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1. Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

Author

Hamid, M.M.A., Abdelraheem, M.H., Acheampong, D.O., Ahouidi, A., Ali, M, Almagro-Garcia, J., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andagalu, B., Anderson, T., Andrianaranjaka, V., Aniebo, I., Aninagyei, E., Ansah, F., Ansah, P.O., Apinjoh, T., Arnaldo, P., Ashley, E., Auburn, S., Awandare, G.A., Ba, H., Baraka, V., Barry, A., Bejon, P., Bertin, G.I., Boni, M.F., Borrmann, S., Bousema, T., Bouyou-Akotet, M., Branch, O., Bull, P.C., Cheah, H., Chindavongsa, K., Chookajorn, T., Chotivanich, K., Claessens, A., Conway, D.J., Corredor, V., Courtier, E., Craig, A., D'Alessandro, U., Dama, S., Day, N., Denis, B., Dhorda, M., Diakite, M., Djimde, A., Dolecek, C., Dondorp, A., Doumbia, S., Drakeley, C., Drury, E., Duffy, P., Echeverry, D.F., Egwang, T.G., Enosse, S.M.M., Erko, B., Fairhurst, R.M., Faiz, A., Fanello, C.A., Fleharty, M., Forbes, M., Fukuda, M., Gamboa, D., Ghansah, A., Golassa, L., Goncalves, S., Harrison, G.L.A., Healy, Sara A., Hendry, J.A., Hernandez-Koutoucheva, A., Hien, T.T., Hill, C.A., Hombhanje, F., Hott, A., Htut, Y., Hussein, M., Imwong, M., Ishengoma, D., Jackson, S.A., Jacob, C.G., Jeans, J., Johnson, K.J., Kamaliddin, C., Kamau, E., Keatley, J., Kochakarn, T., Konate, D.S., Konaté, A., Kone, A., Kwiatkowski, D.P., Kyaw, M.P., Kyle, D., Lawniczak, M., Lee, S.K., Lemnge, M., Lim, P., Lon, C., Yavo, W., Pluijm, R.W. van der, Hamid, M.M.A., Abdelraheem, M.H., Acheampong, D.O., Ahouidi, A., Ali, M, Almagro-Garcia, J., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andagalu, B., Anderson, T., Andrianaranjaka, V., Aniebo, I., Aninagyei, E., Ansah, F., Ansah, P.O., Apinjoh, T., Arnaldo, P., Ashley, E., Auburn, S., Awandare, G.A., Ba, H., Baraka, V., Barry, A., Bejon, P., Bertin, G.I., Boni, M.F., Borrmann, S., Bousema, T., Bouyou-Akotet, M., Branch, O., Bull, P.C., Cheah, H., Chindavongsa, K., Chookajorn, T., Chotivanich, K., Claessens, A., Conway, D.J., Corredor, V., Courtier, E., Craig, A., D'Alessandro, U., Dama, S., Day, N., Denis, B., Dhorda, M., Diakite, M., Djimde, A., Dolecek, C., Dondorp, A., Doumbia, S., Drakeley, C., Drury, E., Duffy, P., Echeverry, D.F., Egwang, T.G., Enosse, S.M.M., Erko, B., Fairhurst, R.M., Faiz, A., Fanello, C.A., Fleharty, M., Forbes, M., Fukuda, M., Gamboa, D., Ghansah, A., Golassa, L., Goncalves, S., Harrison, G.L.A., Healy, Sara A., Hendry, J.A., Hernandez-Koutoucheva, A., Hien, T.T., Hill, C.A., Hombhanje, F., Hott, A., Htut, Y., Hussein, M., Imwong, M., Ishengoma, D., Jackson, S.A., Jacob, C.G., Jeans, J., Johnson, K.J., Kamaliddin, C., Kamau, E., Keatley, J., Kochakarn, T., Konate, D.S., Konaté, A., Kone, A., Kwiatkowski, D.P., Kyaw, M.P., Kyle, D., Lawniczak, M., Lee, S.K., Lemnge, M., Lim, P., Lon, C., Yavo, W., and Pluijm, R.W. van der

Abstract

Item does not contain fulltext, We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network. It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented. For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations. We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent. We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines. Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website.

Published
2023

2. An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

Author

Ahouidi, A., Ali, M, Almagro-Garcia, J., Amambua-Ngwa, A., Amaratunga, C., Amato, R., Amenga-Etego, L., Andagalu, B., Anderson, T.J., 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., 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. 't, 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.N.D., Noedl, H., Nosten, F., Noviyanti, R., Nzila, A., Ochola-Oyier, L.I., and MalariaGEN

Subjects
0301 basic medicine, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, lnfectious Diseases and Global Health Radboud Institute for Health Sciences [Radboudumc 4], 030231 tropical medicine, parasitic diseases, Medicine (miscellaneous), General Biochemistry, Genetics and Molecular Biology, 3. Good health
Abstract

Contains fulltext : 238195.pdf (Publisher’s version ) (Open Access) 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.

