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: 9982343
• 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/9982343
• 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.

项目总结