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: 10051376
• 负责人: David E Reich
• 金额: $ 43.12万
• 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/10051376
• 关键词: Address; Admixture; Adoption; Affect; Africa; African; African American; 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; 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生物学，遗传变异和疾病风险。尽管它很重要，但分析性 在全基因组量表上研究历史的方法的分辨率和定性能力受到限制 重建过去的方面。这使得开发能够建模的新方法成为优先事项 由于基因组和古老的DNA数据已记录的主要人口混合物事件 过去十年的革命。目前，世界上古老的DNA数据遭受了主要的技术偏见 无法适当控制，这是用于研究种群混合物与现代和古老的分析工具包 DNA不足，我们才开始开发实现古代DNA潜力的方法 揭示生物学与历史一样多。该建议旨在通过扩展来满足这些需求 授予R01 GM100233的资金，从2012 - 2020年支持PIS的中央研究计划 开发研究人口历史并利用此信息学习的方法 生物学，导致70个与该赠款相关的出版物。我们提出了三个新目标： （1）创建一条无偏的管道来处理古代DNA，并使用它重新分析了世界数据； （2）扩展了混合图的能力来进行人口历史推断； （3）引入新的工具，用于分析人口历史和生物学。 这笔赠款将以四种方式具有价值。 （a）它将支持方法和用户友好的开发 有据可查的软件对于进化和医学遗传学很重要。 （b）它将支持 将导致与在最近的人群中找到疾病基因有关的洞察力的工作 古老的混合。 （c）这将导致有关人类历史的新发现。 （d）它将产生公开可用的 对社区广泛使用的世界古代DNA数据的重新加入版本。 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种群混合物的工作与人类之间的联系 生物学包括遗传易感性。我们利用非裔美国人的混合历史 使新的疾病基因发现（例如，前列腺癌的危险因素），了解变异 人群疾病风险，并记录重组生物学的差异 非洲裔美国人和没有西非血统的人，预计会导致不同 与重组错误有关的疾病风险水平。我们专注于绘制连接之间的连接 人口病史和疾病风险还强调了发现隐性疾病基因的机会 在南亚成千上万的创始人团体中。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有关人类变异和疾病风险的最新研究协同作用。