Advanced tools for using ancient DNA to study biology and history

使用古代 DNA 研究生物学和历史的先进工具

• 批准号: 10803645
• 负责人: David E Reich
• 金额: $ 5.16万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10803645
• 关键词: Address; Admixture; Adoption; Affect; Africa; African American population; African ancestry; Asia; Awareness; Biology; Communities; Computer software; DNA; Data; Data Set; Development; Disease; Europe; Event; Farm; Funding; Genes; Genetic Drift; Genetic Predisposition to Disease; Genetic Recombination; Genetic Variation; Genome; Genomics; Genotype; Grant; Graph; Growth; Human; Human Biology; Individual; Inherited; Iran; Laboratories; Learning; Link; Malignant neoplasm of prostate; Manuals; Maps; Medical Genetics; Methodology; Methods; Modeling; Modernization; Movement; Natural Selections; Near East; Northern Europe; Paper; Persons; Population; Predisposition; Process; Protocols documentation; Public Health; Publications; Publishing; Recording of previous events; Reporting; Research; Resolution; Resources; Risk Factors; Running; Sex Bias; Shapes; Southeastern Asia; Space Models; Structure; Testing; Trees; Variant; Work; analytical method; detection method; disorder risk; flexibility; gene discovery; genetic variant; genome-wide; heterogenous data; human population study; improved; insight; method development; novel; programs; simulation; statistics; study population; synergism; tool; user-friendly

PROJECT SUMMARY / ABSTRACT Population history shapes human biology, genetic variation, and disease risk. Despite its importance, analytical methods to study history on a genome-wide scale are limited in both their resolution and qualitative ability to reconstruct aspects of the past. This makes it a priority to develop new methods that are able to model the major population mixture events that have been documented as a result of the genomic and ancient DNA data revolutions in the last decade. At present, the world's ancient DNA data suffer from major technical biases that are not properly controlled for, the analytical toolkit for studying population mixture with modern and ancient DNA is inadequate, and we are only beginning to develop methods that realize the potential of ancient DNA to reveal as much about biology as about history. This proposal aims to address these needs by extending funding for grant R01 GM100233, which from 2012-2020 supported the PIs' central research program on developing methods for studying human population history and leveraging this information to learn about biology, resulting in 70 publications linked to the grant. We propose three new Aims: (1) To create an unbiased pipeline for processing ancient DNA, and to use it reanalyze the world's data; (2) To extend the capabilities of admixture graphs for population history inference; (3) To introduce new tools for analyzing population history and biology. This grant will be of value in four ways. (a) It will support the development of methods and user-friendly and well-documented software that will be important for evolutionary and medical genetics. (b) It will support work that will result in insights relevant to finding disease genes in human populations that are recently or anciently admixed. (c) It will lead to new discoveries about human history. (d) It will produce a publicly available reprocessed version of the world's ancient DNA data that will be of broad use to the community. The link to medical genetics is important. In the past, we have been successful at drawing a direct connection between our laboratory's work on detecting and characterizing population mixture, and human biology including genetic susceptibility to disease. We leveraged the history of admixture in African Americans to make new disease gene discoveries (for example, risk factors for prostate cancer), to understand variation in disease risk across populations, and to document differences in the biology of recombination between African Americans and people who do not have West African ancestry, which are predicted to lead to different levels of risk for diseases associated with errors in recombination. Our focus on drawing connections between population history and disease risk also highlighted the opportunities for discovery of recessive disease genes in thousands of founder groups in South Asia. We anticipate that the methods and resources we develop with the support of this grant will continue to synergize with the latest research on human variation and disease risk.

项目概要/摘要 人口历史塑造了人类生物学、遗传变异和疾病风险。尽管分析很重要， 在全基因组范围内研究历史的方法在分辨率和定性能力方面都受到限制。 重建过去的各个方面。这使得开发能够模拟的新方法成为当务之急。 根据基因组和古代 DNA 数据记录的主要种群混合事件 过去十年的革命。目前，世界古代 DNA 数据存在重大技术偏差， 没有得到适当的控制，用于研究现代和古代人口混合的分析工具包 DNA 是不够的，我们才刚刚开始开发方法来实现古代 DNA 的潜力 揭示生物学和历史一样多。该提案旨在通过扩展来满足这些需求 拨款 R01 GM100233 的资金，从 2012 年至 2020 年支持 PI 的中央研究计划 开发研究人类历史的方法并利用这些信息来了解 生物学，产生了 70 篇与该资助相关的出版物。我们提出三个新目标： （1）创建一条公正的管道来处理古代DNA，并用它重新分析世界数据； (2) 扩展混合图的群体历史推断能力； (3) 引入分析人口历史和生物学的新工具。 这笔赠款将在四个方面发挥作用。 (a) 它将支持方法的开发和用户友好 以及对进化和医学遗传学非常重要的记录良好的软件。 (b) 它将支持 这项工作将产生与在最近或最近发生的人群中寻找疾病基因相关的见解 古时混杂。 (c) 它将带来关于人类历史的新发现。 (d) 它将产生一个公开的 世界古代 DNA 数据的重新处理版本，将为社区广泛使用。 与医学遗传学的联系很重要。过去，我们已经成功地绘制了直接 我们实验室在检测和表征人口混合方面的工作与人类之间的联系 生物学，包括对疾病的遗传易感性。我们利用非裔美国人的混血历史 发现新的疾病基因（例如前列腺癌的危险因素），了解变异 不同人群的疾病风险，并记录不同人群之间重组生物学的差异 非裔美国人和没有西非血统的人，预计将导致不同的结果 与重组错误相关的疾病风险水平。我们专注于建立之间的联系 人口史和疾病风险也凸显了发现隐性疾病基因的机会 在南亚的数千个创始人团体中。我们预计我们开发的方法和资源 这笔赠款的支持将继续与人类变异和疾病风险的最新研究相结合。