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: 10586271
• 负责人: David E Reich
• 金额: $ 7.98万
• 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/10586271
• 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; Funding; Genes; Genetic Drift; Genetic Predisposition to Disease; Genetic Recombination; Genetic Variation; Genome; Genomic Segment; Genomics; Genotype; Grant; Graph; Growth; Human; Human Biology; Individual; Inherited; Iran; Laboratories; Lead; Learning; Link; Malignant neoplasm of prostate; Manuals; Maps; Medical Genetics; Methodology; Methods; Modeling; Modernization; Movement; Natural Selections; Near East; Northern Europe; Paper; Persons; Population; Population Analysis; 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; Time; Trees; Variant; Work; analytical method; base; detection method; disorder risk; flexibility; gene discovery; genetic variant; genome-wide; heterogenous data; human population study; insight; method development; novel; programs; simulation; statistics; study population; 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.

项目摘要/摘要 人口历史塑造了人类的生物学、基因变异和疾病风险。尽管它很重要，但分析 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 重建过去的一些方面。这使得开发能够对 已被记录为基因组和古代DNA数据结果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，这是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 揭示关于生物学和历史的同样多的东西。该提案旨在通过扩展 为补助金R01 GM100233提供资金，该基金在2012-2020年间支持私人投资机构的中央研究方案 开发研究人类人口历史的方法，并利用这些信息了解 生物学，产生了70种与赠款相关的出版物。我们提出三个新目标： (1)创建一条无偏见的处理古代DNA的管道，并利用它重新分析世界数据； (2)扩展混合图的种群历史推断能力； (3)引入分析种群历史和生物学的新工具。 这笔赠款将在四个方面发挥价值。(A)将支持制定方法和方便用户使用 以及文件齐全的软件，这对进化和医学遗传学将是重要的。(B)会支持 将导致与在最近或最近在人类种群中发现疾病基因相关的见解的工作 古人用来混合的。(C)它将导致关于人类历史的新发现。(D)它将制作一份可供公众使用的 世界古代DNA数据的再处理版本，将对社区有广泛的用途。 与医学遗传学的联系很重要。在过去，我们成功地将一项直接 我们实验室检测和表征混合种群的工作与人类的联系 生物学包括对疾病的遗传易感性。我们利用了非裔美国人混血的历史 发现新的疾病基因(例如前列腺癌的危险因素)，了解变异 不同人群之间的疾病风险，并记录重组生物学上的差异 非洲裔美国人和没有西非血统的人，预计会导致不同的 与重组错误相关的疾病的风险水平。我们的重点是找出 种群历史和疾病风险也突出了发现隐性疾病基因的机会 在南亚数以千计的创始人团体中。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关于人类变异和疾病风险的最新研究相协同。