Characterizing modes of natural selection via diverse ancient and modern samples

通过不同的古代和现代样本表征自然选择模式

• 批准号: 10463845
• 负责人: Emilia Huerta-Sanchez
• 金额: $ 38.02万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10463845
• 关键词: Address; Admixture; Americas; Biological; Biology; Collection; DNA; DNA Sequence; Data; Data Set; Disease; Environment; European; Event; Evolution; Genes; Genetic Variation; Genomics; Goals; Human; Human Genome; Individual; Knowledge; Libraries; Medical; Methods; Modernization; Mutation; Natural Selections; Pattern; Phenotype; Play; Population; Preparation; Process; Publishing; Recording of previous events; Research; Research Project Grants; Role; Sampling; Statistical Methods; Technology; Work; base; comparative; genetic makeup; genome-wide analysis; genomic locus; human disease; improved; method development; novel sequencing technology; personalized medicine; risk variant; tool

Project Summary   With the advent of new sequencing technologies, we now have generated more data than ever before. These data have greatly improved our knowledge of human history, human adaptation to different environments and human disease. Genome-wide studies have highlighted many genes or genomic loci that may play a role in adaptive or disease related phenotypes of biological importance. Now that we have access to thousands of human genomes from a diverse set of populations around the globe, we can zoom in at the local scale (e.g. within a gene) and leverage information from multiple populations to understand the observed patterns of genetic variation, without the ascertainment bias associated with the older array-based technologies. In addition, thanks to advances in DNA extraction and library preparation, we now are beginning to have access to DNA sequence data from ancient human samples. We propose to leverage these collections of modern and ancient sequence data to address some key questions in the field, and we have identified opportunities for methods development and biological discovery. The common theme in the proposal is to understand the different modes of natural selection in human populations. We plan to develop methods to detect shared selective events across populations by means of extending current statistical summaries, and methods for detecting admixture-facilitated adaptation which we believe is likely a common mode of natural selection based on our earlier published work. We will apply these tools to new datasets to characterize the interplay of natural selection, archaic and modern admixture in populations in the Americas and make a comparative analysis of modern and ancient European samples to understand the changing profile of medically important risk alleles for disease. As a result our work will reveal evolutionary processes that have played an important role in human evolution and disease.

项目摘要 -- 随着新的测序技术的出现，我们现在已经产生了更多的数据 比以往任何时候都要好。这些数据极大地提高了我们对人类历史的了解， 人类对不同环境和人类疾病的适应。全基因组研究 强调了许多基因或基因组位置可能在适应性或 具有生物学重要性的疾病相关表型。现在我们有权访问 来自全球不同人群的数千个人类基因组，我们 可以放大局部尺度(例如，在一个基因内)并利用来自 多个群体了解观察到的遗传变异模式，而不是 与旧的基于阵列的技术相关的确定偏差。此外, 多亏了DNA提取和文库准备方面的进步，我们现在开始 可以获取古人类样本的DNA序列数据。 我们建议利用这些现代和古代序列数据的集合来 解决了该领域的一些关键问题，我们已经确定了以下机会 方法发展和生物学发现。提案中的共同主题是 以了解人类种群中自然选择的不同模式。我们计划 开发方法，通过以下方式跨人群检测共享的选择性事件 扩展当前统计摘要以及用于检测促进掺混物的方法 适应，我们认为这可能是一种常见的自然选择模式，基于我们的 更早出版的作品。我们将把这些工具应用于新的数据集，以表征 自然选择、古代和现代混合在种群中的相互作用 并对现代和古代欧洲的样本进行了比较分析 了解医学上重要的疾病风险等位基因的变化情况。作为一名 结果我们的工作将揭示进化过程，这些过程在 人类进化和疾病。

项目成果

Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure.

用于检测种群结构的古代单倍型推断的基于模拟的基准测试。

• DOI: 10.1101/2023.09.28.560049
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Tretmanis,JazepsMedina;Jay,Flora;Avila-Árcos,MaríaC;Huerta-Sanchez,Emilia
• 通讯作者: Huerta-Sanchez,Emilia

Simultaneous Viral Exposure and Protection from Neanderthal Introgression.

同时进行病毒暴露和免受尼安德特人渗入的保护。

• DOI: 10.1016/j.cell.2018.09.019
• 发表时间: 2018
• 期刊: Cell
• 影响因子: 64.5
• 作者: Huerta-Sánchez,Emilia;Casey,FergalP
• 通讯作者: Casey,FergalP

ABO Genetic Variation in Neanderthals and Denisovans.

• DOI: 10.1093/molbev/msab109
• 发表时间: 2021-07-29
• 期刊: Molecular biology and evolution
• 影响因子: 10.7
• 作者: Villanea FA;Huerta-Sanchez E;Fox K
• 通讯作者: Fox K

Integrative analysis of DNA, macroscopic remains and stable isotopes of dog coprolites to reconstruct community diet.

DNA，宏观残留物和稳定同位素的综合分析，以重建社区饮食。

• DOI: 10.1038/s41598-021-82362-6
• 发表时间: 2021-02-04
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Witt KE;Yarlagadda K;Allen JM;Bader AC;Simon ML;Kuehn SR;Swanson KS;Cross TL;Hedman KM;Ambrose SH;Malhi RS
• 通讯作者: Malhi RS

Population genetics of wild Macaca fascicularis with low-coverage shotgun sequencing of museum specimens.

• DOI: 10.1002/ajpa.24099
• 发表时间: 2020-09
• 期刊: American journal of physical anthropology
• 影响因子: 2.8
• 作者: Yao L;Witt K;Li H;Rice J;Salinas NR;Martin RD;Huerta-Sánchez E;Malhi RS
• 通讯作者: Malhi RS