Published
2021

3. An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

Author

MalariaGEN, Ahouidi, A, Ali, M, Almagro-Garcia, J, Amambua-Ngwa, A, Amaratunga, C, Amato, R, Amenga-Etego, L, Andagalu, B, Anderson, TJC, Andrianaranjaka, V, Apinjoh, T, Ariani, C, Ashley, EA, Auburn, S, Awandare, GA, Ba, H, Baraka, V, Barry, Alyssa, Bejon, P, Bertin, GI, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Busby, GBJ, Chookajorn, T, Chotivanich, K, Claessens, A, Conway, D, Craig, A, D'Alessandro, U, Dama, S, Day, NP, Denis, B, Diakite, M, Djimdé, A, Dolecek, C, Dondorp, AM, Drakeley, C, Drury, E, Duffy, P, Echeverry, DF, Egwang, TG, Erko, B, Fairhurst, RM, Faiz, A, Fanello, CA, Fukuda, MM, Gamboa, D, Ghansah, A, Golassa, L, Goncalves, S, Hamilton, WL, Harrison, GLA, Hart, L, Henrichs, C, Hien, TT, Hill, CA, Hodgson, A, Hubbart, C, Imwong, M, Ishengoma, DS, Jackson, SA, Jacob, CG, Jeffery, B, Jeffreys, AE, Johnson, KJ, Jyothi, D, Kamaliddin, C, Kamau, E, Kekre, M, Kluczynski, K, Kochakarn, T, Konaté, A, Kwiatkowski, DP, Kyaw, MP, Lim, P, Lon, C, Loua, KM, Maïga-Ascofaré, O, Malangone, C, Manske, M, Marfurt, J, Marsh, K, Mayxay, M, Miles, A, Miotto, O, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Newton, PN, Nguyen, T, Nguyen, T-N, Noedl, H, Nosten, F, Noviyanti, R, Nzila, A, Ochola-Oyier, LI, Ocholla, H, Oduro, A, Omedo, I, Onyamboko, MA, Ouedraogo, J-B, Oyebola, K, Pearson, RD, Peshu, N, Phyo, AP, Plowe, CV, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Rayner, JC, Ringwald, P, Rockett, KA, Rowlands, K, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Simpson, VJ, Stalker, J, Su, X-Z, Sutherland, C, Takala-Harrison, S, Tavul, L, Thathy, V, Tshefu, A, Verra, F, Vinetz, J, Wellems, TE, Wendler, J, White, NJ, Wright, I, Yavo, W, Ye, H, MalariaGEN, Ahouidi, A, Ali, M, Almagro-Garcia, J, Amambua-Ngwa, A, Amaratunga, C, Amato, R, Amenga-Etego, L, Andagalu, B, Anderson, TJC, Andrianaranjaka, V, Apinjoh, T, Ariani, C, Ashley, EA, Auburn, S, Awandare, GA, Ba, H, Baraka, V, Barry, Alyssa, Bejon, P, Bertin, GI, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Busby, GBJ, Chookajorn, T, Chotivanich, K, Claessens, A, Conway, D, Craig, A, D'Alessandro, U, Dama, S, Day, NP, Denis, B, Diakite, M, Djimdé, A, Dolecek, C, Dondorp, AM, Drakeley, C, Drury, E, Duffy, P, Echeverry, DF, Egwang, TG, Erko, B, Fairhurst, RM, Faiz, A, Fanello, CA, Fukuda, MM, Gamboa, D, Ghansah, A, Golassa, L, Goncalves, S, Hamilton, WL, Harrison, GLA, Hart, L, Henrichs, C, Hien, TT, Hill, CA, Hodgson, A, Hubbart, C, Imwong, M, Ishengoma, DS, Jackson, SA, Jacob, CG, Jeffery, B, Jeffreys, AE, Johnson, KJ, Jyothi, D, Kamaliddin, C, Kamau, E, Kekre, M, Kluczynski, K, Kochakarn, T, Konaté, A, Kwiatkowski, DP, Kyaw, MP, Lim, P, Lon, C, Loua, KM, Maïga-Ascofaré, O, Malangone, C, Manske, M, Marfurt, J, Marsh, K, Mayxay, M, Miles, A, Miotto, O, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Newton, PN, Nguyen, T, Nguyen, T-N, Noedl, H, Nosten, F, Noviyanti, R, Nzila, A, Ochola-Oyier, LI, Ocholla, H, Oduro, A, Omedo, I, Onyamboko, MA, Ouedraogo, J-B, Oyebola, K, Pearson, RD, Peshu, N, Phyo, AP, Plowe, CV, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Rayner, JC, Ringwald, P, Rockett, KA, Rowlands, K, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Simpson, VJ, Stalker, J, Su, X-Z, Sutherland, C, Takala-Harrison, S, Tavul, L, Thathy, V, Tshefu, A, Verra, F, Vinetz, J, Wellems, TE, Wendler, J, White, NJ, Wright, I, Yavo, W, and Ye, H

Abstract

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.

Published
2021

4. Global and local patterns of population structure and their role in the evolution and demography of Plasmodium falciparum

Author

Almagro-Garcia, J, Kwiatkowski, D, and McVean, G

Subjects
Malaria
Abstract

In this thesis, I study the role of genetic population structure in the evolution and demography of Plasmodium falciparum by focusing on the recent onset of artemisinin resistance in Southeast Asia, an alarming event for global public health. I describe the population structure of Plasmodium falciparum in the Thai-Cambodian border region, characterizing sympatric but differentiated subpopulations associated with artemisinin resistance. I show evidence that they are the product of recent founder events and seem the primary force spreading resistance. Next, I study a superset of the kelch13 mutations associated with artemisinin resistance, assessing their relationship with population structure and recent founder effects. Each resistant subpopulation possesses a distinct kelch13 allele that, in conjunction with a particular genetic background, seem to have driven recent founder effects. I examine the demography of these resistance alleles using patterns of haplotype sharing and show that the primary mode of spread consists of independent mutational events, with limited gene flow within countries in East Southeast Asia. Subsequently, I assess the origin of kelch13 mutations observed in African isolates, concluding that they are indigenous and have originated independently. These observations undermine localized resistance containment as a strategy for malaria control and suggest that population structure and founder effects may predate and facilitate the emergence of resistance. Therefore, monitoring these phenomena could warn about the development of resistance before phenotypic evidence materializes. Next, given the importance of demographic inference to inform malaria control programs and the advent of large genomic datasets, I develop a fast and scalable method to build the ancestral haplotype graph. I show that this data structure, composed of a collection of local haplotype trees, is informative about the recent genealogical history of the sequences and can be used to summarize and study shared haplotype patterns along the genome. I describe a set of algorithms with quasilinear time complexity as a first step in the development of scalable demographic inferential methods that can be applied to several thousands of sequences. I also evaluate how mixed infections affect the analysis of deep sequencing data and review the FWS statistic, a relative measure of inbreeding and complexity of infection. In doing so, I show that the original FWS estimator discards the diversity encoded by rare variants and provide an alternative estimator without such bias that is simpler, more intuitive and has a better resolution.

Published
2018

5. Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

Author

Manske, M, Miotto, O, Campino, S, Auburn, S, Almagro-Garcia, J, Maslen, G, O'Brien, J, Djimde, A, Doumbo, O, Zongo, I, Ouedraogo, JB, Michon, P, Mueller, I, Siba, P, Nzila, A, Borrmann, S, Kiara, SM, Marsh, K, Jiang, H, Su, XZ, Amaratunga, C, Fairhurst, R, Socheat, D, Nosten, F, Imwong, M, White, NJ, Sanders, M, Anastasi, E, Alcock, D, Drury, E, Oyola, S, Quail, MA, Turner, DJ, Ruano-Rubio, V, Jyothi, D, Amenga-Etego, L, Hubbart, C, Jeffreys, A, Rowlands, K, Sutherland, C, Roper, C, Mangano, V, Modiano, D, Tan, JC, Ferdig, MT, Amambua-Ngwa, A, Conway, DJ, Takala-Harrison, S, Plowe, CV, Rayner, JC, Rockett, KA, Clark, TG, Newbold, CI, Berriman, M, MacInnis, B, and Kwiatkowski, DP

