Tracking malaria parasite lineages through de novo mutations in highly related Plasmodium falciparum genomes
4 affiliations
- 1LPHI, MIVEGEC, University of Montpellier, CNRS, INSERM , Montpellier 34090 ,
- 2Host-Pathogen Interaction Program, Texas Biomedical Research Institute , San Antonio, 78227 TX ,
- 3Department of Infection Biology, London School of Hygiene and Tropical Medicine , WC1E 7HT, London ,
- 4Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine , Banjul ,
Abstract
Where malaria transmission declines, the remaining infections are increasingly low-density and asymptomatic, forming a persistent reservoir that is difficult to track using conventional epidemiological approaches. However, genomic data from such community-level infections remain scarce, limiting the ability to track parasite lineages, detect clonal expansions, and identify persistent chronic infections in pre-elimination settings. Here, 78 single-genotype Plasmodium falciparum genome sequences are analysed from community infections within a small area of The Gambia, where malaria transmission has substantially declined over recent decades. Pairwise identity-by-descent (IBD) analysis revealed generally low genetic relatedness among parasites, consistent with ongoing recombination and genetic mixing at the community scale. Nevertheless, eight clusters of near-identical genomes (IBD > 0.9) were identified, enabling the inference of recent de novo mutations that differentiate these genomes. Across these clusters, 43 de novo single-nucleotide polymorphisms and 19 short indels were identified using long-read-derived reference genomes. The observed pattern of mutation in natural infections broadly resembled that previously reported from laboratory mutation-accumulation experiments, including a strong transition bias and enrichment of G:C→A:T substitutions. These results demonstrate that combining IBD analysis with de novo mutation detection enables fine-scale resolution of parasite relatedness and recent transmission history. As malaria transmission continues to decline, such approaches may become increasingly valuable for tracking local transmission, identifying parasite lineages, and potentially distinguish persistent infections from reintroduction events.
Related
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- A Plasmodium falciparum Pangenome Resource to Drive Structural Variant Discovery and to assist Malaria Control
BibTeX
@article{fogang2026tracking,
title = {{Tracking malaria parasite lineages through de novo mutations in highly related Plasmodium falciparum genomes}},
author = {Balotin Fogang and Marc-Antoine Guery and Ian Cheeseman and David J Conway and Antoine Claessens},
journal = {G3: Genes, Genomes, Genetics},
year = {2026},
month = nov,
doi = {10.1093/g3journal/jkag313},
url = {https://academic.oup.com/g3journal/advance-article/doi/10.1093/g3journal/jkag313/9022231},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Tracking malaria parasite lineages through de novo mutations in highly related Plasmodium falciparum genomes
AU - Balotin Fogang
AU - Marc-Antoine Guery
AU - Ian Cheeseman
AU - David J Conway
AU - Antoine Claessens
PY - 2026
DA - 2026/11/09
JO - G3: Genes, Genomes, Genetics
DO - 10.1093/g3journal/jkag313
UR - https://academic.oup.com/g3journal/advance-article/doi/10.1093/g3journal/jkag313/9022231
AB - Where malaria transmission declines, the remaining infections are increasingly low-density and asymptomatic, forming a persistent reservoir that is difficult to track using conventional epidemiological approaches. However, genomic data from such community-level infections remain scarce, limiting the ability to track parasite lineages, detect clonal expansions, and identify persistent chronic infections in pre-elimination settings. Here, 78 single-genotype Plasmodium falciparum genome sequences are analysed from community infections within a small area of The Gambia, where malaria transmission has substantially declined over recent decades. Pairwise identity-by-descent (IBD) analysis revealed generally low genetic relatedness among parasites, consistent with ongoing recombination and genetic mixing at the community scale. Nevertheless, eight clusters of near-identical genomes (IBD > 0.9) were identified, enabling the inference of recent de novo mutations that differentiate these genomes. Across these clusters, 43 de novo single-nucleotide polymorphisms and 19 short indels were identified using long-read-derived reference genomes. The observed pattern of mutation in natural infections broadly resembled that previously reported from laboratory mutation-accumulation experiments, including a strong transition bias and enrichment of G:C→A:T substitutions. These results demonstrate that combining IBD analysis with de novo mutation detection enables fine-scale resolution of parasite relatedness and recent transmission history. As malaria transmission continues to decline, such approaches may become increasingly valuable for tracking local transmission, identifying parasite lineages, and potentially distinguish persistent infections from reintroduction events.
SN - 2160-1836
ER -