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1. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data [version 2; peer review: 2 approved]

Author

Ndila, CM, Nyirongo, V, Macharia, AW, Jeffreys, AE, Rowlands, K, Hubbart, C, Busby, GBJ, Band, G, Harding, RM, Rockett, KA, Williams, TN, and MalariaGEN Consortium

Subjects
hemic and lymphatic diseases, Science, Medicine
Abstract

Background: The -α 3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study, we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha ( HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.

Published
2021

2. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data [version 1; peer review: 1 approved, 1 approved with reservations]

Author

Ndila, CM, Nyirongo, V, Macharia, AW, Jeffreys, AE, Rowlands, K, Hubbart, C, Busby, GBJ, Band, G, Harding, RM, Rockett, KA, and Williams, TN

Abstract

Background: The -α3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha (HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.

Published
2020

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. New insights into malaria susceptibility from the genomes of 17,000 individuals from Africa, Asia, and Oceania

Author

Kate Rowlands, Timothy M. E. Davis, Salimata Konate, Umberto D'Alessandro, Angeliki Kerasidou, Sodiomon B. Sirima, David J. Conway, Fatoumatta Sisay-Joof, S Ademola, Mahamadou A. Thera, Momodou W. Jallow, Edith C. Bougouma, Alexander J. Mentzer, Alphaxard Manjurano, Chris Drakeley, Carolyne M. Ndila, Giorgio Sirugo, Eleanor Drury, Nguyen Hoan Phu, Moses Laman, Anthony Enimil, Pascal Michon, N T Ngoc Quyen, Terrie E. Taylor, Jennifer Evans, Ogobara K. Doumbo, Anita Ghansah, Malcolm E. Molyneux, Alexander T. Dilthey, Sibiry Sissoko, Olukemi K. Amodu, Kalifa Bojang, Yik Ying Teo, Ousmane Touré, Eleanor M. Riley, Dominic P. Kwiatkowski, Angela Allen, Laurens Manning, D Ansong, Peter Siba, Stephen Allen, Thomas N. Williams, Christina Hubbart, Tobias O. Apinjoh, Cao Quang Thai, Hugh Reyburn, Q S Le, Melanie Bahlo, Geraldine M. Clarke, Spencer Cca., Ivo Mueller, Anna E. Jeffreys, Gil McVean, Valentina D. Mangano, Jj J. Farrar, Victoria Cornelius, Busby Gbj., Kevin Marsh, Jim Stalker, David Modiano, Tran Tinh Hien, Michael T. Wilson, Tsiri Agbenyega, A Hodgson, Sarah J. Dunstan, Harin Karunajeewa, L. Amenga-Etego, Ellen M. Leffler, Katja Kivinen, Eric A. Achidi, Kirk A. Rockett, Kwadwo A. Koram, and J Shelton

Subjects
Genetics, Host resistance, biology, Plasmodium falciparum, Disease, Heritability, Hla association, biology.organism_classification, medicine.disease, Genome, Cerebral Malaria, parasitic diseases, medicine, Malaria
Abstract

We conducted a genome-wide association study of host resistance to severePlasmodium falciparummalaria in over 17,000 individuals from 11 malaria-endemic countries, undertaking a wide ranging analysis which identifies five replicable associations with genome-wide levels of evidence. Our findings include a newly implicated variant on chromosome 6 associated with risk of cerebral malaria, and the discovery of an erythroid-specific transcription start site underlying the association inATP2B4. Previously reported HLA associations cannot be replicated in this dataset. We estimate substantial heritability of severe malaria (h2~ 23%), of which around 10% is explained by the currently identified associations. Our dataset will provide a major building block for future research on the genetic determinants of disease in these diverse human populations.

Published
2019
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5. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania

