Real-time landscape of Eimeria population structure and genetic diversity for coccidiosis intervention

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Coccidiosis is the most important parasitic disease in chickens, which impacts onproductivity and welfare and costs the global poultry industry over £10 billion everyyear [1]. The disease is caused by protozoan parasites Eimeria, a genus of parasiteswithin the phylum Apicomplexa, a group of obligate intracellular pathogens that cancause serious infectious diseases including Plasmodium, and Toxoplasma. There areseven well recognised chicken infecting Eimeria species. However, driven by genomicplasticity and possible inter-species hybridisations, three new cryptic species that werefirst described in Australia have recently detected across much of the southernhemisphere. These studies have found all three to be capable of escape from immunekilling induced by commercial anticoccidial vaccines [2]. Such unexpected levels ofcomplexity have made the understanding of Eimeria occurrence, abundance andpopulation structure increasingly important. Harnessing the advantages of thirdgeneration long reads and easy to deploy sequencing platforms, particularly fromnanopore technology, we aim to use targeted and genome-wide sequencing to definea real-time landscape of parasite field populations and 'Eimeria-ome' tools forpopulation structure and vaccinology genetic analyses. The project will take amultidisciplinary approach with the following objectives: 1. Establish sampleprocessing and library preparation protocols for nanopore sequencing. Genomic DNAextracted from culture and Eimeria field isolates representing five continents fromProf. Blake's group will be used to test and refine the protocols. 2. Optimisebioinformatic analyse workflows to characterise population genetic and antigenicdiversity in field samples. A streamlined bioinformatics workflow for genome sequencegeneration, assembly and analysis will be established to facilitate real-time analysis ofnanopore sequencing data. 3. Develop an integrative machine learning model onvaccine effectiveness predictions. Features from genotypes, targeted antigen diversitysequencing, subcellular localisations and multi-omics vaccine responses datasets willbe extracted and evaluated to build a predictive model for various Eimeria species.