Subjects
Genotype, 030231 tropical medicine, Population, Plasmodium falciparum, Genomics, Biology, Polymorphism, Single Nucleotide, Deep sequencing, Article, 03 medical and health sciences, 0302 clinical medicine, parasitic diseases, Humans, Genetic variability, Malaria, Falciparum, education, Genotyping, Alleles, Phylogeny, 030304 developmental biology, Genetics, Whole genome sequencing, 0303 health sciences, Genetic diversity, education.field_of_study, Principal Component Analysis, Multidisciplinary, High-Throughput Nucleotide Sequencing, Biodiversity, biology.organism_classification, 3. Good health, Genome, Protozoan
Abstract

methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genomewide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for the exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome. The genetic diversity and evolutionary plasticity of P. falciparum are major obstacles for malaria elimination. New forms of resistance against antimalarial drugs are continually emerging 1,2 , and new forms of antigenic variation are a critical point of vulnerability for future malaria vaccines. Effective tools are needed to detect evolutionary changes in the parasite population and to monitor the spread of genetic variants that affect malaria control. Here we describe the use of deep sequencing to analyse P. falciparum diversity, using blood samples from patients with malaria. The P. falciparum genome has several unusual features that greatly complicate sequence analysis, such as extreme AT bias, large tracts of nonunique sequence and several large families of intensely polymorphic genes 3 . Our aim was therefore not to determine the entire genome sequence of individual field samples—which would be prohibitively expensive with current technologies—but to define an initial set of single nucleotide polymorphisms (SNPs) distributed across the P. falciparum genome, whose genotype can be ascertained with confidence in parasitized blood samples by deep sequencing. An additional complication in the analysis of P. falciparum genome variation is that the billions of haploid parasites that infect a single individual can be a complex mixture of genetic types. Previous studies 4–8 have largely focused on laboratory-adapted parasite clones, but the within-host diversity of natural infections is of fundamental biological interest. Parasites in the blood replicate asexually, but when they are taken up in the blood meal of an Anopheles mosquito they undergo sexual mating. If the parasites in the blood are of diverse genetic types, this process of sexual mating can generate novel recombinant forms. Deep sequencing provides new ways of investigating within-host diversity and the role of sexual recombination in parasite evolution.

Published
2016

6. Genomic epidemiology of artemisinin resistant malaria.

Author

Amato, A., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, A., Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., et al., Amato, A., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, A., Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., and et al.

Abstract

Contains fulltext : 172626.pdf (publisher's version ) (Open Access)

Published
2016

7. Genomic epidemiology of artemisinin resistant malaria

Author

Amato, R., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, Alyssa, Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., Echeverry, D.F., Egwang, T.G., Fairhurst, R.M., Faiz, A., Fanello, C.I., Hien, T.T., Hodgson, A., Imwong, M., Ishengoma, D., Lim, P., Lon, C., Marfurt, J., Marsh, K., Mayxay, M., Michon, P., Mobegi, V., Mokuolu, O.A., Montgomery, J., Mueller, I., Kyaw, M.P., Newton, P.N., Nosten, F., Noviyanti, R., Nzila, A., Ocholla, H., Oduro, A., Onyamboko, M., Ouedraogo, J.B., Phyo, A.P.P., Plowe, C., Price, R.N., Pukrittayakamee, S., Randrianarivelojosia, M., Ringwald, P., Ruiz, L., Saunders, D., Shayo, A., Siba, P., Takala-Harrison, S., Thanh, T.N.N., Thathy, V., Verra, F., Wendler, J., White, N.J., Ye, H., Cornelius, V.J., Giacomantonio, R., Muddyman, D., Henrichs, C., Malangone, C., Jyothi, D., Pearson, R.D., Rayner, J.C., McVean, G., Rockett, K.A., Miles, A., Vauterin, P., Jeffery, B., Manske, M., Stalker, J., Macinnis, B., Kwiatkowski, D.P., Amato, R., Miotto, O., Woodrow, C.J., Almagro-Garcia, J., Sinha, I., Campino, S., Mead, D., Drury, E., Kekre, M., Sanders, M., Amambua-Ngwa, A., Amaratunga, C., Amenga-Etego, L., Andrianaranjaka, V., Apinjoh, T., Ashley, E., Auburn, S., Awandare, G.A., Baraka, V., Barry, Alyssa, Boni, M.F., Borrmann, S., Bousema, T., Branch, O., Bull, P.C., Chotivanich, K., Conway, D.J., Craig, A., Day, N.P., Djimdé, A., Dolecek, C., Dondorp, A.M., Drakeley, C., Duffy, P., Echeverry, D.F., Egwang, T.G., Fairhurst, R.M., Faiz, A., Fanello, C.I., Hien, T.T., Hodgson, A., Imwong, M., Ishengoma, D., Lim, P., Lon, C., Marfurt, J., Marsh, K., Mayxay, M., Michon, P., Mobegi, V., Mokuolu, O.A., Montgomery, J., Mueller, I., Kyaw, M.P., Newton, P.N., Nosten, F., Noviyanti, R., Nzila, A., Ocholla, H., Oduro, A., Onyamboko, M., Ouedraogo, J.B., Phyo, A.P.P., Plowe, C., Price, R.N., Pukrittayakamee, S., Randrianarivelojosia, M., Ringwald, P., Ruiz, L., Saunders, D., Shayo, A., Siba, P., Takala-Harrison, S., Thanh, T.N.N., Thathy, V., Verra, F., Wendler, J., White, N.J., Ye, H., Cornelius, V.J., Giacomantonio, R., Muddyman, D., Henrichs, C., Malangone, C., Jyothi, D., Pearson, R.D., Rayner, J.C., McVean, G., Rockett, K.A., Miles, A., Vauterin, P., Jeffery, B., Manske, M., Stalker, J., Macinnis, B., and Kwiatkowski, D.P.

Published
2016

8. Genomic epidemiology of artemisinin resistant malaria

Author

Amato, R, Miotto, O, Woodrow, CJ, Almagro-Garcia, J, Sinha, I, Campino, S, Mead, D, Drury, E, Kekre, M, Sanders, M, Amambua-Ngwa, A, Amaratunga, C, Amenga-Etego, L, Andrianaranjaka, V, Apinjoh, T, Ashley, E, Auburn, S, Awandare, GA, Baraka, V, Barry, A, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Chotivanich, K, Conway, DJ, Craig, A, Day, NP, Djimde, A, Dolecek, C, Dondorp, AM, Drakeley, C, Duffy, P, Echeverry, DF, Egwang, TG, Fairhurst, RM, Faiz, MA, Fanello, CI, Tran, TH, Hodgson, A, Imwong, M, Ishengoma, D, Lim, P, Lon, C, Marfurt, J, Marsh, K, Mayxay, M, Michon, P, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Kyaw, MP, Newton, PN, Nosten, F, Noviyanti, R, Nzila, A, Ocholla, H, Oduro, A, Onyamboko, M, Ouedraogo, J-B, Phyo, APP, Plowe, C, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Ringwald, P, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Takala-Harrison, S, Thanh, T-NN, Thathy, V, Verra, F, Wendler, J, White, NJ, Ye, H, Cornelius, VJ, Giacomantonio, R, Muddyman, D, Henrichs, C, Malangone, C, Jyothi, D, Pearson, RD, Rayner, JC, McVean, G, Rockett, KA, Miles, A, Vauterin, P, Jeffery, B, Manske, M, Stalker, J, Maclnnis, B, Kwiatkowski, DP, Amato, R, Miotto, O, Woodrow, CJ, Almagro-Garcia, J, Sinha, I, Campino, S, Mead, D, Drury, E, Kekre, M, Sanders, M, Amambua-Ngwa, A, Amaratunga, C, Amenga-Etego, L, Andrianaranjaka, V, Apinjoh, T, Ashley, E, Auburn, S, Awandare, GA, Baraka, V, Barry, A, Boni, MF, Borrmann, S, Bousema, T, Branch, O, Bull, PC, Chotivanich, K, Conway, DJ, Craig, A, Day, NP, Djimde, A, Dolecek, C, Dondorp, AM, Drakeley, C, Duffy, P, Echeverry, DF, Egwang, TG, Fairhurst, RM, Faiz, MA, Fanello, CI, Tran, TH, Hodgson, A, Imwong, M, Ishengoma, D, Lim, P, Lon, C, Marfurt, J, Marsh, K, Mayxay, M, Michon, P, Mobegi, V, Mokuolu, OA, Montgomery, J, Mueller, I, Kyaw, MP, Newton, PN, Nosten, F, Noviyanti, R, Nzila, A, Ocholla, H, Oduro, A, Onyamboko, M, Ouedraogo, J-B, Phyo, APP, Plowe, C, Price, RN, Pukrittayakamee, S, Randrianarivelojosia, M, Ringwald, P, Ruiz, L, Saunders, D, Shayo, A, Siba, P, Takala-Harrison, S, Thanh, T-NN, Thathy, V, Verra, F, Wendler, J, White, NJ, Ye, H, Cornelius, VJ, Giacomantonio, R, Muddyman, D, Henrichs, C, Malangone, C, Jyothi, D, Pearson, RD, Rayner, JC, McVean, G, Rockett, KA, Miles, A, Vauterin, P, Jeffery, B, Manske, M, Stalker, J, Maclnnis, B, and Kwiatkowski, DP

