diversification that followed. We further discuss the morphological, behavioral, molecular and genomic tools available that together make semi-aquatic bugs a prime model for integration across disciplines. We present case studies showing how the implementation and combination of these approaches can advance our understanding of how the interaction between genotypes, phenotypes and the environment drives the evolution of distinct morphologies. Finally, we explain how the same set of experimental designs can be applied in other systems to address similar biological questions.

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