Genome-wide locus sequence typing (GLST) of eukaryotic pathogens Article Swipe
Philipp Schwabl
,
Jalil Maiguashca Sánchez
,
Jaime A. Costales
,
Sofía Ocaña-Mayorga
,
Maikell Segovia
,
H. Carrasco
,
Carolina Hernández
,
Juan David Ramírez
,
Michael D. Lewis
,
Mario J. Grijalva
,
Martin Llewellyn
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.03.24.003590
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1101/2020.03.24.003590
Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from vector/host material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective ‘genome-wide locus sequence typing’ (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Approximately 100 libraries can be sequenced together in one Illumina MiSeq run. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi , the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/μl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate DTUs. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.
Related Topics
Concepts
Biology
Genetics
Locus (genetics)
Typing
Genome
Computational biology
Multilocus sequence typing
Genotype
Gene
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2020.03.24.003590
- https://www.biorxiv.org/content/biorxiv/early/2020/03/25/2020.03.24.003590.full.pdf
- OA Status
- green
- Cited By
- 2
- References
- 113
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3013961599
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3013961599Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2020.03.24.003590Digital Object Identifier
- Title
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Genome-wide locus sequence typing (GLST) of eukaryotic pathogensWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-03-25Full publication date if available
- Authors
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Philipp Schwabl, Jalil Maiguashca Sánchez, Jaime A. Costales, Sofía Ocaña-Mayorga, Maikell Segovia, H. Carrasco, Carolina Hernández, Juan David Ramírez, Michael D. Lewis, Mario J. Grijalva, Martin LlewellynList of authors in order
- Landing page
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https://doi.org/10.1101/2020.03.24.003590Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2020/03/25/2020.03.24.003590.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2020/03/25/2020.03.24.003590.full.pdfDirect OA link when available
- Concepts
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Biology, Genetics, Locus (genetics), Typing, Genome, Computational biology, Multilocus sequence typing, Genotype, GeneTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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113Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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