Abstract

Plasmodium vivax is a major public health burden, responsible for the majority of malaria infections outside Africa. We explored the impact of demographic history and selective pressures on the P. vivax genome by sequencing 182 clinical isolates sampled from 11 countries across the globe, using hybrid selection to overcome human DNA contamination. We confirmed previous reports of high genomic diversity in P. vivax relative to the more virulent Plasmodium falciparum species; regional populations of P. vivax exhibited greater diversity than the global P. falciparum population, indicating a large and/or stable population. Signals of natural selection suggest that P. vivax is evolving in response to antimalarial drugs and is adapting to regional differences in the human host and the mosquito vector. These findings underline the variable epidemiology of this parasite species and highlight the breadth of approaches that may be required to eliminate P. vivax globally.

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Acknowledgements

We acknowledge J. Bochicchio and S. Chapman for project management, A. Gnirke for technical support, and members of the Broad Institute Genomics Platform and NYU's Genomics Core for data generation. We thank F. Santillan and P. Michon for technical assistance and MR4 for providing us with malaria parasites deposited by W.E. Collins. The following grants supported this work: National Institute of Allergy and Infectious Diseases (NIAID)/National Institutes of Health (NIH) International Centers of Excellence for Malaria Research U19AI089676 to J.M.C.; U19AI089681, K24AI068903 and D43TW007120 to J.M.V.; U19AI089672 to L.C.; São Paulo Research Foundation 2009/52729-9 to M.U.F.; National Council for Science and Technology Mexico 29005-M SALUD-2004-119 and National Institute of Public Health Mexico project 476191 to L.G.-C.; Victorian State Government Operational Infrastructure Support and Australian Government National Health and Medical Research Council Independent Medical Research Institutes Infrastructure Support Scheme (NHMRC IRIISS) to A.B. and I.M.; 5U19AI089702 to S.H. and M.A.-H.; Armed Forces Health Surveillance Center, Global Emerging Infections Surveillance and Response System and US NIH grant D43TW007393 to A.G.L.; NIH U19AI089686 to J.W.K.; and Bill and Melinda Gates Foundation grant to J.S. Sequencing and analysis work at the Broad Institute was supported by federal funds from the NIAID, NIH, US Department of Health and Human Services, under contract HHSN272200900018C. M.U.F. is supported by a senior research scholarship from the Conselho Nacional de Desenvolvimento Científico e Tecnológico of Brazil, I.M. is supported by NHMRC senior research fellowship 1043345 and D.N.H. is supported by NIH training grant T32AI007180. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official policy or position of the US Department of the Navy, the US Department of Defense, the US government or the National Institutes of Health.

Author information

Affiliations

  1. Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, USA.

    • Daniel N Hupalo
    • , Zunping Luo
    • , Patrick L Sutton
    •  & Jane M Carlton
  2. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Alexandre Melnikov
    • , Peter Rogov
    • , Bruce W Birren
    •  & Daniel E Neafsey
  3. Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Philadelphia, Pennsylvania, USA.

    • Ananias Escalante
  4. Caucaseco Scientific Research Center, Cali, Colombia.

    • Andrés F Vallejo
    • , Sócrates Herrera
    •  & Myriam Arévalo-Herrera
  5. Faculty of Health, Universidad del Valle, Cali, Colombia.

    • Myriam Arévalo-Herrera
  6. Dalian Institute of Biotechnology, Dalian, Liaoning, China.

    • Qi Fan
  7. Third Military Medical University, Shapingba, Chongqing, China.

    • Ying Wang
  8. Department of Entomology, Pennsylvania State University, University Park, Pennsylvania, USA.

    • Liwang Cui
  9. US Naval Medical Research Unit No. 6, Callao, Peru.

    • Carmen M Lucas
    • , Salomon Durand
    • , Juan F Sanchez
    • , G Christian Baldeviano
    •  & Andres G Lescano
  10. Papua New Guinea Institute of Medical Research, Madang, Papua, New Guinea.

    • Moses Laman
  11. Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Goroka, Papua New Guinea.

    • Celine Barnadas
  12. Division of Infection and Immunity, Walter & Eliza Hall Institute of Medical Research, Parkville, Australia.

    • Celine Barnadas
  13. Division of Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.

    • Alyssa Barry
    •  & Ivo Mueller
  14. Department of Medical Biology, University of Melbourne, Carlton, Victoria, Australia.

    • Alyssa Barry
    •  & Ivo Mueller
  15. Institute of Global Health (ISGLOBAL), Barcelona, Spain.

    • Ivo Mueller
  16. Center for Global Health and Diseases, Case Western Reserve University, Cleveland, Ohio, USA.

