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Modelling transmission dynamics and genomic diversity in a recombining parasite population
1St. John's College, University of Oxford, Oxford, UK.
Wellcome Open Research
|November 18, 2024
Summary
This study introduces a genomic transmission graph to simplify parasite diversity analysis. The model helps understand malaria parasite genomic diversity and transmission dynamics using deep sequencing data.
Area of Science:
- Parasitology
- Population Genetics
- Computational Biology
Background:
- Parasite genomic diversity is complex due to superinfection, cotransmission, and recombination.
- Analyzing the relationship between transmission dynamics and genomic diversity is challenging.
Purpose of the Study:
- To simplify the analysis of parasite genomic diversity by introducing a genomic transmission graph.
- To provide a mathematical framework for analyzing within-host variation and simulating coalescence times.
Main Methods:
- Developed a genomic transmission graph model with three key parameters: effective number of hosts, quantum of transmission, and crossing rate.
- Simulated coalescence times in recombining parasite populations with superinfection and cotransmission.
- Applied the model to malaria (Plasmodium falciparum) to study transmission dynamics and migration effects on genomic diversity.
Main Results:
- The model enables rapid simulation of coalescence times and analysis of within-host variation.
- Examined how transmission dynamics and migration influence parasite genomic diversity, effective recombination rate, and recent common ancestry metrics.
- Demonstrated inference of key transmission parameters from deep sequencing data, including estimating the Plasmodium falciparum transmission bottleneck.
Conclusions:
- The genomic transmission graph offers a novel inferential framework for understanding parasite genomic diversity.
- The framework has potential applications in genomic surveillance for malaria control and elimination.
- Online tools are available for exploring the genomic transmission graph.
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