Back

PvGAP: Development of a globally-applicable, highly-multiplexed microhaplotype amplicon panel for Plasmodium vivax

Hubbard, A.; Solares, E.; Bradley, L.; Jeang, B.; Yewhalaw, D.; Janies, D.; Lo, E.; Yan, G.; Hemming-Schroeder, E.

2025-05-02 infectious diseases
10.1101/2025.04.30.25326751 medRxiv
Show abstract

BackgroundPlasmodium vivax malaria research has yet to fully benefit from the advances in genomic surveillance that have revolutionized P. falciparum epidemiology. Closing this gap is critical because genomic tools are necessary to monitor the spread of drug resistance, classify infections as local or imported, and distinguish reinfection, recrudescence, and relapse. To achieve these objectives, microhaplotype marker panels that allow powerful genotyping of polyclonal infections are needed. MethodsWe designed a Globally-applicable Amplicon Panel for P. vivax (PvGAP), selecting targets based on both genetic diversity and genetic distance from each other to maximize discriminatory capability between geographic regions. We evaluated this panel with field samples from Ethiopia and in silico using whole genomes from the MalariaGEN Pv4 database. ResultsPvGAP has 80 high diversity targets suitable for population genomics and eight targets of specific epidemiological interest, such as putative markers of drug resistance. We demonstrate PvGAP achieves robust amplification with field data and that it provides competitive accuracy for relatedness inference in three disparate geographic regions. ConclusionsPvGAP joins existing P. vivax panels as a cost effective and practical option for genomic epidemiology of this neglected disease. It will support drug resistance surveillance, discrimination of local and imported cases, and it may aid in separating reinfection, recrudescence, and relapse in therapeutic efficacy studies, all critical needs of National Malaria Control Programs.

Published in The Journal of Infectious Diseases (predicted rank #12) · training set

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Malaria Journal
58 papers in training set
Top 0.1%
18.3%
2
eLife
5828 papers in training set
Top 22%
5.4%
3
Scientific Reports
3612 papers in training set
Top 17%
5.4%
4
Open Research Europe
14 papers in training set
Top 0.1%
4.3%
5
BMC Genomics
406 papers in training set
Top 2%
4.3%
6
Frontiers in Cellular and Infection Microbiology
109 papers in training set
Top 0.4%
4.0%
7
Frontiers in Microbiology
427 papers in training set
Top 3%
3.5%
8
Microbial Genomics
225 papers in training set
Top 1.0%
3.2%
9
Infection, Genetics and Evolution
42 papers in training set
Top 0.3%
2.6%
50% of probability mass above
10
Evolutionary Applications
108 papers in training set
Top 0.6%
2.4%
11
Molecular Ecology
336 papers in training set
Top 2%
2.1%
The Journal of Infectious Diseases · published here
202 papers in training set
Top 2%
2.1%
13
PLOS Neglected Tropical Diseases
466 papers in training set
Top 3%
2.1%
14
PLOS ONE
5266 papers in training set
Top 47%
1.9%
15
International Journal for Parasitology
26 papers in training set
Top 0.4%
1.7%
16
mBio
833 papers in training set
Top 8%
1.5%
17
Parasites & Vectors
60 papers in training set
Top 0.9%
1.4%
18
Nature Communications
5641 papers in training set
Top 49%
1.3%
19
Microbiology Spectrum
469 papers in training set
Top 9%
1.1%
20
Frontiers in Genetics
230 papers in training set
Top 4%
1.1%
21
PeerJ
308 papers in training set
Top 9%
1.1%
22
Molecular Biology and Evolution
542 papers in training set
Top 4%
1.1%
23
BMC Infectious Diseases
133 papers in training set
Top 4%
1.0%
24
Peer Community Journal
281 papers in training set
Top 4%
1.0%
25
PLOS Computational Biology
1863 papers in training set
Top 19%
1.0%
26
mSphere
302 papers in training set
Top 6%
1.0%
27
Molecular Ecology Resources
171 papers in training set
Top 2%
0.9%
28
Virus Evolution
155 papers in training set
Top 1%
0.8%
29
Acta Tropica
13 papers in training set
Top 0.5%
0.8%
30
F1000Research
88 papers in training set
Top 4%
0.8%