Author

Band, G, Le, QS, Clarke, GM, Kivinen, K, Hubbart, C, Jeffreys, AE, Rowlands, K, Leffler, EM, Jallow, M, Conway, DJ, Sisay-Joof, F, Sirugo, G, d'Alessandro, U, Toure, OB, Thera, MA, Konate, S, Sissoko, S, Mangano, VD, Bougouma, EC, Sirima, SB, Amenga-Etego, LN, Ghansah, AK, Hodgson, AVO, Wilson, MD, Enimil, A, Ansong, D, Evans, J, Ademola, SA, Apinjoh, TO, Ndila, CM, Manjurano, A, Drakeley, C, Reyburn, H, Nguyen, HP, Nguyen, TNQ, Cao, QT, Tran, TH, Teo, YY, Manning, L, Laman, M, Michon, P, Karunajeewa, H, Siba, P, Allen, S, Allen, A, Bahlo, M, Davis, TME, Simpson, V, Shelton, J, Spencer, CCA, Busby, GBJ, Kerasidou, A, Drury, E, Stalker, J, Dilthey, A, Mentzer, AJ, McVean, G, Bojang, KA, Doumbo, O, Modiano, D, Koram, KA, Agbenyega, T, Amodu, OK, Achidi, E, Williams, TN, Marsh, K, Riley, EM, Molyneux, M, Taylor, T, Dunstan, SJ, Farrar, J, Mueller, I, Rockett, KA, Kwiatkowski, DP, Band, G, Le, QS, Clarke, GM, Kivinen, K, Hubbart, C, Jeffreys, AE, Rowlands, K, Leffler, EM, Jallow, M, Conway, DJ, Sisay-Joof, F, Sirugo, G, d'Alessandro, U, Toure, OB, Thera, MA, Konate, S, Sissoko, S, Mangano, VD, Bougouma, EC, Sirima, SB, Amenga-Etego, LN, Ghansah, AK, Hodgson, AVO, Wilson, MD, Enimil, A, Ansong, D, Evans, J, Ademola, SA, Apinjoh, TO, Ndila, CM, Manjurano, A, Drakeley, C, Reyburn, H, Nguyen, HP, Nguyen, TNQ, Cao, QT, Tran, TH, Teo, YY, Manning, L, Laman, M, Michon, P, Karunajeewa, H, Siba, P, Allen, S, Allen, A, Bahlo, M, Davis, TME, Simpson, V, Shelton, J, Spencer, CCA, Busby, GBJ, Kerasidou, A, Drury, E, Stalker, J, Dilthey, A, Mentzer, AJ, McVean, G, Bojang, KA, Doumbo, O, Modiano, D, Koram, KA, Agbenyega, T, Amodu, OK, Achidi, E, Williams, TN, Marsh, K, Riley, EM, Molyneux, M, Taylor, T, Dunstan, SJ, Farrar, J, Mueller, I, Rockett, KA, and Kwiatkowski, DP

Abstract

The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus. Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on thegenetic determinants of malaria resistance in diverse populations.

Published
2019

6. The peopling of Europe: a genetic perspective

Author

Busby, GBJ and Capelli, C

Subjects
Evolution (zoology), Genetics (life sciences)
Abstract

Following their dispersal out of Africa, humans colonised all continents of the world save one, Antarctica. Whilst Europe was initially peopled soon after this exodus, paleoclimatic, archaeological, and historical evidence suggest that successive waves and migrations of people have contributed to the population resident in Europe today. I therefore examined the impact of past events on the European population through the analysis of DNA sampled both from contemporary Europeans, and from worldwide populations pertinent to its history. I genotyped and analysed data from the Y chromosomes of over 2,000 haplogroup R-M269 European men from over 30 different populations and, in combination with comparable datasets gathered from the literature, show that there it is not possible to assign a date to the origin of this lineage in Europe, and thus that any conclusion as to the ancient or recent spread of this lineage in Europe is unfounded. I also show that commonly used Y chromosome lineage dating techniques based on STR variation are biased by the markers used and conclusions based on such dates should be viewed with a large amount of caution. I next use genome-wide SNP data from 1,550 individuals from 95 worldwide populations to explore the population structure of Europe and present an analysis of the detailed structure of Europe in a novel analytical framework using ChromoPainter and fineSTRUCTURE. Admixture analysis based this data reveals distinct genomic inputs to peripheral European populations, from North Africa, Sub-Saharan Africa, the Middle East, and East Asia, and provides dates for this admixture within the last 1,000 years that correspond to the emergence and decline of empires and kingdoms in these regions of Europe. This novel analysis highlights the importance of recent historical events on European population structure, but also suggests a degree of ancient structure across European populations. Taken together, these analyses demonstrate the substantial effects of both ancient and recent migrations and mixture on the contemporary genetic structure of Europe.

