Discovery, species diversity, and utilisation of parasitoids using AI in a genomic framework

Project Background 

Parasitoid wasps, a megadiverse group within the insect order Hymenoptera, are essential for maintaining ecological balance and pest control. Parasitoids attack and kill an astonishing range of arthropod hosts of all life stages, using a variety of strategies, often in complex combinations. These strategies include endo- and ectoparasitoidism, gregarious or solitary development, koiniobiontism and idiobiontism, ooparasitoidism, hyperparasitoidism, kleptoparasitism and more (Polaszek & Vilhelmsen, 2023).

Because of this suite of unique life traits, they also display great potential for being studied as new model organisms. But the extent of their biodiversity remains largely unknown, hampering our ability to leverage their potential fully.

This proposal outlines an ambitious project that harnesses cutting-edge artificial intelligence (AI) and genomic techniques to expedite the discovery of parasitoid species and uncover the evolutionary trends driving their diversification. Through interdisciplinary collaboration and innovative methodologies, we aim to revolutionize our comprehension of parasitoid wasps, and harness and improve their potential as biocontrol agents. 

Project Aims and Methods 

1. Species Discovery 

Deploy cutting-edge AI algorithms, including machine learning and deep learning models, for precise species identification through image recognition (see MacLeod et al., 2022).  

2. Phylogenetic Analysis 

Employ high-throughput genomic sequencing to gather extensive genetic data from diverse parasitoid wasp species, with a particular focus on key genetic markers. Given the taxonomic uncertainty surrounding this important group of insects we will send all reference specimens to the sequencing pipeline at the Sanger institute under their Darwin Tree of Life. They maintain an interactive database that will allow us to see which species have been collected (and or sequenced) and which have not.

Given the collective expertise of the team we expect to vastly increase the number of parasitoids entering the pipeline and thus contribute new species to the DToL project’s production of chromosomal assemblies. As the Sanger releases genome data openly, this will allow us to refine parasitoid taxonomy based on phylogenies derived from whole genomes. It will also facilitate future studies to look at their population genetics using low coverage re-sequencing. DNA barcoding will be performed prior to whole genome sequencing- to confirm that the animal corresponds to a new taxonomic group without a whole genome. 

Leverage of advanced computational tools for phylogenetic reconstruction, allowing us to elucidate the evolutionary history of “dark taxa” with unparalleled accuracy (see Hartop et al., 2022). 

3. Data Accessibility 

Establish a cutting-edge, centralized database, adhering to the highest data security standards, to house and disseminate genomic, taxonomic, and ecological data pertaining to parasitoid wasps. 

Develop robust data-sharing protocols to guarantee the widespread availability of research outputs. 

Candidate requirements 

Knowledge and experience of parasitoid species-level taxonomic techniques essential. Demonstrated ability to handle microscopic specimens (usually <0.5 mm) for non-destructive DNA extraction and slide-mounting of extracted specimens. Training will be available. 

Project partners  

University of Exeter, Biosciences; Natural History Museum; UK Centre for Ecology & Hydrology; Biobest BV; Taylor & Francis, Darwin Tree of Life-Sanger partnership. 

Training 

Training will be available in all required lab techniques and protocols, including non-destructive DNA extraction, dissection and slide mounting of extracted specimens, specialised specimen imaging techniques (whole specimens and dissected slide mounts). Fieldwork will be an essential component of the project. Biobest BV will provide training in principles of biocontrol using parasitoids in either their UK or continental facilities.   

How to apply

Apply for this project here.

The application deadline is Tuesday 9 January 2024 at 23.59 GMT.

Interviews will take place from 26 February to 8 March 2024. For more information about the NERC GW4+ Doctoral Training Partnership please visit https://www.nercgw4plus.ac.uk.

If you are interested in applying, you must complete the Personal Statement form.

Please also complete the applicant's questionnaire GW4+ DTP PhD applicants questionnaire - 2023-24.

For more information on who can apply please visit the GW4+ page: Apply - NERC GW4+.

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