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Detecting host-parasitoid interactions in an invasive Lepidopteran using nested tagging DNA metabarcoding.

James J N Kitson1,2, Christoph Hahn1,3, Richard J Sands4,5

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Molecular Ecology
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A new DNA sequencing method accurately identifies parasitoids of invasive species. This technique revealed two main parasitoid species, with one infecting 45.7% of oak processionary moth caterpillars.

Keywords:
biocontrolinvasive speciesnested taggingparasitismspecies interactions

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Area of Science:

  • Ecology
  • Entomology
  • Genetics

Background:

  • Understanding host-parasitoid interactions is crucial for managing invasive species and developing biocontrol strategies.
  • Traditional methods for identifying parasitoids, such as insect rearing and taxonomic identification, are time-consuming and can introduce biases.

Purpose of the Study:

  • To present a next-generation sequencing (NGS) approach for tracking invertebrate samples and identifying host-parasitoid interactions.
  • To demonstrate the utility of this NGS method using data from the invasive oak processionary moth (Thaumetopoea processionea) in the UK.

Main Methods:

  • Development and application of a DNA metabarcoding technique using hierarchically organized molecular identification tags.
  • Individual-level metadata tracking of numerous invertebrate samples.
  • Analysis of late larval stages of the oak processionary moth to determine species identity and parasitism rates.

Main Results:

  • Two primary parasitoid species were identified in the late larval stages of the oak processionary moth.
  • The main parasitoid, Carcelia iliaca, infected 45.7% of caterpillars.
  • A secondary parasitoid, Compsilura concinnata, was detected in 0.4% of caterpillars.

Conclusions:

  • The developed NGS approach provides a rapid and unbiased method for assessing host-parasitoid interactions in ecological studies.
  • Further application across all life stages of the oak processionary moth could reveal greater parasitoid diversity.
  • Nested tagging DNA metabarcoding holds significant potential for constructing detailed species interaction networks.