Abstract

The current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.

Published
2016

9. Genomic analysis of local variation and recent evolution in Plasmodium vivax

Author

Pearson, RD, Amato, R, Auburn, S, Miotto, O, Almagro-Garcia, J, Amaratunga, C, Suon, S, Mao, S, Noviyanti, R, Trimarsanto, H, Marfurt, J, Anstey, NM, William, T, Boni, MF, Dolecek, C, Hien, TT, White, NJ, Michon, P, Siba, P, Tavul, L, Harrison, G, Barry, A, Mueller, I, Ferreira, MU, Karunaweera, N, Randrianarivelojosia, M, Gao, Q, Hubbart, C, Hart, L, Jeffery, B, Drury, E, Mead, D, Kekre, M, Campino, S, Manske, M, Cornelius, VJ, MacInnis, B, Rockett, KA, Miles, A, Rayner, JC, Fairhurst, RM, Nosten, F, Price, RN, Kwiatkowski, DP, Pearson, RD, Amato, R, Auburn, S, Miotto, O, Almagro-Garcia, J, Amaratunga, C, Suon, S, Mao, S, Noviyanti, R, Trimarsanto, H, Marfurt, J, Anstey, NM, William, T, Boni, MF, Dolecek, C, Hien, TT, White, NJ, Michon, P, Siba, P, Tavul, L, Harrison, G, Barry, A, Mueller, I, Ferreira, MU, Karunaweera, N, Randrianarivelojosia, M, Gao, Q, Hubbart, C, Hart, L, Jeffery, B, Drury, E, Mead, D, Kekre, M, Campino, S, Manske, M, Cornelius, VJ, MacInnis, B, Rockett, KA, Miles, A, Rayner, JC, Fairhurst, RM, Nosten, F, Price, RN, and Kwiatkowski, DP

Abstract

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax.

Published
2016

10. Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

Author

Manske, M, Miotto, O, Campino, S, Auburn, S, Almagro-Garcia, J, Maslen, G, O'Brien, J, Djimde, A, Doumbo, O, Zongo, I, Ouedraogo, J-B, Michon, P, Mueller, I, Siba, P, Nzila, A, Borrmann, S, Kiara, SM, Marsh, K, Jiang, H, Su, X-Z, Amaratunga, C, Fairhurst, R, Socheat, D, Nosten, F, Imwong, M, White, NJ, Sanders, M, Anastasi, E, Alcock, D, Drury, E, Oyola, S, Quail, MA, Turner, DJ, Ruano-Rubio, V, Jyothi, D, Amenga-Etego, L, Hubbart, C, Jeffreys, A, Rowlands, K, Sutherland, C, Roper, C, Mangano, V, Modiano, D, Tan, JC, Ferdig, MT, Amambua-Ngwa, A, Conway, DJ, Takala-Harrison, S, Plowe, CV, Rayner, JC, Rockett, KA, Clark, TG, Newbold, CI, Berriman, M, MacInnis, B, Kwiatkowski, DP, Manske, M, Miotto, O, Campino, S, Auburn, S, Almagro-Garcia, J, Maslen, G, O'Brien, J, Djimde, A, Doumbo, O, Zongo, I, Ouedraogo, J-B, Michon, P, Mueller, I, Siba, P, Nzila, A, Borrmann, S, Kiara, SM, Marsh, K, Jiang, H, Su, X-Z, Amaratunga, C, Fairhurst, R, Socheat, D, Nosten, F, Imwong, M, White, NJ, Sanders, M, Anastasi, E, Alcock, D, Drury, E, Oyola, S, Quail, MA, Turner, DJ, Ruano-Rubio, V, Jyothi, D, Amenga-Etego, L, Hubbart, C, Jeffreys, A, Rowlands, K, Sutherland, C, Roper, C, Mangano, V, Modiano, D, Tan, JC, Ferdig, MT, Amambua-Ngwa, A, Conway, DJ, Takala-Harrison, S, Plowe, CV, Rayner, JC, Rockett, KA, Clark, TG, Newbold, CI, Berriman, M, MacInnis, B, and Kwiatkowski, DP

Abstract

Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. Here we describe methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for the exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.

Published
2012

11. Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana.

Author

Girgis ST, Adika E, Nenyewodey FE, Senoo Jnr DK, Ngoi JM, Bandoh K, Lorenz O, van de Steeg G, Harrott AJR, Nsoh S, Judge K, Pearson RD, Almagro-Garcia J, Saiid S, Atampah S, Amoako EK, Morang'a CM, Asoala V, Adjei ES, Burden W, Roberts-Sengier W, Drury E, Pierce ML, Gonçalves S, Awandare GA, Kwiatkowski DP, Amenga-Etego LN, and Hamilton WL

Subjects
Child, Humans, Child, Preschool, Plasmodium falciparum genetics, Ghana epidemiology, Drug Resistance genetics, Nanopore Sequencing, Antimalarials pharmacology, Malaria epidemiology, Malaria, Falciparum epidemiology, Malaria, Falciparum prevention & control, Malaria, Falciparum drug therapy
Abstract

Malaria results in over 600,000 deaths annually, with the highest burden of deaths in young children living in sub-Saharan Africa. Molecular surveillance can provide important information for malaria control policies, including detection of antimalarial drug resistance. However, genome sequencing capacity in malaria-endemic countries is limited. We designed and implemented an end-to-end workflow to detect Plasmodium falciparum antimalarial resistance markers and diversity in the vaccine target circumsporozoite protein (csp) using nanopore sequencing in Ghana. We analysed 196 clinical samples and showed that our method is rapid, robust, accurate and straightforward to implement. Importantly, our method could be applied to dried blood spot samples, which are readily collected in endemic settings. We report that P. falciparum parasites in Ghana are mostly susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine resistance and no evidence of artemisinin resistance. Multiple single nucleotide polymorphisms were identified in csp, but their significance is uncertain. Our study demonstrates the feasibility of nanopore sequencing for malaria genomic surveillance in endemic countries., (© 2023. The Author(s).)

