A Resource for the Genetic Dissection of Complex Traits

复杂性状遗传解析的资源

• 批准号: 10564298
• 负责人: ANTHONY Douglas LONG
• 金额: $ 62.56万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10564298
• 关键词: Alleles; Animals; Architecture; Biological Models; Biology; Cell Differentiation process; Cell physiology; Collection; Communities; Complement; Complex; Computer software; Consensus; Control Animal; DNA Transposable Elements; Data; Data Set; Diagnostic; Disease; Dissection; Drosophila genus; Equilibrium; Event; Experimental Designs; Fat Body; Frequencies; Future; Gene Expression; Gene Frequency; Generations; Genes; Genetic; Genetic Diseases; Genetic Models; Genome; Genomic Segment; Genotype; Goals; Haplotypes; Health; Heterogeneity; Human; Immune response; Immunologics; Inbreeding; Individual; Infection; Learning; Link; Maps; Mediating; Memory; Mendelian disorder; Mental Depression; Methods; Modeling; Molecular; Movement; Mutation; Nature; Pharmaceutical Preparations; Phenotype; Population; Process; Quantitative Trait Loci; Reaction; Recombinants; Recurrence; Regulation; Regulator Genes; Research; Research Personnel; Resolution; Resources; Sampling; Site; Structure; System; Techniques; Testing; Therapeutic; Time; Tissues; Toxic effect; Update; Validation; Variant; Vial device; Xenobiotics; analytical method; causal variant; cohort; data visualization; design; empowerment; experimental study; flexibility; fly; genetic resource; genetic variant; genome resource; genome sequencing; genome wide association study; human disease; improved; insight; life history; model organism; mosaic; multidimensional data; novel; novel strategies; pathogen; predictive modeling; rare variant; response; segregation; tool; trait; transcriptome sequencing; usability; user-friendly; whole genome

PROJECT SUMMARY A large, diverse set of common human diseases, and most of the biomedically-relevant traits that model organism biologists routinely target, are complex and polygenic. Population variation in these traits has a sizeable genetic component, and dissecting this variation can yield improved diagnostics and therapeutics, and enable detailed descriptions of the molecular and cellular processes underlying disease and trait variation. Genomewide association studies (GWAS) are largely responsible for dramatic progress in the analysis of human complex traits in recent years. GWAS have linked many genes to variation in human health, and imply a significant fraction of trait variation is controlled by thousands of tiny-effect, primarily regulatory sites spread along the genome. Despite this critical insight, there remain many gaps in our understanding of the nature of causative loci. One notable caveat of the GWAS approach is its inherent bias towards intermediate- frequency alleles; GWAS are ill-suited to uncovering rare alleles of large effect and genes harboring several individually-rare mutations, events that mutation-selection balance models predict contribute to trait variation. The dissection of complex traits in model organisms offers great experimental flexibility, and the opportunity to deploy methods synergistic with the dominant GWAS paradigm, yielding a more complete picture of the genetic basis of trait variation. With this in mind we established the DSPR (Drosophila Synthetic Population Resource) as a shareable toolkit for complex trait analysis in flies. The set of 1600 DSPR strains were derived from 15 highly-characterized founder genotypes, and represent the most extensive multiparental population (MPP) available in animals. The DSPR is used by many research groups, has enabled the identification of thousands of QTL, and has associated rare alleles with trait variation. The DSPR complements GWAS approaches for uncovering the full spectrum of allelic variation contributing to complex traits. In Aim 1 we will validate and refine the genotypes of all DSPR strains, strengthening the living resource we will continue to share with the Drosophila community, and enhance the usability of the collection by integrating analytical routines into the powerful R/qtl2 software platform. In Aim 2 we will extend the DSPR, and enable extreme QTL (or X-QTL) mapping. For many traits, an efficient and user-friendly strategy to identify QTL is to compare allele frequencies in phenotypically-extreme recombinant populations to those in control cohorts. We will derive such mixed DSPR populations, experimentally refine our approach, and distribute populations and software to facilitate novel, investigator-driven research. In Aim 3 we will broaden the utility of the DSPR to explore the nature of expression regulation. Using a host-pathogen model, we will exploit the rapid regulatory change that occurs during the immune response to develop dynamic eQTL mapping methods, finding loci that contribute to variation in the trajectory of the regulatory reaction. These general resources will allow researchers employing any MPP to move beyond static pictures of gene expression in populations.

项目概要 大量不同的常见人类疾病，以及模拟的大多数生物医学相关特征 生物体生物学家通常关注的目标是复杂的和多基因的。这些特征的群体变异 相当大的遗传成分，剖析这种变异可以改进诊断和治疗，并且 能够详细描述疾病和性状变异背后的分子和细胞过程。 全基因组关联研究 (GWAS) 在分析中取得巨大进展 近年来人类复杂特征的研究。 GWAS 已将许多基因与人类健康的变异联系起来，并且 意味着性状变异的很大一部分是由数千个微小效应（主要是调控位点）控制的 沿着基因组传播。尽管有这一批判性的见解，但我们对这一问题的理解仍然存在许多差距。 致病位点的性质。 GWAS 方法的一个值得注意的警告是其固有的偏向中间- 频率等位基因； GWAS 不适合发现具有大效应的罕见等位基因和含有多种基因的基因 个体罕见的突变，突变选择平衡模型预测的事件会导致性状变异。 对模式生物复杂性状的剖析提供了极大的实验灵活性，并且 有机会部署与占主导地位的 GWAS 范例协同的方法，从而产生更完整的结果 性状变异的遗传基础的图片。考虑到这一点，我们建立了 DSPR（果蝇合成 Population Resource）作为果蝇复杂性状分析的可共享工具包。 1600 个 DSPR 菌株组 源自 15 个高度特征化的创始人基因型，代表了最广泛的多亲本 动物中可用的种群（MPP）。 DSPR 被许多研究小组使用，使得 鉴定了数千个 QTL，并将稀有等位基因与性状变异相关联。 DSPR 的补充 GWAS 方法用于揭示导致复杂性状的全谱等位基因变异。 在目标 1 中，我们将验证和完善所有 DSPR 菌株的基因型，加强生物资源 我们将继续与果蝇社区分享，并通过以下方式增强集合的可用性 将分析例程集成到强大的 R/qtl2 软件平台中。在目标 2 中，我们将扩展 DSPR，并且 启用极端 QTL（或 X-QTL）作图。对于许多性状，有一种有效且用户友好的策略来识别 QTL是将表型极端重组群体中的等位基因频率与对照群体中的等位基因频率进行比较 队列。我们将导出这种混合 DSPR 群体，通过实验改进我们的方法，并分发 人口和软件以促进新颖的、研究者驱动的研究。在目标 3 中，我们将扩大 DSPR 探索表达调控的本质。使用宿主-病原体模型，我们将利用 免疫反应过程中发生的快速调节变化，以开发动态 eQTL 作图方法， 寻找导致调节反应轨迹变化的基因座。这些通用资源将 允许研究人员使用任何 MPP 超越人群中基因表达的静态图片。