Published
2016

7. Admixture into and within sub-Saharan Africa

Author

Angeliki Kerasidou, J O'Brien, Aaron Vanderwal, Christina Hubbart, Alistair Miles, Catherine L. Moyes, A Nyika, Abier Elzein, J Shelton, Spencer Cca., Anthony Enimil, A Diss, C Hughes, Lucas Amenga-Etego, E Somaskantharajah, Ogobara K. Doumbo, Jacob Almagro Garcia, Valentina D. Mangano, E Drury, Edith Bougama, Angie Green, Busby Gbj., Geraldine M. Clarke, Dominic P. Kwiatkowski, Jiannis Ragoussis, Alphaxard Manjurano, Bronwyn MacInnis, Tobias O. Apinjoh, D Mead, Gareth Maslen, George B.J. Busby, Kirk A. Rockett, Dushyanth Jyothi, C Potter, C Malangone, Muminatou Jallow, I Ragoussis, Ellen M. Leffler, J Rogers, J Stalker, Quang Si Le, J Rodford, D Barnwell, Alieu Mendy, J deVries, Anna E. Jeffreys, Carolyne M. Ndila, E Hilton, Vysaul Nyirongo, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], The Wellcome Trust Sanger Institute [Cambridge], Medical Research Council Unit The Gambia (MRC), Centre National de Recherche et de Formation sur le Paludisme [Ouagadougou, Burkina Faso] (CNRFP), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Navrongo Health Research Centre [Navrongo, Ghana] (NHRC), Komfo Anokye Teaching Hospital, University of Buéa, KEMRI-Wellcome Trust Research Programme (KWTRP), London School of Hygiene and Tropical Medicine (LSHTM), University of Malawi, University of Bamako [Mali], Institut Pasteur de Dakar, Réseau International des Instituts Pasteur (RIIP), Wellcome Trust, Medical Research Council, Foundation for the National Institutes of Health, Malaria Genomics Epidemiology Network : Vanderwal A, Elzein A, Nyika A, Mendy A, Miles A, Diss A, Kerasidou A, Green A, Jeffreys AE, MacInnis B, Hughes C, Moyes C, Spencer CC, Hubbart C, Malangone C, Potter C, Mead D, Barnwell D, Kwiatkowski DP, Jyothi D, Drury E, Somaskantharajah E, Hilton E, Leffler E, Maslen G, Band G, Busby G, Clarke GM, Ragoussis I, Garcia JA, Rogers J, deVries J, Shelton J, Ragoussis J, Stalker J, Rodford J, O'Brien J, Evans J, Rowlands K, Cook K, Fitzpatrick K, Kivinen K, Small K, Johnson KJ, Rockett KA, Hart L, Manske M, McCreight M, Stevens M, Pirinen M, Hennsman M, Parker M, SanJoaquin M, Seplúveda N, Cook O, Miotto O, Deloukas P, Craik R, Wrigley R, Watson R, Pearson R, Hutton R, Oyola S, Auburn S, Shah S, Le SQ, Molloy S, Bull S, Campino S, Clark TG, Ruano-Rubio V, Cornelius V, Teo YY, Corran P, Silva ND, Risley P, Doyle A, Evans J, Horstmann R, Plowe C, Duffy P, Carucci D, Gottleib M, Tall A, Ly AB, Dolo A, Sakuntabhai A, Puijalon O, Bah A, Camara A, Sadiq A, Khan AA, Jobarteh A, Mendy A, Ebonyi A, Danso B, Taal B, Casals-Pascual C, Conway DJ, Onykwelu E, Sisay-Joof F, Sirugo G, Kanyi H, Njie H, Obu H, Saine H, Sambou I, Abubakar I, Njie J, Fullah J, Jaiteh J, Bojang KA, Jammeh K, Sabally-Ceesay K, Manneh L, Camara L, Yamoah L, Njie M, Njie M, Pinder M, Jallow M, Aiyegbo M, Jasseh M, Keita ML, Saidy-Khan M, Jallow M, Ceesay N, Rasheed O, Ceesay PL, Esangbedo P, Cole-Ceesay R, Olaosebikan R, Correa S, Njie S, Usen S, Dibba Y, Barry A, Djimdé A, Sall AH, Abathina A, Niangaly A, Dembele A, Poudiougou B, Diarra E, Bamba K, Thera MA, Doumbo O, Toure O, Konate S, Sissoko S, Diakite M, Konate AT, Modiano D, Bougouma EC, Bancone G, Ouedraogo IN, Simpore J, Sirima SB, Mangano VD, Troye-Blomberg M, Oduro AR, Hodgson AV, Ghansah A, Nkrumah F, Atuguba F, Koram KA, Amenga-Etego LN, Wilson MD, Ansah NA, Mensah N, Ansah PA, Anyorigiya T, Asoala V, Rogers WO, Akoto AO, Ofori AO, Enimil A, Ansong D, Sambian D, Asafo-Agyei E, Sylverken J, Antwi S, Agbenyega T, Orimadegun AE, Amodu FA, Oni O, Omotade OO, Amodu O, Olaniyan S, Ndi A, Yafi C, Achidi EA, Mbunwe E, Anchang-Kimbi J, Mugri R, Besingi R, Apinjoh TO, Titanji V, Elhassan A, Hussein A, Mohamed H, Elhassan I, Ibrahim M, Kokwaro G, Oluoch T, Macharia A, Ndila CM, Newton C, Opi DH, Kamuya D, Bauni E, Marsh K, Peshu N, Molyneux S, Uyoga S, Williams TN, Marsh V, Manjurano A, Nadjm B, Maxwell C, Drakeley C, Riley E, Mtei F, Mtove G, Wangai H, Reyburn H, Joseph S, Ishengoma D, Lemnge M, Mutabingwa T, Makani J, Cox S, Phiri A, Munthali A, Kachala D, Njiragoma L, Molyneux ME, Moore M, Ntunthama N, Pensulo P, Taylor T, Nyirongo V, Carter R, Fernando D, Karunaweera N, Dewasurendra R, Suriyaphol P, Singhasivanon P, Simmons CP, Thai CQ, Sinh DX, Farrar J, Chuong LV, Phu NH, Hieu NT, Hoang Mai NT, Ngoc Quyen NT, Day N, Dunstan SJ, O'Riordan SE, Hong Chau TT, Hien TT, Allen A, Lin E, Karunajeewa H, Mueller I, Reeder J, Manning L, Laman M, Michon P, Siba P, Allen S, Davis TM., Commission of the European Communities, and Wellcome Trust

