- Open Access
Genome-wide association studies in Plasmodiumspecies
© Penman et al; licensee BioMed Central Ltd. 2010
- Received: 07 June 2010
- Accepted: 23 June 2010
- Published: 13 July 2010
Genome-wide association studies (GWAS) look for correlations between traits of interest and genetic markers spread throughout the genome. A recent study in BMC Genetics has found that populations of the malaria parasite Plasmodium vivax should be amenable to GWAS searching for a genetic basis of parasite pathogenicity. Geographical substructure in populations may, however, prove a problem in interpreting the results.
See research article http://www.biomedcentral.com/1471-2156/11/65
- Malaria Parasite
- Severe Malaria
- Malaria Endemicity
- Parasite Genome
The first and fundamental consideration in planning a GWAS is how much the trait of interest is likely to be influenced by genetics at all. In the case of a trait such as virulence, it may be that the host's genetics are far more important than the parasite's, and looking at the parasite genome is not going to turn up a useful result. A recent paper by Anderson et al.  considers how to approach this issue in another malaria parasite, Plasmodium falciparum. Here, the authors used microsatellite analysis to determine the relatedness between parasites obtained from 185 patients. Microsatellite analysis is cheap and quick, as appreciated by any daytime TV viewer who has seen it used for talk-show paternity tests. If parasite relatedness correlates with a trait, then parasite genetics are likely to be important in governing that trait. They found that parasite relatedness was correlated with drug resistance, but that the rate of parasite clearance following artemisinin-based combination therapies was not.
Once a trait is identified as having a strong genetic link, we may be justified in conducting a GWAS to look for the genes responsible. However, the very nature of a GWAS presents another problem - this time, statistical. It is well recognized that when processing such large datasets as provided by GWAS, performing many tests looking for associations, there is the high possibility of obtaining an apparently significant association purely by chance. The great evolutionary biologist John Maynard Smith once said: 'statistics is the science that lets you do 20 experiments a year and publish one false result in Nature'. There are statistical means for correcting for multiple comparisons - for example, the Bonferroni correction - but these are so stringent that they make it hard to find any effects at all. There is no simple solution to this problem ; ultimately we have to rely on the judgement of informed scientists concerning the nature of the genes identified by the analysis. Perhaps this all illustrates that, fortunately, there is no immediate possibility of science being conducted by robots chucking things into sequencers and computer programs analyzing the data and emailing the results to big Pharma.
A third issue to be overcome if a GWAS is to give useful results is the choice of the genetic markers themselves. These markers are single nucleotide polymorphisms (SNPs), and it is vital to choose the correct set of reference SNPs for the question of interest. The older the mutation governing a trait, or the lower the degree of linkage disequilibrium in a population, the higher the density of SNPs required. In malaria parasites, the ratio of self-fertilizing to cross-fertilizing reproductive events is extremely variable in different malaria parasite populations, and is affected by natural selection. This complicates assumptions about linkage disequilibrium across different parts of the genome and increases the density of SNPs required for successful association mapping.
The crucial importance of choosing the correct set of reference SNPs in a GWAS is well illustrated by efforts to explore human genes that influence malaria susceptibility. The mutation responsible for sickle-cell anemia (a point mutation at the beta-globin locus) is known to offer substantial protection against severe malaria (for a review, see ). Jallow et al.  conducted a GWAS of severe malaria in Gambian children, and used the sickle-cell mutation as a benchmark to detect the success of different GWAS methods. When a reference sample from a non-Gambian African population (the Yoruba HapMap sample) was used to analyze the Gambian data, no signal could be detected for the sickle-cell mutation (even though at a macroscopic level the Yoruba and Gambian patterns of linkage disequilibrium appeared similar). Choosing the wrong set of reference SNPs therefore presents a huge potential pitfall for GWAS.
The study by Orjuela-Sanchéz et al.  hints at the possibility of conserved recombination hotspots within P. vivax; such hotspots, as they note, have also been observed in Plasmodium falciparum . The identification and confirmation of hotspots will play an important part in the design and analysis of future GWAS in both of these malaria parasites.
The very first Plasmodium GWAS was published by Mu et al.  in December 2009. The authors analyzed 189 P. falciparum isolates from Asia (146 isolates), Africa (26 isolates), America (14 isolates) and Papua New Guinea (3 isolates), and conducted a GWAS looking for genes associated with drug resistance. They were able to identify a gene (PFA0665w) that had not previously been associated with the parasite response to antimalarials. As discussed earlier, drug resistance seems to be a trait largely governed by parasite genetics and is thus clearly an area where parasite GWAS may continue to prove helpful. However, as noted by Orjuela-Sanchéz et al. , gene copy number variation (CNV) can contribute to drug-resistance phenotypes in addition to point mutation. Future GWAS in malaria parasites will need to take CNV into account, and methods are being developed to make this possible .
Orjuela-Sanchéz et al.  make two additional points of broad interest for the GWAS field and beyond. For P. falciparum, geographical regions of high transmission have greater genetic diversity than regions with low transmission [11, 12]. We expect this relationship because high transmission means higher population sizes of the parasite and lower levels of inbreeding. However, Orjuela-Sanchéz et al. identified the opposite relationship between P. vivax endemicity and genetic diversity: they observed the highest levels of diversity in their Sri Lankan sample (which came from their area of lowest malaria endemicity), and the lowest in their Vietnamese sample (which came from their area of highest malaria endemicity). Given the aforementioned problems about statistical artifacts in GWAS, such a pattern requires further confirmation - but it is certainly an intriguing result.
Second, their study's investigation of mutations in a known resistance locus found evidence in support of the hypothesis that chloroquine resistance at that locus requires a two-step mutation process. This has previously been suggested by  and raises the important possibility using detection of the first mutation as an early warning system for the imminent emergence of drug resistance in a vivax population.