Published
2023
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12. Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples.

Author

Abdel Hamid MM, Abdelraheem MH, Acheampong DO, Ahouidi A, Ali M, Almagro-Garcia J, Amambua-Ngwa A, Amaratunga C, Amenga-Etego L, Andagalu B, Anderson T, Andrianaranjaka V, Aniebo I, Aninagyei E, Ansah F, Ansah PO, Apinjoh T, Arnaldo P, Ashley E, Auburn S, Awandare GA, Ba H, Baraka V, Barry A, Bejon P, Bertin GI, Boni MF, Borrmann S, Bousema T, Bouyou-Akotet M, Branch O, Bull PC, Cheah H, Chindavongsa K, Chookajorn T, Chotivanich K, Claessens A, Conway DJ, Corredor V, Courtier E, Craig A, D'Alessandro U, Dama S, Day N, Denis B, Dhorda M, Diakite M, Djimde A, Dolecek C, Dondorp A, Doumbia S, Drakeley C, Drury E, Duffy P, Echeverry DF, Egwang TG, Enosse SMM, Erko B, Fairhurst RM, Faiz A, Fanello CA, Fleharty M, Forbes M, Fukuda M, Gamboa D, Ghansah A, Golassa L, Goncalves S, Harrison GLA, Healy SA, Hendry JA, Hernandez-Koutoucheva A, Hien TT, Hill CA, Hombhanje F, Hott A, Htut Y, Hussein M, Imwong M, Ishengoma D, Jackson SA, Jacob CG, Jeans J, Johnson KJ, Kamaliddin C, Kamau E, Keatley J, Kochakarn T, Konate DS, Konaté A, Kone A, Kwiatkowski DP, Kyaw MP, Kyle D, Lawniczak M, Lee SK, Lemnge M, Lim P, Lon C, Loua KM, Mandara CI, Marfurt J, Marsh K, Maude RJ, Mayxay M, Maïga-Ascofaré O, Miotto O, Mita T, Mobegi V, Mohamed AO, Mokuolu OA, Montgomery J, Morang'a CM, Mueller I, Murie K, Newton PN, Ngo Duc T, Nguyen T, Nguyen TN, Nguyen Thi Kim T, Nguyen Van H, Noedl H, Nosten F, Noviyanti R, Ntui VN, Nzila A, Ochola-Oyier LI, Ocholla H, Oduro A, Omedo I, Onyamboko MA, Ouedraogo JB, Oyebola K, Oyibo WA, Pearson R, Peshu N, Phyo AP, Plowe CV, Price RN, Pukrittayakamee S, Quang HH, Randrianarivelojosia M, Rayner JC, Ringwald P, Rosanas-Urgell A, Rovira-Vallbona E, Ruano-Rubio V, Ruiz L, Saunders D, Shayo A, Siba P, Simpson VJ, Sissoko MS, Smith C, Su XZ, Sutherland C, Takala-Harrison S, Talman A, Tavul L, Thanh NV, Thathy V, Thu AM, Toure M, Tshefu A, Verra F, Vinetz J, Wellems TE, Wendler J, White NJ, Whitton G, Yavo W, and van der Pluijm RW

Abstract

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 MalariaGEN et al.)

Published
2023
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13. Genetic surveillance in the Greater Mekong subregion and South Asia to support malaria control and elimination.

Author

Jacob CG, Thuy-Nhien N, Mayxay M, Maude RJ, Quang HH, Hongvanthong B, Vanisaveth V, Ngo Duc T, Rekol H, van der Pluijm R, von Seidlein L, Fairhurst R, Nosten F, Hossain MA, Park N, Goodwin S, Ringwald P, Chindavongsa K, Newton P, Ashley E, Phalivong S, Maude R, Leang R, Huch C, Dong LT, Nguyen KT, Nhat TM, Hien TT, Nguyen H, Zdrojewski N, Canavati S, Sayeed AA, Uddin D, Buckee C, Fanello CI, Onyamboko M, Peto T, Tripura R, Amaratunga C, Myint Thu A, Delmas G, Landier J, Parker DM, Chau NH, Lek D, Suon S, Callery J, Jittamala P, Hanboonkunupakarn B, Pukrittayakamee S, Phyo AP, Smithuis F, Lin K, Thant M, Hlaing TM, Satpathi P, Satpathi S, Behera PK, Tripura A, Baidya S, Valecha N, Anvikar AR, Ul Islam A, Faiz A, Kunasol C, Drury E, Kekre M, Ali M, Love K, Rajatileka S, Jeffreys AE, Rowlands K, Hubbart CS, Dhorda M, Vongpromek R, Kotanan N, Wongnak P, Almagro Garcia J, Pearson RD, Ariani CV, Chookajorn T, Malangone C, Nguyen T, Stalker J, Jeffery B, Keatley J, Johnson KJ, Muddyman D, Chan XHS, Sillitoe J, Amato R, Simpson V, Gonçalves S, Rockett K, Day NP, Dondorp AM, Kwiatkowski DP, and Miotto O

Subjects
Animals, Asia, Southeastern, Bangladesh, Democratic Republic of the Congo, India, Plasmodium drug effects, Communicable Disease Control statistics & numerical data, Disease Eradication statistics & numerical data, Drug Resistance genetics, Malaria prevention & control, Plasmodium genetics
Abstract

Background: National Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures., Methods: Samples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs., Results: GenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs., Conclusions: GenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community., Funding: The GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases., Competing Interests: CJ, NT, MM, RM, HQ, BH, VV, TN, HR, Rv, Lv, RF, FN, MH, NP, SG, PR, KC, PN, EA, SP, RM, RL, CH, LD, KN, TN, TH, AS, DU, CB, CF, MO, TP, RT, CA, AM, GD, JL, DP, NC, DL, SS, JC, PJ, BH, SP, AP, FS, KL, MT, TH, PS, SS, PB, AT, SB, NV, AA, AU, AF, CK, ED, MK, MA, KL, SR, AJ, KR, CH, MD, RV, NK, PW, JA, RP, CA, TC, CM, TN, JS, BJ, JK, KJ, DM, XC, JS, RA, VS, SG, KR, ND, AD, DK, OM No competing interests declared, HN, NZ, SC is an employee of Vysnova Partners Inc

Published
2021
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14. The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria.