Subjects
0301 basic medicine, Population genetics, Gene flow, 0302 clinical medicine, MESH: Genetic Variation, Biology (General), African Continental Ancestry Group, media_common, Genetics, 0303 health sciences, education.field_of_study, Human migration, General Neuroscience, 030305 genetics & heredity, General Medicine, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Geography, Genomics and Evolutionary Biology, MESH: Human Migration, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Medicine, admixture, gene-flow, Research Article, Gene Flow, QH301-705.5, Science, media_common.quotation_subject, Human Migration, Population, Black People, Genomics, Biology, africa, chromosome painting, evolutionary biology, genomics, human, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Genetic variation, Humans, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, MESH: Africa South of the Sahara, Allele, education, Africa South of the Sahara, MESH: Gene Flow, MESH: Genome, Human, 030304 developmental biology, Genetic diversity, MESH: Humans, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], General Immunology and Microbiology, business.industry, Genome, Human, Haplotype, Genetic Variation, MESH: Haplotypes, 030104 developmental biology, Genetic epidemiology, Haplotypes, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Agriculture, Evolutionary biology, Africa, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: African Continental Ancestry Group, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business, 030217 neurology & neurosurgery, Demography, Diversity (politics)
Abstract

Similarity between two individuals in the combination of genetic markers along their chromosomes indicates shared ancestry and can be used to identify historical connections between different population groups due to admixture. We use a genome-wide, haplotype-based, analysis to characterise the structure of genetic diversity and gene-flow in a collection of 48 sub-Saharan African groups. We show that coastal populations experienced an influx of Eurasian haplotypes over the last 7000 years, and that Eastern and Southern Niger-Congo speaking groups share ancestry with Central West Africans as a result of recent population expansions. In fact, most sub-Saharan populations share ancestry with groups from outside of their current geographic region as a result of gene-flow within the last 4000 years. Our in-depth analysis provides insight into haplotype sharing across different ethno-linguistic groups and the recent movement of alleles into new environments, both of which are relevant to studies of genetic epidemiology. DOI: http://dx.doi.org/10.7554/eLife.15266.001, eLife digest Our genomes contain a record of historical events. This is because when groups of people are separated for generations, the DNA sequence in the two groups’ genomes will change in different ways. Looking at the differences in the genomes of people from the same population can help researchers to understand and reconstruct the historical interactions that brought their ancestors together. The mixing of two populations that were previously separate is known as admixture. Africa as a continent has few written records of its history. This means that it is somewhat unknown which important movements of people in the past generated the populations found in modern-day Africa. Busby et al. have now attempted to use DNA to look into this and reconstruct the last 4000 years of genetic history in African populations. As has been shown in other regions of the world, the new analysis showed that all African populations are the result of historical admixture events. However, Busby et al. could characterize these events to unprecedented level of detail. For example, multiple ethnic groups from The Gambia and Mali all show signs of sharing the same set of ancestors from West Africa, Europe and Asia who mixed around 2000 years ago. Evidence of a migration of people from Central West Africa, known as the Bantu expansion, could also be detected, and was shown to carry genes to the south and east. An important next step will be to now look at the consequences of the observed gene-flow, and ask if it has contributed to spreading beneficial, or detrimental, mutations around Africa. DOI: http://dx.doi.org/10.7554/eLife.15266.002

Published
2016
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8. Admixture into and within sub-Saharan Africa

Author

Busby, GBJ, Band, G, Le, QS, Jallow, M, Bougama, E, Mangano, VD, Amenga-Etego, LN, Enimil, A, Apinjoh, T, Ndila, CM, Manjurano, A, Nyirongo, V, Doumbo, O, Rockett, KA, Kwiatkowski, DP, Spencer, CCA, Busby, GBJ, Band, G, Le, QS, Jallow, M, Bougama, E, Mangano, VD, Amenga-Etego, LN, Enimil, A, Apinjoh, T, Ndila, CM, Manjurano, A, Nyirongo, V, Doumbo, O, Rockett, KA, Kwiatkowski, DP, and Spencer, CCA

Abstract

Similarity between two individuals in the combination of genetic markers along their chromosomes indicates shared ancestry and can be used to identify historical connections between different population groups due to admixture. We use a genome-wide, haplotype-based, analysis to characterise the structure of genetic diversity and gene-flow in a collection of 48 sub-Saharan African groups. We show that coastal populations experienced an influx of Eurasian haplotypes over the last 7000 years, and that Eastern and Southern Niger-Congo speaking groups share ancestry with Central West Africans as a result of recent population expansions. In fact, most sub-Saharan populations share ancestry with groups from outside of their current geographic region as a result of gene-flow within the last 4000 years. Our in-depth analysis provides insight into haplotype sharing across different ethno-linguistic groups and the recent movement of alleles into new environments, both of which are relevant to studies of genetic epidemiology.

