Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations

View ORCID ProfileJanneke Wit, Matthew L. Workentine, Elizabeth Redman, Roz Laing, Lewis Stevens, James A. Cotton, Umer Chaudhry, Qasim Ali, View ORCID ProfileErik C. Andersen, Samuel Yeaman, View ORCID ProfileJames D. Wasmuth, View ORCID ProfileJohn S. Gilleard
doi: https://doi.org/10.1101/2022.04.05.487096
Janneke Wit
1Department of Comparative Biology and Experimental Medicine, Host -Parasite Interactions (HPI) program, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Janneke Wit
  • For correspondence: jannekewit@gmail.com jsgillea@ucalgary.ca
Matthew L. Workentine
2Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elizabeth Redman
1Department of Comparative Biology and Experimental Medicine, Host -Parasite Interactions (HPI) program, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Roz Laing
3Institute of Biodiversity Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Garscube Campus, Glasgow, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lewis Stevens
4Tree of Life, Wellcome Sanger Institute, Cambridge, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James A. Cotton
5Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK. CB10 1SA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Umer Chaudhry
6University of Edinburgh, Roslin Institute, Easter Bush Veterinary Centre, Roslin, Midlothian, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Qasim Ali
7Department of Veterinary Parasitology, University of Veterinary and Animal Sciences Lahore, Pakistan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Erik C. Andersen
8Molecular Biosciences, Northwestern University, Evanston, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Erik C. Andersen
Samuel Yeaman
9Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James D. Wasmuth
10Department of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for James D. Wasmuth
John S. Gilleard
1Department of Comparative Biology and Experimental Medicine, Host -Parasite Interactions (HPI) program, University of Calgary, Calgary, Alberta, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for John S. Gilleard
  • For correspondence: jannekewit@gmail.com jsgillea@ucalgary.ca
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

ABSTRACT

Genome-wide methods offer a powerful approach to detect signatures of drug selection in parasite populations in the field. However, their application to parasitic nematodes has been limited because of both a lack of suitable reference genomes and the difficulty of obtaining field populations with sufficiently well-defined drug selection histories. Consequently, there is little information on the genomic signatures of drug selection for parasitic nematodes in the field and on how best to detect them. This study was designed to address these knowledge gaps using field populations of Haemonchus contortus with well-defined and contrasting benzimidazole-selection histories, leveraging a recently completed chromosomal-scale reference genome assembly. We generated a panel of 49,393 ddRADseq markers and used this resource to genotype 20 individual H. contortus adult worms from each of four H. contortus populations: two from closed sheep flocks that had an approximately 20-year history of frequent treatment exclusively with benzimidazole drugs, and two populations with a history of little or no drug treatment. The populations were chosen from the same geographical region to limit population structure in order to maximize the sensitivity of the approach. A clear signature of selection was detected on the left arm of chromosome I centered on the isotype-1 β-tubulin gene in the benzimidazole-selected but not the unselected populations. Two additional, but weaker, signatures of selection were detected; one near the middle of chromosome I and one near the isotype-2 β-tubulin locus on chromosome II. We examined genetic differentiation between populations, and nucleotide diversity and linkage disequilibrium within populations to define these two additional regions as encompassing five genes and a single gene. We also compared the relative power of using pooled versus individual worm sequence data to detect genomic selection signatures and how sensitivity is impacted by sequencing depth, worm number, and population structure.

In summary, this study used H. contortus field populations with well-defined drug selection histories to provide the first direct genome-wide evidence for any parasitic nematode that the isotype-1 β-tubulin gene is the quantitatively most important benzimidazole resistance locus. It also identified two additional genomic regions that likely contain benzimidazole-resistance loci of secondary importance. Finally, this study provides an experimental framework to maximize the power of genome-wide approaches to detect signatures of selection driven by anthelmintic drug treatments in field populations of parasitic nematodes.

AUTHOR SUMMARY Benzimidazoles are important anthelmintic drugs for human and animal parasitic nematode control with ∼0.5 billion children at risk of infection treated annually worldwide. Drug resistance is common in livestock parasites and a growing concern in humans. Haemonchus contortus is the most important model parasite system used to study anthelmintic resistance and a significant livestock pathogen. It is also one of the few parasitic nematodes with a chromosomal-scale genome assembly. We have undertaken genome-wide scans using a dense RADseq marker panel on worms from natural field populations under differing levels of benzimidazole selection. We show that there is a single predominant genomic signature of selection in H. contortus associated with benzimidazole selection centred on the isotype-1 β-tubulin locus. We also identify two weaker signatures of selection indicative of secondary drug resistance loci. Additionally, we assess the minimum data requirements for parameters including worm number, sequence depth, marker density needed to detect the signatures of selection and compare individual to Poolseq analysis. This work is the first genome-wide study in a parasitic nematode to provide direct evidence of the isotype-1 β-tubulin locus being the single predominant benzimidazole resistance locus and provides an experimental framework for future population genomic studies on anthelmintic resistance.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted April 07, 2022.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations
Janneke Wit, Matthew L. Workentine, Elizabeth Redman, Roz Laing, Lewis Stevens, James A. Cotton, Umer Chaudhry, Qasim Ali, Erik C. Andersen, Samuel Yeaman, James D. Wasmuth, John S. Gilleard
bioRxiv 2022.04.05.487096; doi: https://doi.org/10.1101/2022.04.05.487096
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations
Janneke Wit, Matthew L. Workentine, Elizabeth Redman, Roz Laing, Lewis Stevens, James A. Cotton, Umer Chaudhry, Qasim Ali, Erik C. Andersen, Samuel Yeaman, James D. Wasmuth, John S. Gilleard
bioRxiv 2022.04.05.487096; doi: https://doi.org/10.1101/2022.04.05.487096

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4684)
  • Biochemistry (10361)
  • Bioengineering (7682)
  • Bioinformatics (26340)
  • Biophysics (13534)
  • Cancer Biology (10692)
  • Cell Biology (15445)
  • Clinical Trials (138)
  • Developmental Biology (8501)
  • Ecology (12824)
  • Epidemiology (2067)
  • Evolutionary Biology (16867)
  • Genetics (11401)
  • Genomics (15484)
  • Immunology (10619)
  • Microbiology (25224)
  • Molecular Biology (10225)
  • Neuroscience (54481)
  • Paleontology (402)
  • Pathology (1669)
  • Pharmacology and Toxicology (2897)
  • Physiology (4345)
  • Plant Biology (9252)
  • Scientific Communication and Education (1586)
  • Synthetic Biology (2558)
  • Systems Biology (6781)
  • Zoology (1466)