Evidence map›Paper›PMID 25830531›Full record

ArticlePloS one2015

Plasmodium knowlesi genome sequences from clinical isolates reveal extensive genomic dimorphism.

Miguel M Pinheiro, Md Atique Ahmed, Scott B Millar, Theo Sanderson, Thomas D Otto, Woon Chan Lu, Sanjeev Krishna, Julian C Rayner, Janet Cox-Singh

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. International journal of molecular sciences · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. In Silico Analysis Reveals High Levels of Genetic Diversity ofTropical medicine and infectious disease · 2023
    Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Frontiers in genetics · 2022
    Article
  14. Review
  15. Frontiers in cellular and infection microbiology · 2021
    Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Miguel M PinheiroSchool of Medicine, University of St Andrews, Medical and Biological Sciences Building, North Haugh, St Andrews, United Kingdom.
Md Atique AhmedMalaria Research Centre, University Malaysia Sarawak, Kuching, Sarawak, Malaysia.
Scott B MillarSchool of Medicine, University of St Andrews, Medical and Biological Sciences Building, North Haugh, St Andrews, United Kingdom.
Theo SandersonMalaria Programme, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
Thomas D OttoMalaria Programme, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
Woon Chan LuSarikei Hospital, Sarikei, Sarawak, 96100, Malaysia.
Sanjeev KrishnaDivision of Clinical Sciences, St. George's, University of London, London, United Kingdom.
Julian C RaynerMalaria Programme, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
Janet Cox-SinghSchool of Medicine, University of St Andrews, Medical and Biological Sciences Building, North Haugh, St Andrews, United Kingdom.

Funding

Great Ape Reservoirs of Human MalariaR01AI091595 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI HAHN, BEATRICE H · 2011 to 2019
$5.3M
Medical Research Council G0801971Medical Research Council MR/J500355/1NIAID NIH HHS R01 AI091595Wellcome TrustWellcome Trust 097831/Z/11/ZWellcome Trust 098051
6 · The paper itself

Abstract

Plasmodium knowlesi is a newly described zoonosis that causes malaria in the human population that can be severe and fatal. The study of P. knowlesi parasites from human clinical isolates is relatively new and, in order to obtain maximum information from patient sample collections, we explored the possibility of generating P. knowlesi genome sequences from archived clinical isolates. Our patient sample collection consisted of frozen whole blood samples that contained excessive human DNA contamination and, in that form, were not suitable for parasite genome sequencing. We developed a method to reduce the amount of human DNA in the thawed blood samples in preparation for high throughput parasite genome sequencing using Illumina HiSeq and MiSeq sequencing platforms. Seven of fifteen samples processed had sufficiently pure P. knowlesi DNA for whole genome sequencing. The reads were mapped to the P. knowlesi H strain reference genome and an average mapping of 90% was obtained. Genes with low coverage were removed leaving 4623 genes for subsequent analyses. Previously we identified a DNA sequence dimorphism on a small fragment of the P. knowlesi normocyte binding protein xa gene on chromosome 14. We used the genome data to assemble full-length Pknbpxa sequences and discovered that the dimorphism extended along the gene. An in-house algorithm was developed to detect SNP sites co-associating with the dimorphism. More than half of the P. knowlesi genome was dimorphic, involving genes on all chromosomes and suggesting that two distinct types of P. knowlesi infect the human population in Sarawak, Malaysian Borneo. We use P. knowlesi clinical samples to demonstrate that Plasmodium DNA from archived patient samples can produce high quality genome data. We show that analyses, of even small numbers of difficult clinical malaria isolates, can generate comprehensive genomic information that will improve our understanding of malaria parasite diversity and pathobiology.

Indexed as

Genome, ProtozoanChromosome MappingDNA, ProtozoanHigh-Throughput Nucleotide SequencingHumansLinkage DisequilibriumMalariaMultiplex Polymerase Chain ReactionPlasmodium knowlesiPolymorphism, Single NucleotideProtozoan ProteinsSequence Analysis, DNADNA, ProtozoanProtozoan Proteins

Identifiers

PMID25830531
PMCPMC4382175

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.