Genomic analysis of malaria resistance

Lead Research Organisation: University of Oxford
Department Name: Wellcome Trust Centre for Human Genetics

Abstract

Malaria is one of humankind‘s most persistent and deadly foes, and is a significant determinant of global poverty - causing debilitating illness in approximately half a billion people each year. The greatest burden of the disease falls on African children - over a million die each year of malaria.

This project hinges on a key observation. Many people survive malaria infection and, after repeated exposure, develop some level of immunity.

Our challenge is to answer this question. What are the natural immune responses that protect people from dying or becoming ill due to malaria? Here are two examples of what we mean by an immune response: (1) the person makes antibodies that attach to molecule X on the surface of the parasite; (2) when white blood cells come into contact with a malaria parasite they release chemical Y that kills the parasite. Knowing the answer to this question would help enormously in designing an effective malaria vaccine.

Researchers have been tackling this question for almost a century - why is it so difficult to answer? Part of the problem is that people who are infected with malaria make a vast range of immune responses that have no protective benefit and some that may even be harmful. Searching through all these different immune responses to find those that protect people from becoming ill or dying is like searching for a needle in a haystack. To complicate matters further, much of the immune battle against the malaria parasite happens in the spleen and other inaccessible parts of the body that are very difficult to study in living people.

Recent advances in human genome research are revolutionising the way that we tackle complex problems of this sort. The key observation is that most human genes show variation between individuals. By investigating how this natural genetic variation affects the ability of people to resist infection, we can get deep insights into molecular mechanisms of protective immunity.

Why is this such a porful approach? Firstly, because it doesn‘t require us to measure proteins directly, so we may be able to identify important mechanisms even if they are impossible to measure in living humans - e.g., if they are hidden away in the spleen. Secondly, because new technologies allow us to screen a vast number of genes without knowing anything about their function, making it possible to discover entirely novel mechanisms that are critical for protection against malaria.

Technical Summary

A major obstacle to the development of a malaria vaccine, or improved treatments for severe malaria, is our poor understanding of the host responses that determine protective immunity. Genomic epidemiology offers a radically new approach to the problem, using natural human diversity as a tool to identify host genes that play a critical role in immunity and pathogenesis.

The long-term goal of this MRC Programme, which began in 1996, is to achieve a comprehensive understanding of malaria resistance genes in human populations. It has 3 key objectives:

1. establish epidemiological infrastructure to discover malaria resistance genes

2. develop effective strategies for high-resolution genomic association mapping

3. characterise functional genetic variants that affect immune gene regulation

All 3 areas have seen substantial progress over the past 5 years. We have established a unique epidemiological resource for large-scale genetic association analysis of malaria, which now contains more than 6000 cases of severe malaria plus parents and population controls. Building on the success of this MRC Programme, and on revolutionary advances in the science of human genomic diversity and genotyping technology, we have obtained funding from the Grand Challenges in Global Health initiative to establish a global network for genomic epidemiology of malaria (MalariaGEN) which will yield extremely large epidemiological collections across 14 malaria endemic countries, plus massive-throughput genotyping. Thus we expect to generate a vast amount of data over the next 5 years. However to achieve our long-term goal we need to do more than simply scale up sample size and genotyping capacity. Genomic epidemiology is a young science and there are many basic methodological issues to be addressed.

This proposal aims to tackle some of these fundamental problems.

First, the huge genetic diversity of African populations poses a major challenge for genetic association analysis due to population stratification - we will address this problem both by detailed population sampling and by analytical approaches.

Second, the complex haplotypic structure of the genome across different African populations greatly complicates the process of linkage disequilibrium mapping - this grant will fund an exceptionally high resolution survey of a single region of the genome, the MHC, across three populations.

Third, we remain at a very early stage in understanding the functional basis of genetic variation in immune gene regulation - a problem we will tackle using allele-specific transcript quantification, an emerging technology to which our group has made a significant contribution over the past 3 years.