Published
2016

9. The Greeks in the West: genetic signatures of the Hellenic colonisation in southern Italy and Sicily

Author

Tofanelli, S, BRISIGHELLI, FRANCESCA, Anagnostou, P, Busby, GBJ, Ferri, G, Thomas, MG, Taglioli, L, Rudan, I, Zemunik, T, Hayward, C, Bolnick, D, Romano, V, Cali, F, Luiselli, D, Shepherd, GB, Tusa, S, Facella, A, Capelli, C, Tofanelli, S, BRISIGHELLI, FRANCESCA, Anagnostou, P, Busby, GBJ, Ferri, G, Thomas, MG, Taglioli, L, Rudan, I, Zemunik, T, Hayward, C, Bolnick, D, Romano, V, Cali, F, Luiselli, D, Shepherd, GB, Tusa, S, Facella, A, and Capelli, C

Published
2015

10. Static and Moving Frontiers: The Genetic Landscape of Southern African Bantu-Speaking Populations

Author

Marks, Sj, Montinaro, F, Levy, H, Brisighelli, F, Ferri, G, Bertoncini, S, Batini, C, Busby, Gbj, Arthur, C, Mitchell, P, Stewart, Ba, Oosthuizen, O, Oosthuizen, E, D'Amato, Me, Davison, S, Pascali, V, Capelli, C, Brisighelli, F (ORCID:0000-0001-5469-4413), Pascali, V (ORCID:0000-0001-6520-5224), Marks, Sj, Montinaro, F, Levy, H, Brisighelli, F, Ferri, G, Bertoncini, S, Batini, C, Busby, Gbj, Arthur, C, Mitchell, P, Stewart, Ba, Oosthuizen, O, Oosthuizen, E, D'Amato, Me, Davison, S, Pascali, V, Capelli, C, Brisighelli, F (ORCID:0000-0001-5469-4413), and Pascali, V (ORCID:0000-0001-6520-5224)

Abstract

A consensus on Bantu-speaking populations being genetically similar has emerged in the last few years, but the demographic scenarios associated with their dispersal are still amatter of debate. The frontier model proposed by archeologists postulates different degrees of interaction among incoming agropastoralist and resident foraging groups in the presence of "static" and "moving" frontiers. By combining mitochondrial DNA and Y chromosome data collected from several southern African populations, we show that Bantu-speaking populations from regions characterized by amoving frontier developing after a long-term static frontier have larger hunter-gatherer contributions than groups from areas where a static frontier was not followed by further spatial expansion. Differences in the female and male components suggest that the process of assimilation of the long-term resident groups into agropastoralist societies was gender biased. Our results show that the diffusion of Bantu languages and culture in Southern Africa was a process more complex than previously described and suggest that the admixture dynamics between farmers and foragers played an important role in shaping the current patterns of genetic diversity.

Published
2015

11. The Role of Recent Admixture in Forming the Contemporary West Eurasian Genomic Landscape

Author

Busby, Gbj, Hellenthal, G, Montinaro, F, Tofanelli, S, Bulayeva, K, Rudan, I, Zemunik, T, Hayward, C, Toncheva, D, Karachanak Yankova, S, Nesheva, D, Anagnostou, P, Cali, F, Brisighelli, Francesca, Romano, V, Lefranc, G, Buresi, C, Ben Chibani, J, Haj Khelil, A, Denden, S, Ploski, R, Krajewski, P, Hervig, T, Moen, T, Herrera, Rj, Wilson, Jf, Myers, S, Capelli, C., Brisighelli, Francesca (ORCID:0000-0001-5469-4413), Busby, Gbj, Hellenthal, G, Montinaro, F, Tofanelli, S, Bulayeva, K, Rudan, I, Zemunik, T, Hayward, C, Toncheva, D, Karachanak Yankova, S, Nesheva, D, Anagnostou, P, Cali, F, Brisighelli, Francesca, Romano, V, Lefranc, G, Buresi, C, Ben Chibani, J, Haj Khelil, A, Denden, S, Ploski, R, Krajewski, P, Hervig, T, Moen, T, Herrera, Rj, Wilson, Jf, Myers, S, Capelli, C., and Brisighelli, Francesca (ORCID:0000-0001-5469-4413)

Abstract

Over the past few years, studies of DNA isolated from human fossils and archaeological remains have generated considerable novel insight into the history of our species. Several landmark papers have described the genomes of ancient humans across West Eurasia, demonstrating the presence of large-scale, dynamic population movements over the last 10,000 years, such that ancestry across present-day populations is likely to be a mixture of several ancient groups [1-7]. While these efforts are bringing the details of West Eurasian prehistory into increasing focus, studies aimed at understanding the processes behind the generation of the current West Eurasian genetic landscape have been limited by the number of populations sampled or have been either too regional or global in their outlook [8-11]. Here, using recently described haplotype-based techniques [11], we present the results of a systematic survey of recent admixture history across Western Eurasia and show that admixture is a universal property across almost all groups. Admixture in all regions except North Western Europe involved the influx of genetic material from outside of West Eurasia, which we date to specific time periods. Within Northern, Western, and Central Europe, admixture tended to occur between local groups during the period 300 to 1200 CE. Comparisons of the genetic profiles of West Eurasians before and after admixture show that population movements within the last 1,500 years are likely to have maintained differentiation among groups. Our analysis provides a timeline of the gene flow events that have generated the contemporary genetic landscape of West Eurasia.

