MIRA: Systems genomics of complex traits

MIRA：复杂性状的系统基因组学

• 批准号: 10006841
• 负责人: Patrick C. Phillips
• 金额: $ 36.62万
• 依托单位: UNIVERSITY OF OREGON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-03 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10006841
• 关键词: Address; Biological Models; Caenorhabditis elegans; Complex; Computational Biology; Coupling; Disease; Engineering; Environment; Evolution; Gene Expression Profile; Genes; Genetic; Genetic Recombination; Genetic Transformation; Genetic Variation; Genomics; Genotype; Goals; Health; Human; Individual; Knock-out; Maps; Microfluidics; Nematoda; Organism; Phenotype; Population; Predisposition; Problem Solving; Regulatory Element; Reproduction; Research; Structure; System; Testing; Variant; genetic approach; genetic evolution; genomic locus; human disease; innovation; response; single cell analysis; success; tool; trait

PROJECT SUMMARY The vast majority of individual susceptibility to sickness and disease in humans is generated by complex interactions between multiple genetic loci and the environment, yet we still have very little understanding of how the map between genotype and phenotype is structured or how this structure influences the response to the environment and long-term evolutionary change. In particular, complex genetic networks should generate pleiotropic relationships among traits whose functional coupling can make individual effects difficult to examine using traditional knockout approaches. Although the structure of these networks is known to be strongly influenced by genomic context, both in terms of their immediate functional response and in the long-term evolution of their structure, we still have little understanding of how all of these factors interact within complex living systems. The goal of this project is to address these questions as part of a broad research framework using three specific experimental paradigms with the nematode Caenorhabditis elegans and its relatives as model systems: (1) How are complex regulatory systems structured and how does this structure determine their evolutionary dynamics?, (2) What are the drivers of genomic hyperdiversity and how can this diversity be used as a tool to understand the evolution of genetic systems?, and (3) How does the genomic landscape of variation, recombination and sexual reproduction influence the response to selection? These questions will be addressed using an innovative integration of approaches drawn from genomics, single-cell analysis, microfluidic engineering, high-throughput phenotyping, genetic transformation, and computational biology. This research uses a systems-genetics approach that integrates an understanding of natural genetic variation within a strong functional hypothesis-testing framework to understand the function and evolution of complex regulatory systems with critical implications for human health.

项目摘要 绝大多数人类个体对疾病的易感性是由复杂的 多个遗传位点与环境之间的相互作用，但我们仍然对 基因型和表型之间的图谱是如何构建的，或者这种结构如何影响对 环境和长期的进化变化。特别是，复杂的遗传网络应该产生 功能耦合使个体效应难以检验的性状间的多效性关系 使用传统的敲除方法。虽然这些网络的结构是众所周知的强烈 受基因组背景的影响，无论是在他们的即时功能反应，并在长期 尽管我们对它们的结构的演变，我们仍然很少了解所有这些因素如何在复杂的环境中相互作用， 生活系统这个项目的目标是解决这些问题作为一个广泛的研究框架的一部分 使用线虫秀丽隐杆线虫及其亲属的三种特定实验范式， 模型系统：（1）复杂的监管系统是如何构建的，这种结构如何决定 它们的进化动力(2)基因组高度多样性的驱动因素是什么？ 作为理解遗传系统进化的工具，以及（3）基因组景观是如何 变异、重组和有性繁殖影响选择反应？这些问题将 通过创新整合基因组学，单细胞分析， 微流体工程、高通量表型分析、遗传转化和计算生物学。这 研究使用系统遗传学方法，将对自然遗传变异的理解整合在 一个强大的功能假设测试框架，以了解复杂的功能和演变 对人类健康具有重大影响的监管制度。