Lacewing venom: Linking the molecular and phenotypic evolution of adaptive traits

Introduction

Understanding the ability of species to adapt to their environment, or their evolvability, is central to evolutionary biology. Most traits are complex in that their phenotype results from the contributions of many genes with small, sometimes non-additive effects.

Quantitative Genetics

While quantitative genetics has been instrumental in showing that short-term evolvability depends on additive genetic variation, it ignores details of the molecular underpinnings of phenotypic characters that are crucial for the production and maintenance of additive genetic variation. This, in turn, affects our understanding of evolvability and calls for model traits that enable the integration of quantitative and molecular genetics.

Venoms as Model Systems

Venoms are great model systems for this purpose. They are convergent sets of traits well-suited for comparative studies. Their phenotypes result from the combined actions of a relatively small number of secreted, functionally repurposed proteins, or toxins, that can be identified, characterized, and quantified.

Focus on Neuroptera

This project focuses on the venoms of Neuroptera, which remain unstudied despite providing a unique opportunity among venomous animals to combine omics techniques, and comparative molecular and morphological evolution with evolutionary quantitative genetics.

Multidisciplinary Approach

This multidisciplinary approach will:

1. Elucidate the genetic and evolutionary mechanisms that underlie the emergence of venoms as complex evolutionary novelties.
2. Identify the molecular properties that facilitate or constrain their evolution across micro- and macroevolutionary timescales.

Hypotheses and Outcomes

Thus, the project will test central hypotheses about venom evolvability. It is also likely to yield novel bioactive molecules with potential use as molecular tools and agrochemical leads.

Conclusion

Finally, it will establish venom as model systems that enable integration of quantitative and molecular genetics, thereby addressing a major methodological challenge in evolutionary biology.