Published
2015

12. Static and Moving Frontiers: The Genetic Landscape of Southern African Bantu-Speaking Populations

Author

Marks, Sj, Montinaro, F, Levy, H, Brisighelli, Francesca, Ferri, G, Bertoncini, S, Batini, C, Busby, Gbj, Arthur, C, Mitchell, P, Stewart, Ba, Oosthuizen, O, Oosthuizen, E, D'Amato, Me, Davison, S, Pascali, V, Capelli, C., Brisighelli, Francesca (ORCID:0000-0001-5469-4413), Marks, Sj, Montinaro, F, Levy, H, Brisighelli, Francesca, Ferri, G, Bertoncini, S, Batini, C, Busby, Gbj, Arthur, C, Mitchell, P, Stewart, Ba, Oosthuizen, O, Oosthuizen, E, D'Amato, Me, Davison, S, Pascali, V, Capelli, C., and Brisighelli, Francesca (ORCID:0000-0001-5469-4413)

Abstract

A consensus on Bantu-speaking populations being genetically similar has emerged in the last few years, but the demographic scenarios associated with their dispersal are still a matter of debate. The frontier model proposed by archeologists postulates different degrees of interaction among incoming agropastoralist and resident foraging groups in the presence of "static" and "moving" frontiers. By combining mitochondrial DNA and Y chromosome data collected from several southern African populations, we show that Bantu-speaking populations from regions characterized by a moving frontier developing after a long-term static frontier have larger hunter-gatherer contributions than groups from areas where a static frontier was not followed by further spatial expansion. Differences in the female and male components suggest that the process of assimilation of the long-term resident groups into agropastoralist societies was gender biased. Our results show that the diffusion of Bantu languages and culture in Southern Africa was a process more complex than previously described and suggest that the admixture dynamics between farmers and foragers played an important role in shaping the current patterns of genetic diversity.

Published
2014

13. The peopling of Europe and the cautionary tale of Y chromosome lineage R-M269

Author

Busby, Gbj, Brisighelli, Francesca, Sanchez Diz, P, Ramos Luis, E, Martinez Cadenas, C, Thomas, Mg, Bradley, Dg, Gusmao, L, Winney, B, Bodmer, W, Vennemann, M, Coia, V, Scarnicci, F, Tofanelli, S, Vona, G, Ploski, R, Vecchiotti, C, Zemunik, T, Rudan, I, Karachanak, S, Toncheva, D, Anagnostou, P, Ferri, G, Rapone, C, Hervig, T, Moen, T, Wilson, Jf, Capelli, C., Brisighelli, Francesca (ORCID:0000-0001-5469-4413), Busby, Gbj, Brisighelli, Francesca, Sanchez Diz, P, Ramos Luis, E, Martinez Cadenas, C, Thomas, Mg, Bradley, Dg, Gusmao, L, Winney, B, Bodmer, W, Vennemann, M, Coia, V, Scarnicci, F, Tofanelli, S, Vona, G, Ploski, R, Vecchiotti, C, Zemunik, T, Rudan, I, Karachanak, S, Toncheva, D, Anagnostou, P, Ferri, G, Rapone, C, Hervig, T, Moen, T, Wilson, Jf, Capelli, C., and Brisighelli, Francesca (ORCID:0000-0001-5469-4413)

Abstract

Recently, the debate on the origins of the major European Y chromosome haplogroup R1b1b2-M269 has reignited, and opinion has moved away from Palaeolithic origins to the notion of a younger Neolithic spread of these chromosomes from the Near East. Here, we address this debate by investigating frequency patterns and diversity in the largest collection of R1b1b2-M269 chromosomes yet assembled. Our analysis reveals no geographical trends in diversity, in contradiction to expectation under the Neolithic hypothesis, and suggests an alternative explanation for the apparent cline in diversity recently described. We further investigate the young, STR-based time to the most recent common ancestor estimates proposed so far for R-M269-related lineages and find evidence for an appreciable effect of microsatellite choice on age estimates. As a consequence, the existing data and tools are insufficient to make credible estimates for the age of this haplogroup, and conclusions about the timing of its origin and dispersal should be viewed with a large degree of caution