    • James W Kazura
  17. National Institute of Malaria Research Field Unit, Indian Council of Medical Research, National Institute of Epidemiology Campus, Chennai, Tamil Nadu, India.

    • Alex Eapen
    •  & Deena Kanagaraj
  18. National Institute of Malaria Research, Indian Council of Medical Research, New Delhi, India.

    • Neena Valecha
  19. Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil.

    • Marcelo U Ferreira
  20. Mahidol Vivax Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.

    • Wanlapa Roobsoong
    •  & Jetsumon Sattabonkot
  21. Department of Molecular Tropical Medicine and Genetics, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.

    • Wang Nguitragool
  22. Instituto de Medicine Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.

    • Dionicia Gamboa
    •  & Joseph M Vinetz
  23. Departamento de Ciencias Celulares y Moleculares, Universidad Peruana Cayetano Heredia, Lima, Peru.

    • Dionicia Gamboa
    •  & Joseph M Vinetz
  24. Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

    • Margaret Kosek
  25. Division of Infectious Diseases, Department of Medicine, University of California San Diego, La Jolla, California, USA.

    • Joseph M Vinetz
  26. Regional Centre for Research in Public Health, National Institute for Public Health, Tapachula, Chiapas, México.

    • Lilia González-Cerón

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Contributions

J.M.C., I.M. and D.E.N. conceived and conducted the study. A.M., P.L.S., P.R., A.F.V., Q.F., Y.W., C.M.L., S.D., J.F.S., M.L., C.B., D.K., W.R., W.N. and M.K. undertook field and/or wet-lab work and sequencing of the samples. D.N.H., Z.L., J.M.C. and D.E.N. analyzed data. D.N.H., J.M.C., Z.L. and D.E.N. wrote the manuscript, and A.E., S.H., M.A.-H., L.C., G.C.B., A.G.L., A.B., I.M., J.W.K., A.E., N.V., M.U.F., J.S., D.G., J.M.V., L.G.-C. and B.W.B. revised the manuscript and made comments.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Daniel E Neafsey or Jane M Carlton.

Integrated supplementary information

Supplementary figures

  1. 1.

    Evaluation of the performance of different hybrid selection baits on a sample with 0.27% initial P. vivax mappable reads.

  2. 2.

    Project workflow used in this study, including sample collection, wet-lab processing and subsequent in silico analyses.

  3. 3.

    Determination of complexity of infection using variant calls from 195 P. vivax isolates.

  4. 4.

    Region-specific projections of the variation data that use two principal components and are limited to Old World and New World populations.

  5. 5.

    Analysis of the incidence and extent of genomic regions exhibiting identity by descent (IBD) within subpopulations.

  6. 6.

    Three maximum-likelihood trees computed by RAxML and REALPHY software that use three different reference genomes (Salvador I, Mauritania I and North Korean) and a subset of high-quality sequenced P. vivax isolates.

  7. 7.

    Admixture analysis of 195 isolates.

  8. 8.

    A comparison of the per-gene fixation index (FST) between New World and Old World isolates and per-gene nucleotide diversity calculated in each case from 73 single-infection, high-quality samples.

  9. 9.

    Results from the McDonald–Kreitman (MK) test using a subset of single-infection and high-quality isolates from Colombia, Peru, Mexico, Thailand, Myanmar and Papua New Guinea.

  10. 10.

    Plots of five different population genetic values across chromosome 5 of P. vivax.

  11. 11.

    Plots of five different population genetic values across chromosome 7 of P. vivax.

  12. 12.

    Plots of six different population genetic values across chromosome 9 of P. vivax.

  13. 13.

    Plots of six different population genetic values across chromosome 11 of P. vivax.

  14. 14.

    Plots of six different population genetic values across chromosome 12 of P. vivax.

  15. 15.

    Plots of six different population genetic values across chromosome 14 of P. vivax.

  16. 16.

    Haplotype map of three genes found to exhibit signals of positive selection within P. vivax.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–16, Supplementary Table 4 and Supplementary Note.

Excel files

  1. 1.

    Supplementary Table 1

    Genome statistics and metadata. Country of origin, GenBank accession number, and various in silico and molecular biology assay results for the 195 P. vivax isolates analyzed in this study.

  2. 2.

    Supplementary Table 2

    Genes of interest. List of nonsynonymous SNPs, insertions, and deletions in 22 genes identified as, or being associated with, genes having high FST.

  3. 3.

    Supplementary Table 3

    Summary of results from the McDonald–Kreitman test.

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DOI

https://doi.org/10.1038/ng.3588

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