Integrative Genomic Analyses of Human Evolution and Adaptation in Africa

非洲人类进化和适应的综合基因组分析

• 批准号: 10561604
• 负责人: Sarah Anne Tishkoff
• 金额: $ 53.43万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10561604
• 关键词: Africa; African; African ancestry; Biological; Biological Assay; Biological Models; Biomedical Research; CRISPR/Cas technology; Cell Line; Cells; Communities; Complex; Data; Diet; Evolution; Gene Expression; Genetic; Genomic approach; Genomics; Human; Immune; In Vitro; Knowledge; Linkage Disequilibrium; Luciferases; Metabolic; Modernization; Natural Selections; Pattern; Persons; Phenotype; Population; Recording of previous events; Reporter; SNP array; Sampling; Shapes; Site; Source; Structure; Variant; biomedical resource; cardiometabolism; epigenomics; ethnic diversity; field study; functional genomics; genetic association; genome sequencing; genome wide association study; genome-wide; genomic variation; gut microbiome; in vivo; in vivo Model; metabolome; metabolomics; microbiome; model organism; novel; phenotypic data; trait; transcriptomics; whole genome

Abstract Africa is the site of origin of modern humans, contains the greatest levels of human genomic variation, and is the source of the worldwide range expansion of modern humans in the past 100,000 years. However, a fundamental gap in knowledge exists regarding African genomic and phenotypic variation, resulting in a lag in biomedical research, not only in Africans, but also in people of recent African descent. We will apply an integrative evolutionary genomics approach incorporating genomic, metabolomic, microbiome, epigenomic, and transcriptomic data in combination with detailed phenotypic data to reconstruct African population history and better understand the genetic basis of adaptive traits in ethnically diverse African populations. Specifically, we will use genome-wide SNP arrays as well as high-coverage whole genome sequencing data to identify targets of natural selection in these populations and to look for genetic associations with gene expression as well as anthropometric, cardio-metabolic, and immune related traits. We will use functional genomics approaches to identify causal regulatory loci and to study their impact on gene expression in vitro using high-throughput luciferase reporter assays in appropriate cell lines. We will also use Crispr-Cas9 technology to validate and characterize the functional impact of potential casual variants in both human cells and in vivo in model systems. Lastly, we will characterize gut microbiome diversity and examine correlations with diet, genetic and environmental variation. Our data will generate a deeper understanding of African genomic diversity, population structure, and patterns of linkage disequilibrium that are critical for the successful application and interpretation of genome wide association studies in African-descent populations. Furthermore, this study will have important implications for understanding the genetic basis of intermediate phenotypes (gene expression and the metabolome) and of complex traits in Africans. In addition, the data collected will be an important resource for the biomedical research community. Lastly, our study will shed light on human evolutionary history and evolutionary forces shaping patterns of genomic variation in ethnically diverse humans.

摘要 非洲是现代人的发源地，含有最高水平的人类基因组 变异，是过去现代人在世界范围内范围扩大的根源 10万年前。然而，关于非洲基因组和生物多样性的知识存在根本性的差距 表型变异，导致生物医学研究滞后，不仅在非洲人，而且在 新近的非洲人后裔。我们将应用一种综合进化基因组学方法 整合基因组、代谢组、微生物组、表观基因组和转录组数据 结合详细的表型数据重建非洲人口历史并更好地 了解非洲不同种族人群适应性特征的遗传基础。 具体地说，我们将使用全基因组SNP阵列以及高覆盖率的全基因组 对数据进行测序以确定这些群体中自然选择的目标并寻找基因 基因表达与人体测量、心脏代谢和免疫的关系 相关特征。我们将使用功能基因组学方法来确定因果调控基因座和 用高通量荧光素酶报告分析研究它们对体外基因表达的影响 在合适的细胞系中。我们还将使用Crispr-Cas9技术来验证和表征 人体细胞和体内模型系统中潜在的偶然变异的功能影响。 最后，我们将描述肠道微生物群的多样性，并检查与饮食、遗传因素的相关性。 和环境的变化。我们的数据将对非洲基因组有更深入的了解 多样性、种群结构和连锁不平衡模式对 全基因组关联研究在非洲裔中的成功应用和解释 人口。此外，这项研究将对理解遗传 中间表型(基因表达和代谢组)和复杂性状的基础 非洲人。此外，收集到的数据将成为生物医学研究的重要资源 社区。最后，我们的研究将揭示人类进化史和进化力。 塑造不同种族人类的基因组变异模式。