Published
2011

14. Ancient human genomes suggest three ancestral populations for present-day Europeans

Author

Joanna L. Mountain, Michael F. Hammer, Ruslan Ruizbakiev, Cesare de Filippo, Kumarasamy Thangaraj, David E. C. Cole, Haim Ben-Ami, Leila Laredj, Mark Lipson, Jüri Parik, Valentino Romano, Andres Ruiz-Linares, Fouad Berrada, Dominique Delsate, Ugur Hodoglugil, Antti Sajantila, Olga Utevska, Shahlo Turdikulova, Tor Hervig, Ludmila P. Osipova, Hovhannes Sahakyan, Robert W. Mahley, Ramiro Barrantes, Kirsten I. Bos, Stanislav Dryomov, Peter H. Sudmant, Nadin Rohland, Heng Li, Gabriel Renaud, Mikhail Voevoda, Claudio M. Bravi, Jean-Michel Guinet, Rem I. Sukernik, Joachim Wahl, Matthias Meyer, Christos Economou, Kay Prüfer, Graciela Bailliet, Mait Metspalu, Mikhail Churnosov, Iosif Lazaridis, Johannes Krause, Bonnie Berger, Levon Yepiskoposyan, Francesca Brisighelli, Francesco Calì, Irene Gallego Romero, Oleg Balanovsky, George Ayodo, Alan Cooper, Alissa Mittnik, Julio Molina, George van Driem, Jean-Michel Dugoujon, Larissa Damba, Fedor Platonov, Nick Patterson, David Reich, Thomas B. Nyambo, David Comas, Olga L. Posukh, Béla Melegh, Draga Toncheva, Alena Kushniarevich, Brenna M. Henn, Montgomery Slatkin, René Vasquez, Elena B. Starikovskaya, Joachim Burger, Ayele Tarekegn, Tatijana Zemunik, Ene Metspalu, Sena Karachanak-Yankova, Lalji Singh, Wolfgang Haak, Susanna Sawyer, Rick A. Kittles, Cheryl A. Winkler, Svante Pääbo, Francisco Rothhammer, Marina Gubina, Pierre Zalloua, Aashish R. Jha, Swapan Mallick, Sergi Castellano, Qiaomei Fu, Desislava Nesheva, Sergey Litvinov, Ingrida Uktveryte, Michael Francken, Cosimo Posth, Theologos Loukidis, Cristian Capelli, Janet Kelso, Sarah A. Tishkoff, Toomas Kivisild, Mark G. Thomas, Elin Fornander, Mercedes Villena, Fredrik Hallgren, Vaidutis Kučinskas, Daniel Corach, George B.J. Busby, Judit Bene, William Klitz, Hamza A. Babiker, Karola Kirsanow, Ruth Bollongino, Rita Khusainova, Evan E. Eichler, Sardana A. Fedorova, Klemetti Näkkäläjärvi, Igor Rudan, Susanne Nordenfelt, Joshua G. Schraiber, Elena Balanovska, Antonio Salas, Richard Villems, Gabriel Bedoya, Elza Khusnutdinova, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Mathematics, Lipson, Mark, Berger Leighton, Bonnie, Lazaridis,I, Patterson,P, Mittnik,A, Renaud,G, Mallick,S, Kirsanow,K, Sudmant,PH, Schraiber,JG, Castellano,S, Lipson,M, Berger,B, Economou,C, Bollongino,R, Fu,Q, Bos,KI, Nordenfelt,S, Li,H, De Filippo,C, Pruefer,K, Sawyer, Posth,C, Haak1,H, Hallgren,F, Fornander,E, Rohland,N, Delsate,D, Francken,M, Guinet,JM, Wah,J, Ayodo,G, Babiker,HA, Bailliet,G, Balanovska,E, Balanovsky,O, Barrantes,R, Bedoya,G, Ben-Ami,H, Bene,J, Berrada,F, Bravi,CM, Brisighelli,F, Busby,GBJ, Cali,F, Churnosov,M, Cole,DEC, Corach,D, Damba,L, van Driem,G, Dryomov,S, Dugoujon,JM, Fedorova,SA, Gallego Romero,I, Gubina,M, Hammer,M, Henn,BM, Hervig,T, Hodoglugi,U, Jha,AR, Karachanak-Yankova,S, Khusainova,R, Khusnutdinova,E, Kittles,R:Kivisild,T, Klitz,W, Kucˇinskas,V, Kushniarevich,A, Laredj,L, Litvinov,S, Loukidis,T, Mahley,RW, Melegh,B, Metspalu,E, Molina,J, Mountain,J, Na¨kka¨la¨ja¨rvi,K, Nesheva,D, Nyambo,T, Osipova,L, Parik,J, Platonov,F, Posukh,O, Romano,V, Rothhammer,F, Rudan,I, Ruizbakiev,R, Sahakyan,H, Sajantila,A, Salas,A, Starikovskaya,EB, Tarekegn,A, Toncheva,D, Turdikulova,S, Uktveryte,I, Utevska,O, Vasquez,R, Villena,M, Voevoda,M, Winkler,CA, Yepiskoposyan,L, Zalloua,P, Zemunik,T, Cooper, Capelli,C, Thomas,MG, Ruiz-inares,A, Tishkoff,SA, Singh,L, Thangaraj,K, Villems,R, Comas,D, Sukernik,R, Metspalu,M, Meyer,M, Eichler,EE, Burger,J, Slatkin,M, Pa¨a¨bo,S, Kelso,J, Reich,D, and Krause,J

