Details

Autor(en) / Beteiligte

• Siegel, Sasha V.
• Trimarsanto, Hidayat
• Amato, Roberto
• Murie, Kathryn
• Taylor, Aimee R.
• Sutanto, Edwin
• Kleinecke, Mariana
• Whitton, Georgia
• Watson, James A.
• Imwong, Mallika
• Assefa, Ashenafi
• Rahim, Awab Ghulam
• Nguyen, Hoang Chau
• Tran, Tinh Hien
• Green, Justin A.
• Koh, Gavin C. K. W.
• White, Nicholas J.
• Day, Nicholas
• Kwiatkowski, Dominic P.
• Rayner, Julian C.
• Price, Ric N.
• Auburn, Sarah

Titel

Lineage-informative microhaplotypes for recurrence classification and spatio-temporal surveillance of Plasmodium vivax malaria parasites

Ist Teil von

• Nature communications, 2024-08, Vol.15 (1), p.6757-16, Article 6757

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2024

Quelle

MEDLINE

Beschreibungen/Notizen

• Challenges in classifying recurrent Plasmodium vivax infections constrain surveillance of antimalarial efficacy and transmission. Recurrent infections may arise from activation of dormant liver stages (relapse), blood-stage treatment failure (recrudescence) or reinfection. Molecular inference of familial relatedness (identity-by-descent or IBD) can help resolve the probable origin of recurrences. As whole genome sequencing of P. vivax remains challenging, targeted genotyping methods are needed for scalability. We describe a P. vivax marker discovery framework to identify and select panels of microhaplotypes (multi-allelic markers within small, amplifiable segments of the genome) that can accurately capture IBD. We evaluate panels of 50–250 microhaplotypes discovered in a global set of 615  P. vivax genomes. A candidate global 100-microhaplotype panel exhibits high marker diversity in the Asia-Pacific, Latin America and horn of Africa (median H E  = 0.70–0.81) and identifies 89% of the polyclonal infections detected with genome-wide datasets. Data simulations reveal lower error in estimating pairwise IBD using microhaplotypes relative to traditional biallelic SNP barcodes. The candidate global panel also exhibits high accuracy in predicting geographic origin and captures local infection outbreak and bottlenecking events. Our framework is open-source enabling customised microhaplotype discovery and selection, with potential for porting to other species or data resources. This work describes an informatic framework to identify multi-allelic markers in the genome of the malaria-causing Plasmodium vivax parasite that can inform on familial relatedness between infections. Spatial and temporal transmission patterns are demonstrated with an example marker set.