Author

Zhu SJ, Hendry JA, Almagro-Garcia J, Pearson RD, Amato R, Miles A, Weiss DJ, Lucas TC, Nguyen M, Gething PW, Kwiatkowski D, and McVean G

Subjects
Africa epidemiology, Asia epidemiology, Humans, Plasmodium falciparum isolation & purification, Prevalence, Whole Genome Sequencing, Coinfection epidemiology, Coinfection parasitology, Genotype, Malaria, Falciparum epidemiology, Malaria, Falciparum parasitology, Plasmodium falciparum classification, Plasmodium falciparum genetics
Abstract

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Furthermore, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD., Competing Interests: SZ, JH, JA, RP, RA, AM, DW, TL, MN, PG, DK, GM No competing interests declared, (© 2019, Zhu et al.)

Published
2019
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15. RTS,S/AS01 malaria vaccine mismatch observed among Plasmodium falciparum isolates from southern and central Africa and globally.

Author

Pringle JC, Carpi G, Almagro-Garcia J, Zhu SJ, Kobayashi T, Mulenga M, Bobanga T, Chaponda M, Moss WJ, and Norris DE

Subjects
Alleles, Amino Acid Substitution, Antigenic Variation genetics, Antigens, Protozoan genetics, Antigens, Protozoan immunology, Democratic Republic of the Congo epidemiology, Epitopes genetics, Epitopes immunology, Gene Frequency, Genetic Variation, Haplotypes, Humans, Malaria, Falciparum parasitology, Plasmodium falciparum genetics, Protozoan Proteins genetics, Protozoan Proteins immunology, Zambia epidemiology, Antigenic Variation immunology, Malaria Vaccines immunology, Malaria, Falciparum epidemiology, Malaria, Falciparum prevention & control, Plasmodium falciparum immunology
Abstract

The RTS,S/AS01 malaria vaccine encompasses the central repeats and C-terminal of Plasmodium falciparum circumsporozoite protein (PfCSP). Although no Phase II clinical trial studies observed evidence of strain-specific immunity, recent studies show a decrease in vaccine efficacy against non-vaccine strain parasites. In light of goals to reduce malaria morbidity, anticipating the effectiveness of RTS,S/AS01 is critical to planning widespread vaccine introduction. We deep sequenced C-terminal Pfcsp from 77 individuals living along the international border in Luapula Province, Zambia and Haut-Katanga Province, the Democratic Republic of the Congo (DRC) and compared translated amino acid haplotypes to the 3D7 vaccine strain. Only 5.2% of the 193 PfCSP sequences from the Zambia-DRC border region matched 3D7 at all 84 amino acids. To further contextualize the genetic diversity sampled in this study with global PfCSP diversity, we analyzed an additional 3,809 Pfcsp sequences from the Pf3k database and constructed a haplotype network representing 15 countries from Africa and Asia. The diversity observed in our samples was similar to the diversity observed in the global haplotype network. These observations underscore the need for additional research assessing genetic diversity in P. falciparum and the impact of PfCSP diversity on RTS,S/AS01 efficacy.

Published
2018
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16. Origins of the current outbreak of multidrug-resistant malaria in southeast Asia: a retrospective genetic study.

Author

Amato R, Pearson RD, Almagro-Garcia J, Amaratunga C, Lim P, Suon S, Sreng S, Drury E, Stalker J, Miotto O, Fairhurst RM, and Kwiatkowski DP

Subjects
Asia, Southeastern epidemiology, Disease Outbreaks statistics & numerical data, Gene Expression Regulation, Genome, Protozoan, Genotype, Humans, Malaria, Falciparum drug therapy, Antimalarials pharmacology, Drug Resistance, Malaria, Falciparum epidemiology, Malaria, Falciparum parasitology, Plasmodium falciparum drug effects, Plasmodium falciparum genetics
Abstract

Background: Antimalarial resistance is rapidly spreading across parts of southeast Asia where dihydroartemisinin-piperaquine is used as first-line treatment for Plasmodium falciparum malaria. The first published reports about resistance to antimalarial drugs came from western Cambodia in 2013. Here, we analyse genetic changes in the P falciparum population of western Cambodia in the 6 years before those reports., Methods: We analysed genome sequence data on 1492 P falciparum samples from 11 locations across southeast Asia, including 464 samples collected in western Cambodia between 2007 and 2013. Different epidemiological origins of resistance were identified by haplotypic analysis of the kelch13 artemisinin resistance locus and the plasmepsin 2-3 piperaquine resistance locus., Findings: We identified more than 30 independent origins of artemisinin resistance, of which the KEL1 lineage accounted for 140 (91%) of 154 parasites resistant to dihydroartemisinin-piperaquine. In 2008, KEL1 combined with PLA1, the major lineage associated with piperaquine resistance. By 2013, the KEL1/PLA1 co-lineage had reached a frequency of 63% (24/38) in western Cambodia and had spread to northern Cambodia., Interpretation: The KEL1/PLA1 co-lineage emerged in the same year that dihydroartemisinin-piperaquine became the first-line antimalarial drug in western Cambodia and spread rapidly thereafter, displacing other artemisinin-resistant parasite lineages. These findings have important implications for management of the global health risk associated with the current outbreak of multidrug-resistant malaria in southeast Asia., Funding: Wellcome Trust, Bill & Melinda Gates Foundation, Medical Research Council, UK Department for International Development, and the Intramural Research Program of the National Institute of Allergy and Infectious Diseases., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Published
2018
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17. Deconvolution of multiple infections in Plasmodium falciparum from high throughput sequencing data.

Author

Zhu SJ, Almagro-Garcia J, and McVean G

Subjects
Coinfection, Haplotypes, Humans, Plasmodium falciparum pathogenicity, High-Throughput Nucleotide Sequencing methods, Malaria, Falciparum genetics, Plasmodium falciparum genetics, Sequence Analysis, DNA methods, Software
Abstract

Motivation: The presence of multiple infecting strains of the malarial parasite Plasmodium falciparum affects key phenotypic traits, including drug resistance and risk of severe disease. Advances in protocols and sequencing technology have made it possible to obtain high-coverage genome-wide sequencing data from blood samples and blood spots taken in the field. However, analyzing and interpreting such data is challenging because of the high rate of multiple infections present., Results: We have developed a statistical method and implementation for deconvolving multiple genome sequences present in an individual with mixed infections. The software package DEploid uses haplotype structure within a reference panel of clonal isolates as a prior for haplotypes present in a given sample. It estimates the number of strains, their relative proportions and the haplotypes presented in a sample, allowing researchers to study multiple infection in malaria with an unprecedented level of detail., Availability and Implementation: The open source implementation DEploid is freely available at https://github.com/mcveanlab/DEploid under the conditions of the GPLv3 license. An R version is available at https://github.com/mcveanlab/DEploid-r., Contact: joe.zhu@bdi.ox.ac.uk or gil.mcvean@bdi.ox.ac.uk., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2017. Published by Oxford University Press.)

