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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

基本信息

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
项目类别：
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

项目摘要

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