Population genomics with pedigrees: new approaches for studying contemporary evolution

具有谱系的群体基因组学：研究当代进化的新方法

• 批准号: 10407053
• 负责人: Nancy Chen
• 金额: $ 38.5万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10407053
• 关键词: Affect; Biology; Collaborations; Data; Data Set; Demography; Drops; Drug resistance; Evolution; Florida; Frequencies; Future; Future Generations; Gene Frequency; Generations; Genetic; Genetic Recombination; Genetic Variation; Genome; Genomic Segment; Genomics; Haplotypes; Health; Human; Immigrant; Individual; Intervention; Knowledge; Left; Livestock; Measures; Medical; Methods; Modeling; Modernization; Nature; Pattern; Phenotype; Population; Population Genetics; Process; Public Health; Research; Role; Shapes; Sheep; System; Testing; Time; Variant; Work; base; environmental change; fitness; genetic evolution; genetic pedigree; genomic data; genomic variation; human genomics; improved; individual variation; insight; life history; novel strategies; pesticide resistance; reproductive success; response; transmission process; whole genome

PROJECT SUMMARY There are now many beautiful examples of phenotypic evolution on ecological timescales. Nevertheless, technological challenges and limited availability of temporal genomic data have left a large gap in knowledge of short-term evolutionary dynamics at the genomic level. Indeed, measuring evolution of natural populations in real-time remains challenging, and systems with sufficient data to study contemporary genetic evolution are rare. The proposed work combines evolutionary genomics with long-term demographic and pedigree data to investigate the evolution of natural populations on short timescales. Long-term, individual-based studies that have accumulated extensive phenotypic, environmental, and fitness data for thousands of individuals on a multigenerational pedigree provide a unique opportunity to study how short-term evolution occurs. In particular, knowledge of the population pedigree, the relationships among all individuals in a population over time, provides the ability to observe directly the actual processes underlying allele frequency change. The PI developed the Florida Scrub-Jay (Aphelocoma coerulescens) as a model for evolutionary genomics by adding substantial genomic data to a 50-year demographic study and formed collaborations with other groups with similar long-term datasets. This study will track the inheritance of the entire genome down the pedigree, as it is broken up by recombination over the generations, in two classic study systems: the Florida Scrub-Jay and the Soay sheep. Elucidating how an individual's genome is distributed across its descendants from generation to generation provides a powerful framework for determining how individual variation in lifetime reproductive success predicts variation in individual genetic contributions to future generations and allele frequency change and for identifying genomic regions associated with fitness. This project will also develop haplotype-dropping methods that simulate Mendelian transmission of haplotypes down the pedigree to test for short-term selection and improve selection component methods to test for selection at different life-history stages. Application of these methods to the Florida Scrub-Jays will increase understanding of the role of fluctuating selection and life- history trade-offs in maintaining adaptive genetic variation in natural populations. Furthermore, the proposed work will quantify the long-term contributions of immigrants to population genetic diversity and fitness by tracing the frequency and fitness impact of specific immigrant haplotypes across generations. Developing more advanced methods that effectively use pedigree information unlocks unprecedented opportunities to directly measure contemporary evolution and study many key questions in evolutionary biology. The proposed framework outlines a powerful approach for future evolutionary and human genomics research. A better understanding of evolution on ecological time scales offers valuable insights to studies of organismal response to rapid environmental change, as well as the evolution of drug and pesticide resistance.

项目摘要 现在有许多在生态时间尺度上表现型进化的美丽例子。然而，尽管如此， 技术挑战和有限的时间基因组数据的可用性留下了很大的差距， 基因组水平的短期进化动力学。事实上，衡量自然种群的进化， 实时仍然具有挑战性，拥有足够数据来研究当代遗传进化的系统 罕见.这项拟议中的工作将进化基因组学与长期的人口统计学和谱系数据相结合， 研究自然种群在短时间尺度上的进化。长期的、基于个人的研究， 已经积累了大量的表型，环境和健身数据，为成千上万的个人在一个 多代系谱为研究短期进化如何发生提供了一个独特的机会。特别是， 人口谱系的知识，人口中所有个体之间的关系随着时间的推移， 提供了直接观察等位基因频率变化背后的实际过程的能力。的PI 开发了佛罗里达灌丛鸦（Aphelocoma coerulescens）作为进化基因组学的模型， 大量的基因组数据，以50年的人口统计学研究，并形成了与其他团体的合作， 类似的长期数据集。这项研究将追踪整个基因组的遗传谱系，因为它是 在两个经典的研究系统：佛罗里达灌丛鸦和 Soay sheep.阐明一个人的基因组如何在其后代中代代相传 世代提供了一个强有力的框架，以确定如何在终身生殖的个体差异 成功预测了个体对后代遗传贡献的变化和等位基因频率的变化 以及用于识别与适应性相关的基因组区域。该项目还将开发单倍型-丢弃 一种模拟单倍型在系谱中的孟德尔传递以测试短期选择的方法 并改进选择成分法，以测试不同生活史阶段的选择。的应用 这些方法对佛罗里达灌丛鸦将增加对波动选择和生活的作用的理解， 在自然群体中维持适应性遗传变异的历史权衡。此外，拟议的 这项工作将量化移民对人口遗传多样性和健康的长期贡献， 追踪世代间特定移民单倍型的频率和适合度影响。开发更多 有效利用谱系信息的先进方法， 测量当代进化并研究进化生物学中的许多关键问题。拟议 框架概述了未来进化和人类基因组学研究的强大方法。更好的 理解生态时间尺度上的进化为研究生物体反应提供了有价值的见解 快速的环境变化，以及药物和杀虫剂耐药性的演变。