Published
2018
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18. treespace: Statistical exploration of landscapes of phylogenetic trees.

Author

Jombart T, Kendall M, Almagro-Garcia J, and Colijn C

Subjects
Data Interpretation, Statistical, Evolution, Molecular, Software, Computational Biology methods, Phylogeny, Trees classification, Trees genetics
Abstract

The increasing availability of large genomic data sets as well as the advent of Bayesian phylogenetics facilitates the investigation of phylogenetic incongruence, which can result in the impossibility of representing phylogenetic relationships using a single tree. While sometimes considered as a nuisance, phylogenetic incongruence can also reflect meaningful biological processes as well as relevant statistical uncertainty, both of which can yield valuable insights in evolutionary studies. We introduce a new tool for investigating phylogenetic incongruence through the exploration of phylogenetic tree landscapes. Our approach, implemented in the R package treespace, combines tree metrics and multivariate analysis to provide low-dimensional representations of the topological variability in a set of trees, which can be used for identifying clusters of similar trees and group-specific consensus phylogenies. treespace also provides a user-friendly web interface for interactive data analysis and is integrated alongside existing standards for phylogenetics. It fills a gap in the current phylogenetics toolbox in R and will facilitate the investigation of phylogenetic results., (© 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.)

Published
2017
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19. Genetic markers associated with dihydroartemisinin-piperaquine failure in Plasmodium falciparum malaria in Cambodia: a genotype-phenotype association study.

Author

Amato R, Lim P, Miotto O, Amaratunga C, Dek D, Pearson RD, Almagro-Garcia J, Neal AT, Sreng S, Suon S, Drury E, Jyothi D, Stalker J, Kwiatkowski DP, and Fairhurst RM

Subjects
Antimalarials pharmacology, Antimalarials therapeutic use, Cambodia epidemiology, Drug Therapy, Combination, Genome-Wide Association Study, Humans, Inhibitory Concentration 50, Malaria, Falciparum drug therapy, Plasmodium falciparum drug effects, Plasmodium falciparum isolation & purification, Polymorphism, Single Nucleotide, Treatment Failure, Artemisinins therapeutic use, Drug Resistance, Genetic Association Studies, Genetic Markers, Malaria, Falciparum epidemiology, Plasmodium falciparum genetics, Quinolines therapeutic use
Abstract

Background: As the prevalence of artemisinin-resistant Plasmodium falciparum malaria increases in the Greater Mekong subregion, emerging resistance to partner drugs in artemisinin combination therapies seriously threatens global efforts to treat and eliminate this disease. Molecular markers that predict failure of artemisinin combination therapy are urgently needed to monitor the spread of partner drug resistance, and to recommend alternative treatments in southeast Asia and beyond., Methods: We did a genome-wide association study of 297 P falciparum isolates from Cambodia to investigate the relationship of 11 630 exonic single-nucleotide polymorphisms (SNPs) and 43 copy number variations (CNVs) with in-vitro piperaquine 50% inhibitory concentrations (IC 50 s), and tested whether these genetic variants are markers of treatment failure with dihydroartemisinin-piperaquine. We then did a survival analysis of 133 patients to determine whether candidate molecular markers predicted parasite recrudescence following dihydroartemisinin-piperaquine treatment., Findings: Piperaquine IC 50 s increased significantly from 2011 to 2013 in three Cambodian provinces (2011 vs 2013 median IC 50 s: 20·0 nmol/L [IQR 13·7-29·0] vs 39·2 nmol/L [32·8-48·1] for Ratanakiri, 19·3 nmol/L [15·1-26·2] vs 66·2 nmol/L [49·9-83·0] for Preah Vihear, and 19·6 nmol/L [11·9-33·9] vs 81·1 nmol/L [61·3-113·1] for Pursat; all p≤10 -3 ; Kruskal-Wallis test). Genome-wide analysis of SNPs identified a chromosome 13 region that associates with raised piperaquine IC 50 s. A non-synonymous SNP (encoding a Glu415Gly substitution) in this region, within a gene encoding an exonuclease, associates with parasite recrudescence following dihydroartemisinin-piperaquine treatment. Genome-wide analysis of CNVs revealed that a single copy of the mdr1 gene on chromosome 5 and a novel amplification of the plasmepsin 2 and plasmepsin 3 genes on chromosome 14 also associate with raised piperaquine IC 50 s. After adjusting for covariates, both exo-E415G and plasmepsin 2-3 markers significantly associate (p=3·0 × 10 -8 and p=1·7 × 10 -7 , respectively) with decreased treatment efficacy (survival rates 0·38 [95% CI 0·25-0·51] and 0·41 [0·28-0·53], respectively)., Interpretation: The exo-E415G SNP and plasmepsin 2-3 amplification are markers of piperaquine resistance and dihydroartemisinin-piperaquine failures in Cambodia, and can help monitor the spread of these phenotypes into other countries of the Greater Mekong subregion, and elucidate the mechanism of piperaquine resistance. Since plasmepsins are involved in the parasite's haemoglobin-to-haemozoin conversion pathway, targeted by related antimalarials, plasmepsin 2-3 amplification probably mediates piperaquine resistance., Funding: Intramural Research Program of the US National Institute of Allergy and Infectious Diseases, National Institutes of Health, Wellcome Trust, Bill & Melinda Gates Foundation, Medical Research Council, and UK Department for International Development., (Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.)

Published
2017
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20. Genomic analysis of local variation and recent evolution in Plasmodium vivax.

Author

Pearson RD, Amato R, Auburn S, Miotto O, Almagro-Garcia J, Amaratunga C, Suon S, Mao S, Noviyanti R, Trimarsanto H, Marfurt J, Anstey NM, William T, Boni MF, Dolecek C, Hien TT, White NJ, Michon P, Siba P, Tavul L, Harrison G, Barry A, Mueller I, Ferreira MU, Karunaweera N, Randrianarivelojosia M, Gao Q, Hubbart C, Hart L, Jeffery B, Drury E, Mead D, Kekre M, Campino S, Manske M, Cornelius VJ, MacInnis B, Rockett KA, Miles A, Rayner JC, Fairhurst RM, Nosten F, Price RN, and Kwiatkowski DP

Subjects
Humans, Malaria, Vivax parasitology, Malaria, Vivax transmission, Plasmodium vivax pathogenicity, Biological Evolution, Genetic Markers genetics, Genetic Variation genetics, Genomics methods, Malaria, Vivax genetics, Plasmodium vivax genetics
Abstract

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax., Competing Interests: The authors declare no competing financial interests.

Published
2016
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21. Genetic architecture of artemisinin-resistant Plasmodium falciparum.