Publications

10 25 50
 
Title Genomewide association studies of malaria in The Gambia, Ghana and Malawi 
Description Data submitted to European Genotyping Archive. Any bona fide researcher may apply for access via an Independent Data Access committee. 
Type Of Material Biological samples 
Year Produced 2009 
Provided To Others? Yes  
Impact First genomewide association study performed in Africa. Papers in Nature Genetics and Nature Reviews Genetics. Development of an ethical policy for GWAS data release, in consultation with stakeholders in developing countries, published in Nature and PLoS Medicine. 
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Institute for Endemic Diseases IEND
Country Sudan 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Kwame Nkrumah University of Science and Technology (KNUST)
Country Ghana 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Liverpool School of Tropical Medicine
Country United Kingdom 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation London School of Hygiene and Tropical Medicine (LSHTM)
Country United Kingdom 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation MURAZ Center
Country Burkina Faso 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Mahidol University
Country Thailand 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Medical Research Council (MRC)
Department MRC Unit, The Gambia
Country Gambia 
Sector Public 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation National Institute for Medical Research, Tanzania
Country Tanzania, United Republic of 
Sector Public 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Noguchi Memorial Institute for Medical Research (NMRR)
Country Ghana 
Sector Learned Society 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Papua New Guinea Institute of Medical Research
Country Papua New Guinea 
Sector Public 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Pasteur Institute Dakar
Country Senegal 
Sector Charity/Non Profit 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Pasteur Institute, Paris
Country France 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Sapienza University of Rome
Department Parasitology Sapienza
Country Italy 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Stockholm University
Country Sweden 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation The Wellcome Trust Sanger Institute
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Bamako
Department Malaria Research and Training Centre (MRTC) Bamako
Country Mali 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Buea
Country Cameroon 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Colombo
Department Department of Parasitology
Country Sri Lanka 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Malawi
Country Malawi 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Maryland
Department Centre for Vaccine Development (CVD)
Country United States 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Michigan
Country United States 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation University of Oxford
Department Oxford University Clinical Research Unit Vietnam (OUCRU)
Country Viet Nam 
Sector Academic/University 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Malaria Genomic Epidemiology Network (MalariaGEN) 
Organisation Wellcome Trust
Department KEMRI-Wellcome Trust Research Programme
Country Kenya 
Sector Multiple 
PI Contribution I direct the MalariaGEN Resource Centre (http://www.malariagen.net/). CGGH supports Resource Centre activities, particularly statistics, software engineering, and ethics.
Collaborator Contribution MalariaGEN - the Malaria Genomic Epidemiology Network - is a community of more than 100 researchers in 30 countries, working together on projects that require sharing and integration of large amounts of data. MalariaGEN brings together the work of many different partner studies, each of which is led by an independent investigator and has its own scientific objectives. MalariaGEN adds value to partner studies by providing access to genotyping and sequencing technologies, and by providing a framework for sharing and integrating data in consortial and community projects. MalariaGEN provides training and support in genetic data analysis for researchers at partner institutions in malaria-endemic countries. We do this through a data bursary scheme and through an active programme of scientific meetings and training workshops. These activities are supported by the MalariaGEN Resource Centre which has a team of experts in statistics, population genetics and bioinformatics at the Sanger Institute, Oxford University, the London School of Hygiene and Tropical Medicine, and Mahidol University in Bangkok. There are many practical and ethical challenges involved in sharing data across a global network comprising investigators and institutions with great disparities in funding and infrastructure. The MalariaGEN community has been working to develop transparent procedures for ethics and governance. We have a governance committee and an independent data access committee, and network policies have been defined for data sharing and data access.
Impact See www.malariagen.net for data resources and web applications produced by the network. Major recent outputs include: Anopheles gambiae 1000 Genomes Consortium. Genetic diversity of the African malaria vector Anopheles gambiae. Nature 2017. 552:96-100. doi: 10.1038/nature24995. PMID:29186111 (Miles and Kwiatkowski are corresponding authors). This is the largest data resource on mosquito genome variation and population genetics. It identifies over 50 million SNPs, with evidence of ancient population expansions and recent bottlenecks, and strong selective sweeps of insecticide-resistance spreading over large geographical distances and between species. All the data were released open access as soon as available (www.malariagen.net/apps/ag1000g ) 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, Kwiatkowski DP; Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 2017. 356(6343). pii: eaam6393. doi: 10.1126/science.aam6393. PMID: 28522690. By combining GWAS data with genome sequence data from diverse African populations, we discovered a complex structural rearrangement involving the loss of GYPB and gain of two GYPB-A hybrid genes, which reduces the risk of severe malaria by 40%. These findings link structural variation of red blood cell invasion receptors with natural resistance to severe malaria.
 
Description Wellcome Trust Sanger Institute 
Organisation The Wellcome Trust Sanger Institute
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution As head of the Malaria Programme and the Global Health Strategy Group at the Sanger Institute, I'm engaged in all levels of work - scientific, strategic and operational.
Collaborator Contribution The Sanger Institute provides infrastructure, resources and expertise in large-scale genome sequencing, genome-wide SNP typing, informatics and functional genomics.
Impact Examples relevant to this grant: 1. The world's largest repository of DNA samples and clinical data for genetic studies of host-parasite interactions in malaria 2. Publication of the first genome-wide association study of human disease susceptibility in Africa 3. A large multicentre case-control study of severe malaria, representing the largest ongoing genome-wide association study of an infectious disease. In December 2011 we completed genotyping of >1 million SNPs on >20,000 individuals from 10 different populations.
Start Year 2006