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Genetic mapping of fitness determinants across the malaria parasite Plasmodium falciparum life cycle.

Xue Li | Sudhir Kumar | Marina McDew-White | Meseret Haile | Ian H Cheeseman | Scott Emrich | Katie Button-Simons | François Nosten | Stefan H I Kappe | Michael T Ferdig | Tim J C Anderson | Ashley M Vaughan
PLoS genetics | 2019

Determining the genetic basis of fitness is central to understanding evolution and transmission of microbial pathogens. In human malaria parasites (Plasmodium falciparum), most experimental work on fitness has focused on asexual blood stage parasites, because this stage can be easily cultured, although the transmission of malaria requires both female Anopheles mosquitoes and vertebrate hosts. We explore a powerful approach to identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-cycle stages of P. falciparum. This combines experimental genetic crosses using humanized mice, with selective whole genome amplification and pooled sequencing to determine genome-wide allele frequencies and identify genomic regions under selection across multiple lifecycle stages. We applied this approach to genetic crosses between artemisinin resistant (ART-R, kelch13-C580Y) and ART-sensitive (ART-S, kelch13-WT) parasites, recently isolated from Southeast Asian patients. Two striking results emerge: we observed (i) a strong genome-wide skew (>80%) towards alleles from the ART-R parent in the mosquito stage, that dropped to ~50% in the blood stage as selfed ART-R parasites were selected against; and (ii) repeatable allele specific skews in blood stage parasites with particularly strong selection (selection coefficient (s) ≤ 0.18/asexual cycle) against alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 containing ARPS10. This approach robustly identifies selected loci and has strong potential for identifying parasite genes that interact with the mosquito vector or compensatory loci involved in drug resistance.

Pubmed ID: 31609965

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: Wellcome Trust, United Kingdom
  • Agency: NCRR NIH HHS, United States
    Id: C06 RR013556
  • Agency: NIAID NIH HHS, United States
    Id: P01 AI127338
  • Agency: NIAID NIH HHS, United States
    Id: R37 AI048071

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GATK (tool)

RRID:SCR_001876

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

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Dryad Digital Repository (tool)

RRID:SCR_005910

International, curated, digital repository that makes the data underlying scientific publications discoverable, freely reusable, and citable. Particularly data for which no specialized repository exists. Provides the infrastructure for, and promotes the re-use of, data underlying the scholarly literature. Governed by a nonprofit membership organization. Membership is open to any stakeholder organization, including but not limited to journals, scientific societies, publishers, research institutions, libraries, and funding organizations. Most data are associated with peer-reviewed articles, although data associated with non-peer reviewed publications from reputable academic sources, such as dissertations, are also accepted. Used to validate published findings, explore new analysis methodologies, repurpose data for research questions unanticipated by the original authors, and perform synthetic studies.UC system is member organization of Dryad general subject data repository.

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Picard (tool)

RRID:SCR_006525

Java toolset for working with next generation sequencing data in the BAM format.

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BWA (tool)

RRID:SCR_010910

Software for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.

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National Institutes of Health (tool)

RRID:SCR_011417

NIH is the nations medical research agency - making important medical discoveries that improve health and save lives. The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the primary Federal agency for conducting and supporting medical research. Helping to lead the way toward important medical discoveries that improve peoples health and save lives, NIH scientists investigate ways to prevent disease as well as the causes, treatments, and even cures for common and rare diseases. NIH research impacts: * child and teen health, * men's health, * minority health, * seniors' health, * women's health, and * wellness and lifestyle issues. Composed of 27 Institutes and Centers, the NIH provides leadership and financial support to researchers in every state and throughout the world.

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PlasmoDB (tool)

RRID:SCR_013331

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

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