High resolution species assignment of Anopheles mosquitoes using k-mer distances on targeted sequences

  1. Marilou Boddé  Is a corresponding author
  2. Alex Makunin
  3. Diego Ayala
  4. Lemonde Bouafou
  5. Abdoulaye Diabaté
  6. Uwem Friday Ekpo
  7. Mahamadi Kientega
  8. Gilbert Le Goff
  9. Boris Kevin Makanga
  10. Marc F Ngangue
  11. Olaitan Olamide Omitola
  12. Nil Rahola
  13. Frederic Tripet
  14. Richard Durbin
  15. Mara KN Lawniczak  Is a corresponding author
  1. University of Cambridge, United Kingdom
  2. Wellcome Sanger Institute, United Kingdom
  3. Institut de Recherche pour le Développement, France
  4. Institut de Recherche en Sciences de la Santé, Burkina Faso
  5. Federal University of Agriculture, Nigeria
  6. Institut de Recherche en Ecologie Tropicale, Gabon
  7. Centre International de Recherches Medicales de Franceville, Gabon
  8. Keele University, United Kingdom

Abstract

The ANOSPP amplicon panel is a genus-wide targeted sequencing panel to facilitate large-scale monitoring of Anopheles species diversity. Combining information from the 62 nuclear amplicons present in the ANOSPP panel allows for a more nuanced species assignment than single gene (e.g. COI) barcoding, which is desirable in the light of permeable species boundaries. Here, we present NNoVAE, a method using Nearest Neighbours (NN) and Variational Autoencoders (VAE), which we apply to k-mers resulting from the ANOSPP amplicon sequences in order to hierarchically assign species identity. The NN step assigns a sample to a species-group by comparing the k-mers arising from each haplotype’s amplicon sequence to a reference database. The VAE step is required to distinguish between closely related species, and also has sufficient resolution to reveal population structure within species. In tests on independent samples with over 80% amplicon coverage, NNoVAE correctly classifies to species level 98% of samples within the An. gambiae complex and 89% of samples outside the complex. We apply NNoVAE to over two thousand new samples from Burkina Faso and Gabon, identifying unexpected species in Gabon. NNoVAE presents an approach that may be of value to other targeted sequencing panels, and is a method that will be used to survey Anopheles species diversity and Plasmodium transmission patterns through space and time on a large scale, with plans to analyse half a million mosquitoes in the next five years.

Data availability

Raw sequencing data will be made available on ENA (accession to be confirmed). Pipelines and analysis code, together with processed target haplotypes are available on GitHub: https://github.com/mariloubodde/NNoVAE.

Article and author information

Author details

  1. Marilou Boddé

    Department of Genetics, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    mmb52@cam.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
  2. Alex Makunin

    Wellcome Sanger Institute, Hinxton, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Diego Ayala

    MIVEGEC, IRD, CNRS, Institut de Recherche pour le Développement, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4726-580X
  4. Lemonde Bouafou

    MIVEGEC, IRD, CNRS, Institut de Recherche pour le Développement, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Abdoulaye Diabaté

    Institut de Recherche en Sciences de la Santé, Bobo-Dioulasso, Burkina Faso
    Competing interests
    The authors declare that no competing interests exist.
  6. Uwem Friday Ekpo

    Federal University of Agriculture, Abeokuta, Nigeria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0543-5463
  7. Mahamadi Kientega

    Institut de Recherche en Sciences de la Santé, Bobo-Dioulasso, Burkina Faso
    Competing interests
    The authors declare that no competing interests exist.
  8. Gilbert Le Goff

    MIVEGEC, IRD, CNRS, Institut de Recherche pour le Développement, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  9. Boris Kevin Makanga

    Institut de Recherche en Ecologie Tropicale, Libreville, Gabon
    Competing interests
    The authors declare that no competing interests exist.
  10. Marc F Ngangue

    Centre International de Recherches Medicales de Franceville, Franceville, Gabon
    Competing interests
    The authors declare that no competing interests exist.
  11. Olaitan Olamide Omitola

    Federal University of Agriculture, Abeokuta, Nigeria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3827-6320
  12. Nil Rahola

    MIVEGEC, IRD, CNRS, Institut de Recherche pour le Développement, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4067-6438
  13. Frederic Tripet

    Centre for Applied Entomology and Parasitology, Keele University, Newcastle, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  14. Richard Durbin

    Department of Genetics, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  15. Mara KN Lawniczak

    Wellcome Sanger Institute, Hinxton, United Kingdom
    For correspondence
    mara@sanger.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3006-2080

Funding

Wellcome Trust (206194/Z/17/Z)

  • Mara KN Lawniczak

Wellcome Trust (RG92770)

  • Marilou Boddé

Wellcome Trust (WT207492)

  • Richard Durbin

Agence Nationale de la Recherche (ANR-18-CE35-0002-01 - WILDING).)

  • Diego Ayala

Institut de Recherche pour le Développement (Bourse ARTS/IRD)

  • Lemonde Bouafou

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Daniel R Matute, University of North Carolina, Chapel Hill, United States

Version history

  1. Received: March 18, 2022
  2. Preprint posted: March 20, 2022 (view preprint)
  3. Accepted: October 11, 2022
  4. Accepted Manuscript published: October 12, 2022 (version 1)
  5. Version of Record published: November 10, 2022 (version 2)

Copyright

© 2022, Boddé et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Marilou Boddé
  2. Alex Makunin
  3. Diego Ayala
  4. Lemonde Bouafou
  5. Abdoulaye Diabaté
  6. Uwem Friday Ekpo
  7. Mahamadi Kientega
  8. Gilbert Le Goff
  9. Boris Kevin Makanga
  10. Marc F Ngangue
  11. Olaitan Olamide Omitola
  12. Nil Rahola
  13. Frederic Tripet
  14. Richard Durbin
  15. Mara KN Lawniczak
(2022)
High resolution species assignment of Anopheles mosquitoes using k-mer distances on targeted sequences
eLife 11:e78775.
https://doi.org/10.7554/eLife.78775

Share this article

https://doi.org/10.7554/eLife.78775

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