Quantifying connectivity between local Plasmodium falciparum malaria parasite populations using identity by descent

Area of Science:

• Population genetics
• Genomics
• Epidemiology

Background:

• Genomic data is increasingly abundant, driving interest in population genetics for understanding organismal dispersal.
• Assessing fine-scale connectivity in organisms like the malaria parasite Plasmodium falciparum (P. falciparum) using genomic data is challenging.
• Understanding local transmission patterns of P. falciparum is crucial for elimination strategies.

Purpose of the Study:

• To systematically assess the data and methods needed to resolve fine-scale connectivity of P. falciparum.
• To compare the effectiveness of genetic divergence (FST) and identity by descent (IBD) relatedness in measuring spatial connectivity.
• To determine the sample size and data type required for robust spatial trend estimation.

Main Methods:

• Collected genomic data from P. falciparum samples across four clinics spanning ~120 km on the Thai-Myanmar border.
• Compared FST and IBD-based relatedness metrics to assess spatial connectivity between parasite populations.
• Estimated the required sample size (whole genome sequencing or SNP genotyping) for reliable spatial trend detection.

Main Results:

• No significant relationship was found between inter-clinic distance and FST.
• A significant decline in IBD-based relatedness was observed with increasing inter-clinic distance.
• Approximately 147 whole-genome sequenced samples or 222 samples genotyped at 93 SNPs were sufficient to detect spatial trends.

Conclusions:

• Classical genetic divergence measures (FST) are unreliable for assessing local P. falciparum transmission.
• IBD-based relatedness offers a viable alternative for measuring local parasite connectivity, contingent on adequate sampling.
• Robust spatial trends in P. falciparum transmission can be identified using approximately 100 SNPs with sufficient sample sizes.