AWI-Gen Phase 2: Genomic and environmental risk factors for cardiometabolic disease in Africans

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Project Summary In line with the objectives of the H3Africa Consortium and the parent grant (AWI-Gen) this study aims to augment African genomic data from diverse populations to ensure that Africa is not left behind in the genomic revolution. We will specifically target previously unstudied populations to discover additional African genetic diversity and to perform population genetic studies that will shed light on migration and admixture events that led to the current population distribution on the continent. The research is proposed in three phases, each providing more information and datasets that will become available to the global research community. This first phase will involve short-read sequences from eight previously unstudied African populations (50 individuals each). The second phase will increase the sample size per population to 100, to better estimate allele frequencies, and will also include long-read sequencing to build reference graphs for African populations to improve variant calling accuracy. The third phase will assess the transcriptomic and methylation profiles in 300 individuals to provide insight into the functional interpretation of novel variants and variants identified in genome-wide association studies. To develop data for better representation of African genetic diversity spanning the four major ethnolinguistic divisions (Niger-Congo, Nilo-Saharan and Afro-Asiatic and North African) we will focus on WGS from understudied geographic regions (Figure 1). The WGS data will be integrated into an open and easily accessible resource such as the African Genome Variation database being developed by H3ABioNet. We will perform in depth population genetic analyses aimed at a better understanding of genomic diversity, migration, admixture and demographic history on the continent. This would include testing various alternative models for the Bantu-migration and will provide a better contextualization of data from ancient genomes. To enable a better assembly of short-read sequences we plan to sequence a subset of these genomes using a long-read sequencing technique (PacBio). This dataset would contribute to other global efforts aimed at generating reference genomes. The transcriptomic and methylation datasets will be of immense value in inferring the possible roles of newly discovered variants and their relevance in health and disease. Through this objective we will start building a functional genome resource for African populations to augment global efforts focused on eQTL identification, alternate splicing and meQTLs. 1