It is important to recognize that these are early days in the development of a very exciting new technique, and that it is not surprising that more questions than answers have arisen from its application so far. There are strong analogies here to administering a large questionnaire to a population and hoping that some clear connections will fall out. We know from such experience that patience is necessary, as are continuous refinements of the technique, and continuous revision of the right questions to ask. The pieces of the complex jigsaw may take a long time to clink together, and it is crucial that the faith of the researchers is located in its long-term outcomes.
- Ku CS, Loy EY, Pawitan Y, Chia KS: The pursuit of genome-wide association studies: where are we now?. J Hum Genet. 2010, 55: 195-206. 10.1038/jhg.2010.19.View ArticlePubMedGoogle Scholar
- Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA: Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA. 2009, 106: 9362-9367. 10.1073/pnas.0903103106.PubMed CentralView ArticlePubMedGoogle Scholar
- Orjuela-Sanchéz P, Karunaweera ND, da Silva-Nunes M, da Silva N, Scopel KKG, Gonçlaves RM, Amaratunga C, Sá JM, Socheat D, Fairhurst RM, Gunawardena S, Thavakodirasah T, Galpaththy GNL, Abeysinghe R, Kawamoto F, Wirth DF, Ferreira MU: Single-nucleotide polymorphism, linkage disequilibrium and geographic structure in the malaria parasite Plasmodium vivax: prospects for genome-wide association studies. BMC Genet. 2010, 11: 65-10.1186/1471-2350-11-65.PubMed CentralView ArticlePubMedGoogle Scholar
- Anderson TJC, Williams JT, Nair S, Sudimack D, Barends M, Jaidee A, Price RN, Nosten F: Inferred relatedness and heritability in malaria parasites. Proc Bio Sci. published online 14 April 2010, DOI: 10.1098/rspb.2010.0196Google Scholar
- Rothman KJ: No adjustments are needed for multiple comparisons. Epidemiology. 1990, 1: 43-46. 10.1097/00001648-199001000-00010.View ArticlePubMedGoogle Scholar
- Williams TN: Red blood cell defects and malaria. Mol Biochem Parasitol. 2006, 149: 121-127. 10.1016/j.molbiopara.2006.05.007.View ArticlePubMedGoogle Scholar
- Jallow M, Teo YY, Small KS, Rockett KA, Deloukas P, Clark TG, Kivinen K, Bojang KA, Conway DJ, Pinder M, Sirugo G, Sisay-Joof F, Usen S, Auburn S, Bumpstead SJ, Campino S, Coffey A, Dunham A, Fry AE, Green A, Gwilliam R, Hunt SE, Inouye M, Jeffreys AE, Mendy A, Palotie A, Potter S, Ragoussis J, Rogers J, Rowlands K, et al: Genome-wide and fine-resolution association analysis of malaria in West Africa. Nat Genet. 2009, 41: 657-665. 10.1038/ng.388.PubMed CentralView ArticlePubMedGoogle Scholar
- Mu J, Awadalla P, Duan J, McGee KM, Joy DA, McVean GAT, Su XZ: Recombination hotspots and population structure in Plasmodium falciparum. PLoS Biol. 2005, 3: e335-10.1371/journal.pbio.0030335.PubMed CentralView ArticlePubMedGoogle Scholar
- Mu J, Myers RA, Jiang H, Liu S, Ricklefs S, Waisberg M, Chotivanich K, Wilairatana P, Krudsood S, White NJ, Udomsangpetch R, Cui L, Ho M, Ou F, Li H, Song J, Li G, Wang X, Seila S, Sokunthea S, Socheat D, Sturdevant DE, Porcella SF, Fairhurst RM, Wellems TE, Awadalla P, Su XZ: Plasmodium falciparum genome-wide scans for positive selection, recombination hot spots and resistance to antimalarial drugs. Nat Genet. 2010, 42: 268-271. 10.1038/ng.528.PubMed CentralView ArticlePubMedGoogle Scholar
- McCarroll SA: Extending genome-wide association studies to copy-number variation. Hum Mol Genet. 2008, 17: R135-R142. 10.1093/hmg/ddn282.View ArticlePubMedGoogle Scholar
- Anderson TJC, Haubold B, Williams JT, Estrada-Franco JG, Richardson L, Mollinedo R, Bockarie M, Mokili J, Mharakurwa S, French N, Whitworth J, Velez ID, Brockman AH, Nosten F, Ferreira MU, Day KP: Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Mol Biol Evol. 2000, 17: 1467-1482.View ArticlePubMedGoogle Scholar
- Neafsey DE, Schaffner SF, Volkman SK, Park D, Montgomery P, Milner DA, Lukens A, Rosen D, Daniels R, Houde N, Cortese JF, Tyndall E, Gates C, Stange-Thomann N, Sarr O, Ndiaye D, Ndir O, Mboup S, Ferreira MU, Moraes S, Dash AP, Chitnis CE, Wiegand RC, Hartl DL, Birren BW, Lander ES, Sabeti PC, Wirth DF: Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence. Genome Biol. 2008, 9: R171-10.1186/gb-2008-9-12-r171.PubMed CentralView ArticlePubMedGoogle Scholar
- Brega S, Meslin B, De Monbrison F, Severini C, Gradoni L, Udomsangpetch R, Sutanto I, Peyron F, Picot S: Identification of the Plasmodium vivax mdr-like gene (pvmdr1) and analysis of single-nucleotide polymorphisms among isolates from different areas of endemicity. J Infect Dis. 2005, 191: 272-277. 10.1086/426830.View ArticlePubMedGoogle Scholar
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