Browsing by Author "Johnson, K.J."
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Item A novel locus of resistance to severe malaria in a region of ancient balancing selection.(Nature Publishing Group, 2015-09) Band, G.; Rockett, K.A.; Spencer, C.C.A.; Johnson, K.J.; Koram, K.A.; Wilson, M.D.; Agbenyega, T.; Malaria Genomic Epidemiology NetworkAbstract The high prevalence of sickle haemoglobin in Africa shows that malaria has been a major force for human evolutionary selection, but surprisingly few other polymorphisms have been proven to confer resistance to malaria in large epidemiological studies. To address this problem, we conducted a multi-centre genome-wide association study (GWAS) of life-threatening Plasmodium falciparum infection (severe malaria) in over 11,000 African children, with replication data in a further 14,000 individuals. Here we report a novel malaria resistance locus close to a cluster of genes encoding glycophorins that are receptors for erythrocyte invasion by P. falciparum. We identify a haplotype at this locus that provides 33% protection against severe malaria (odds ratio = 0.67, 95% confidence interval = 0.60-0.76, P value = 9.5 × 10(-11)) and is linked to polymorphisms that have previously been shown to have features of ancient balancing selection, on the basis of haplotype sharing between humans and chimpanzees. Taken together with previous observations on the malaria-protective role of blood group O, these data reveal that two of the strongest GWAS signals for severe malaria lie in or close to genes encoding the glycosylated surface coat of the erythrocyte cell membrane, both within regions of the genome where it appears that evolution has maintained diversity for millions of years. These findings provide new insights into the host-parasite interactions that are critical in determining the outcome of malaria infection.Item An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples(2021) MalariaGEN; Ahouidi, A.; Ali, M.; Almagro-Garcia, J.; Amambua-Ngwa, A.; Amaratunga, C.; Amato, R.; Amenga-Etego, L.; Andagalu, B.; Anderson, T.J.C.; Andrianaranjaka, V.; Apinjoh, T.; Ariani, C.; Ashley, E.A.; Auburn, S.; Awandare, G.A.; Ba, H.; Baraka, V.; Barry, A.E.; Bejon, P.; Bertin, G.I.; Boni, M.F.; Borrmann, S.; Bousema, T.; Branch, O.; Bull, P.C.; Busby, G.B.J.; Chookajorn, T.; Chotivanich, K.; Claessens, A.; Conway, D.; Craig, A.; D'Alessandro, U.; Dama, S.; Day, N.P.J.; Denis, B.; Diakite, M.; Djimdé, A.; Dolecek, C.; Dondorp, A.M.; Drakeley, C.; Drury, E.; Duffy, P.; Echeverry, D.F.; Egwang, T.G.; Erko, B.; Fairhurst, R.M.; Faiz, A.; Fanello, C.A.; Fukuda, M.M.; Gamboa, D.; Ghansah, A.; Golassa, L.; Goncalves, S.; Hamilton, W.L.; Harrison, G.L.A.; Hart, L.; Henrichs, C.; Hien, T.T.; Hill, C.A.; Hodgson, A.; Hubbart, C.; Imwong, M.; Ishengoma, D.S.; Jackson, S.A.; Jacob, C.G.; Jeffery, B.; Jeffreys, A.E.; Johnson, K.J.; Jyothi, D.; Kamaliddin, C.; Kamau, E.; Kekre, M.; Kluczynski, K.; Kochakarn, T.; Konaté, A.; Kwiatkowski, D.P.; Kyaw, M.P.; Lim, P.; Lon, C.; Loua, K.M.; Maïga-Ascofaré, O.; Malangone, C.; Manske, M.; Marfurt, J.; Marsh, K.; Mayxay, M.; Miles, A.; Miotto, O.; Mobegi, V.; Mokuolu, O.A.; Montgomery, J.; Mueller, I.; Newton, P.N.; Nguyen, T.; Nguyen, T.; Noedl, H.; Nosten, F.; Noviyanti, R.; Nzila, A.; Ochola-Oyier, L.I.; Ocholla, H.; Oduro, A.; Omedo, I.; Onyamboko, M.A.; Ouedraogo, J.; Oyebola, K.; Pearson, R.D.; Peshu, N.; Phyo, A.P.; Plowe, C.V.; Price, R.N.; Pukrittayakamee, S.; Randrianarivelojosia, M.; Rayner, J.C.; Ringwald, P.; Rockett, K.A.; Rowlands, K.; Ruiz, L.; Saunders, D.; Shayo, A.; Siba, P.; Simpson, V.J.; Stalker, J.; Su, X.; Sutherland, C.; Takala-Harrison, S.; Tavul, L.; Thathy, V.; Tshefu, A.; Verra, F.; Vinetz, J.; Wellems, T.E.; Wendler, J.; White, N.J.; Wright, I.; Yavo, W.; Ye, H.MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.