Subjects
History, Neanderthal, Biología, Population Dynamics, Present day, Genoma humà, Genome, purl.org/becyt/ford/1 [https], Basal (phylogenetics), Settore BIO/13 - Biologia Applicata, History, Ancient, Genetics, Principal Component Analysis, education.field_of_study, 0303 health sciences, Multidisciplinary, Ancient DNA, 030305 genetics & heredity, food and beverages, Agriculture, Genomics, 3. Good health, Europe, Workforce, CIENCIAS NATURALES Y EXACTAS, Human, Archaeogenetics, Asia, Lineage (genetic), EUROPE, Otras Ciencias Biológicas, European Continental Ancestry Group, Population, Settore BIO/08 - ANTROPOLOGIA, evolution, Europeans, Biology, Article, White People, Ancient, Genètica de poblacions humanes, Human origins, Ciencias Biológicas, 03 medical and health sciences, HUMAN ORIGINS, biology.animal, Humans, ANCIENT DNA, purl.org/becyt/ford/1.6 [https], education, Quantitative Biology - Populations and Evolution, Denisovan, 030304 developmental biology, Genetic diversity, ancient DNA, modern DNA, Europeans, prehistory, Genome, Human, Populations and Evolution (q-bio.PE), biology.organism_classification, Evolutionary biology, FOS: Biological sciences, Upper Paleolithic, Human genome, GENOMICS
Abstract

We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes1,2,3,4 with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians3, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations’ deep relationships and show that early European farmers had ∼44% ancestry from a ‘basal Eurasian’ population that split before the diversification of other non-African lineages., Instituto Multidisciplinario de Biología Celular

Published
2014

15. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α 3.7I form of α-thalassaemia using genome-wide microarray data.

Author

Ndila CM, Nyirongo V, Macharia AW, Jeffreys AE, Rowlands K, Hubbart C, Busby GBJ, Band G, Harding RM, Rockett KA, and Williams TN

Abstract

Background: The -α 3.7I -thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study, we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha ( HBA ) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Ndila CM et al.)

Published
2021
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16. 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 TJC, Andrianaranjaka V, Apinjoh T, Ariani C, Ashley EA, Auburn S, Awandare GA, Ba H, Baraka V, Barry AE, 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 TN, Noedl H, Nosten F, Noviyanti R, Nzila A, Ochola-Oyier LI, Ocholla H, Oduro A, Omedo I, Onyamboko MA, Ouedraogo JB, 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 XZ, 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., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 MalariaGEN et al.)

Published
2021
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17. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α 3.7I form of α-thalassaemia using genome-wide microarray data.

Author

Ndila CM, Nyirongo V, Macharia AW, Jeffreys AE, Rowlands K, Hubbart C, Busby GBJ, Band G, Harding RM, Rockett KA, and Williams TN

Abstract

Background: The -α 3.7I -thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha ( HBA ) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Ndila CM et al.)

Published
2020
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18. Resistance to malaria through structural variation of red blood cell invasion receptors.

Author

Leffler EM, Band G, Busby GBJ, Kivinen K, Le QS, Clarke GM, Bojang KA, Conway DJ, Jallow M, Sisay-Joof F, Bougouma EC, Mangano VD, Modiano D, Sirima SB, Achidi E, Apinjoh TO, Marsh K, Ndila CM, Peshu N, Williams TN, Drakeley C, Manjurano A, Reyburn H, Riley E, Kachala D, Molyneux M, Nyirongo V, Taylor T, Thornton N, Tilley L, Grimsley S, Drury E, Stalker J, Cornelius V, Hubbart C, Jeffreys AE, Rowlands K, Rockett KA, Spencer CCA, and Kwiatkowski DP

Subjects
Adult, Africa South of the Sahara, Child, DNA Copy Number Variations genetics, Gene Frequency, Genome, Human genetics, Humans, Protein Structure, Secondary, Receptors, Cell Surface chemistry, Receptors, Cell Surface genetics, Disease Resistance genetics, Erythrocytes parasitology, Glycophorins chemistry, Glycophorins genetics, Glycophorins metabolism, Host-Parasite Interactions genetics, Malaria, Falciparum genetics, Models, Molecular
Abstract

The malaria parasite Plasmodium falciparum invades human red blood cells by a series of interactions between host and parasite surface proteins. By analyzing genome sequence data from human populations, including 1269 individuals from sub-Saharan Africa, we identify a diverse array of large copy-number variants affecting the host invasion receptor genes GYPA and GYPB We find that a nearby association with severe malaria is explained by a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which encode a serologically distinct blood group antigen known as Dantu. This variant reduces the risk of severe malaria by 40% and has recently increased in frequency in parts of Kenya, yet it appears to be absent from west Africa. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria., (Copyright © 2017, American Association for the Advancement of Science.)

Published
2017
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20. A genetic atlas of human admixture history.

Author

Hellenthal G, Busby GBJ, Band G, Wilson JF, Capelli C, Falush D, and Myers S

Subjects
Alleles, Chromosome Painting methods, DNA genetics, Europe, Eastern ethnology, Genetic Drift, Haplotypes, History, Ancient, Humans, Middle East ethnology, Mongolia ethnology, Polymorphism, Single Nucleotide, Software, Computer Simulation, Genotyping Techniques, Human Migration history, Models, Genetic, Population genetics
Abstract

Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years. We identified events whose dates and participants suggest they describe genetic impacts of the Mongol empire, Arab slave trade, Bantu expansion, first millennium CE migrations in Eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations.

Published
2014
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