Author

Miotto O, Amato R, Ashley EA, MacInnis B, Almagro-Garcia J, Amaratunga C, Lim P, Mead D, Oyola SO, Dhorda M, Imwong M, Woodrow C, Manske M, Stalker J, Drury E, Campino S, Amenga-Etego L, Thanh TN, Tran HT, Ringwald P, Bethell D, Nosten F, Phyo AP, Pukrittayakamee S, Chotivanich K, Chuor CM, Nguon C, Suon S, Sreng S, Newton PN, Mayxay M, Khanthavong M, Hongvanthong B, Htut Y, Han KT, Kyaw MP, Faiz MA, Fanello CI, Onyamboko M, Mokuolu OA, Jacob CG, Takala-Harrison S, Plowe CV, Day NP, Dondorp AM, Spencer CC, McVean G, Fairhurst RM, White NJ, and Kwiatkowski DP

Subjects
Drug Resistance genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Humans, Malaria, Falciparum drug therapy, Malaria, Falciparum parasitology, Mutation, Polymorphism, Single Nucleotide, Antimalarials pharmacology, Artemisinins pharmacology, Genome, Protozoan, Plasmodium falciparum drug effects, Plasmodium falciparum genetics
Abstract

We report a large multicenter genome-wide association study of Plasmodium falciparum resistance to artemisinin, the frontline antimalarial drug. Across 15 locations in Southeast Asia, we identified at least 20 mutations in kelch13 (PF3D7_1343700) affecting the encoded propeller and BTB/POZ domains, which were associated with a slow parasite clearance rate after treatment with artemisinin derivatives. Nonsynonymous polymorphisms in fd (ferredoxin), arps10 (apicoplast ribosomal protein S10), mdr2 (multidrug resistance protein 2) and crt (chloroquine resistance transporter) also showed strong associations with artemisinin resistance. Analysis of the fine structure of the parasite population showed that the fd, arps10, mdr2 and crt polymorphisms are markers of a genetic background on which kelch13 mutations are particularly likely to arise and that they correlate with the contemporary geographical boundaries and population frequencies of artemisinin resistance. These findings indicate that the risk of new resistance-causing mutations emerging is determined by specific predisposing genetic factors in the underlying parasite population.

Published
2015
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22. Multiple populations of artemisinin-resistant Plasmodium falciparum in Cambodia.

Author

Miotto O, Almagro-Garcia J, Manske M, Macinnis B, Campino S, Rockett KA, Amaratunga C, Lim P, Suon S, Sreng S, Anderson JM, Duong S, Nguon C, Chuor CM, Saunders D, Se Y, Lon C, Fukuda MM, Amenga-Etego L, Hodgson AV, Asoala V, Imwong M, Takala-Harrison S, Nosten F, Su XZ, Ringwald P, Ariey F, Dolecek C, Hien TT, Boni MF, Thai CQ, Amambua-Ngwa A, Conway DJ, Djimdé AA, Doumbo OK, Zongo I, Ouedraogo JB, Alcock D, Drury E, Auburn S, Koch O, Sanders M, Hubbart C, Maslen G, Ruano-Rubio V, Jyothi D, Miles A, O'Brien J, Gamble C, Oyola SO, Rayner JC, Newbold CI, Berriman M, Spencer CC, McVean G, Day NP, White NJ, Bethell D, Dondorp AM, Plowe CV, Fairhurst RM, and Kwiatkowski DP

Subjects
Cambodia epidemiology, Chromosome Painting, Cluster Analysis, Drug Resistance, Founder Effect, Genetic Association Studies, Homozygote, Humans, Malaria, Falciparum drug therapy, Malaria, Falciparum epidemiology, Models, Genetic, Plasmodium falciparum drug effects, Polymorphism, Single Nucleotide, Principal Component Analysis, Antimalarials pharmacology, Artemisinins pharmacology, Genes, Protozoan, Malaria, Falciparum parasitology, Plasmodium falciparum genetics
Abstract

We describe an analysis of genome variation in 825 P. falciparum samples from Asia and Africa that identifies an unusual pattern of parasite population structure at the epicenter of artemisinin resistance in western Cambodia. Within this relatively small geographic area, we have discovered several distinct but apparently sympatric parasite subpopulations with extremely high levels of genetic differentiation. Of particular interest are three subpopulations, all associated with clinical resistance to artemisinin, which have skewed allele frequency spectra and high levels of haplotype homozygosity, indicative of founder effects and recent population expansion. We provide a catalog of SNPs that show high levels of differentiation in the artemisinin-resistant subpopulations, including codon variants in transporter proteins and DNA mismatch repair proteins. These data provide a population-level genetic framework for investigating the biological origins of artemisinin resistance and for defining molecular markers to assist in its elimination.

Published
2013
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23. Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing.

Author

Manske M, Miotto O, Campino S, Auburn S, Almagro-Garcia J, Maslen G, O'Brien J, Djimde A, Doumbo O, Zongo I, Ouedraogo JB, Michon P, Mueller I, Siba P, Nzila A, Borrmann S, Kiara SM, Marsh K, Jiang H, Su XZ, Amaratunga C, Fairhurst R, Socheat D, Nosten F, Imwong M, White NJ, Sanders M, Anastasi E, Alcock D, Drury E, Oyola S, Quail MA, Turner DJ, Ruano-Rubio V, Jyothi D, Amenga-Etego L, Hubbart C, Jeffreys A, Rowlands K, Sutherland C, Roper C, Mangano V, Modiano D, Tan JC, Ferdig MT, Amambua-Ngwa A, Conway DJ, Takala-Harrison S, Plowe CV, Rayner JC, Rockett KA, Clark TG, Newbold CI, Berriman M, MacInnis B, and Kwiatkowski DP

Subjects
Alleles, Genome, Protozoan, Genotype, Humans, Phylogeny, Plasmodium falciparum classification, Polymorphism, Single Nucleotide, Principal Component Analysis, Biodiversity, High-Throughput Nucleotide Sequencing, Malaria, Falciparum parasitology, Plasmodium falciparum genetics
Abstract

Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. Here we describe methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for the exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.

Published
2012
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24. SnoopCGH: software for visualizing comparative genomic hybridization data.

Author

Almagro-Garcia J, Manske M, Carret C, Campino S, Auburn S, Macinnis BL, Maslen G, Pain A, Newbold CI, Kwiatkowski DP, and Clark TG

Subjects
Comparative Genomic Hybridization instrumentation, Computer Graphics, Gene Expression Profiling methods, Genome, Bacterial, Oligonucleotide Array Sequence Analysis methods, Plasmodium falciparum genetics, Comparative Genomic Hybridization methods, Computational Biology methods, Genome, Software
Abstract

Unlabelled: Array-based comparative genomic hybridization (CGH) technology is used to discover and validate genomic structural variation, including copy number variants, insertions, deletions and other structural variants (SVs). The visualization and summarization of the array CGH data outputs, potentially across many samples, is an important process in the identification and analysis of SVs. We have developed a software tool for SV analysis using data from array CGH technologies, which is also amenable to short-read sequence data., Availability and Implementation: SnoopCGH is written in java and is available from http://snoopcgh.sourceforge.net/

Published
2009
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