Reverse Engineering Quantitative Genetic Variation

逆向工程定量遗传变异

• 批准号: 9915941
• 负责人: Robert R. H Anholt
• 金额: $ 45.39万
• 依托单位: CLEMSON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-23 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9915941
• 关键词: Affect; Agriculture; Alleles; Animals; Behavior Disorders; Behavioral; Biological Models; Biology; Breeding; CRISPR/Cas technology; Chills; Code; Coma; Complex; Controlled Environment; DNA Sequence; DNA Shuffling; Development; Disease; Drosophila melanogaster; Engineering; Environment; Exhibits; Female; Future; Gene Expression; Genes; Genetic; Genetic Polymorphism; Genetic Transcription; Genetic Variation; Genotype; Goals; Human; Human Biology; Inbreeding; Individual; Intercistronic Region; Introns; Laboratories; Linkage Disequilibrium; Maps; Mediating; Medicine; Molecular; Molecular Genetics; Morphology; Pharmacology; Phenotype; Physiological; Plants; Population; Positioning Attribute; