Population Genomics of Geographically and Ethnically Diverse Africans

地理和种族多样化非洲人的人口基因组学

• 批准号: 8412026
• 负责人: Joseph L. Lachance
• 金额: $ 5.13万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-12-15 至 2014-12-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8412026
• 关键词: 5' Untranslated Regions; Acute; Address; Admixture; Africa; African; Alleles; Cataloging; Catalogs; Climate; Computer Simulation; Data; Data Set; Demography; Diabetes Mellitus; Diet; Disease; Disease Association; Environment; Exons; Gene Frequency; Genes; Genetic; Genetic Medicine; Genetic Variation; Genome; Genomics; Genotype; Goals; Haplotypes; Health; Heredity; Human; Human Genetics; Human Genome; Hypertension; Individual; Introns; Knowledge; Life; Linkage Disequilibrium; Methods; Natural Selections; Partner in relationship; Pattern; Phase; Play; Population; Population Genetics; Population Sizes; Public Health; Reading; Recording of previous events; Relative (related person); Research Project Grants; Resources; Role; Running; Site; Structure; Technology; Testing; Time; Training; Variant; Work; cost; design; disorder risk; expectation; experience; genetic analysis; genetic variant; genome sequencing; genome wide association study; genome-wide; human population genetics; mathematical model; migration; next generation sequencing; novel; post-doctoral training; statistics; theories; trait

DESCRIPTION (provided by applicant): The proposed research project involves detailed characterization of whole genome variation in understudied ethnically and geographically diverse Africans living in distinct environments and with distinct diets. The dataset represents the most detailed catalog of genomic variation in under-represented African populations created to date. Population genetic analyses will enable us to identify potential functional variants that play a role in adaptation to diverse environments and to infer the demographic history of populations. Despite immense amounts of genetic variation and significant public health challenges, African human genetics has largely been understudied. It is important that recent advances in genomics and genetic medicine do not ignore Africa populations. Using high-coverage whole genome sequencing we will analyze whole genome sequences of multiple individuals in multiple African populations in order to infer both recent and ancient demographic history in Africa and to identify targets of natural selection in the human genome. Existing statistical population genetics approaches will be applied, and novel theoretical approaches will be developed to analyze population genomics datasets using a combination of computer simulations and mathematical modeling. Whole genome sequences will also be combined with data generated from genotyping arrays to assess the impact of SNP ascertainment bias on diverse African populations. Genomic variation present in African populations living in diverse climates and with diverse diets (agriculturalists, pastoralists and hunter- gatherers) is relevant o diseases of modernity, such as hypertension and diabetes. In addition, genetic variation found will be useful for genome-wide association studies of African populations. This proposed study is also highly relevant to the NIH's Human Heredity and Health in Africa Project (H3Africa), and this research project will contribute substantially to postdoctoral training. Finally, analytic approaches developed for African populations will also be useful to other studies that utilize next-generation sequencing technology.

描述(由申请人提供)：拟议的研究项目涉及对生活在不同环境和饮食中的未被研究的种族和地理多样性的非洲人的整个基因组变异的详细描述。该数据集代表了迄今为止创建的代表性不足的非洲人口中最详细的基因组变异目录。人口遗传分析将使我们能够确定在适应不同环境方面发挥作用的潜在功能变异，并推断人口的人口历史。尽管存在巨大的基因变异和重大的公共卫生挑战，但非洲人类遗传学在很大程度上仍未得到充分研究。重要的是，基因组学和遗传医学的最新进展不能忽视非洲人口。利用高覆盖率的全基因组测序，我们将分析多个非洲种群中多个个体的全基因组序列，以推断非洲现代和古代人口历史，并确定人类基因组中自然选择的目标。将应用现有的统计种群遗传学方法，并将开发新的理论方法，使用计算机模拟和数学建模相结合的方法来分析种群基因组数据集。全基因组序列还将与基因分型阵列产生的数据相结合，以评估SNP确定偏差对非洲不同人群的影响。生活在不同气候和不同饮食的非洲人口(农场主、牧民和狩猎采集者)的基因组变异与高血压和糖尿病等现代性疾病有关。此外，所发现的遗传变异将有助于对非洲人口进行全基因组关联研究。这项拟议的研究也与美国国立卫生研究院的非洲人类遗传与健康项目(H3Africa)高度相关，该研究项目将为博士后培训做出重大贡献。最后，为非洲人口开发的分析方法也将对利用下一代测序技术的其他研究有用。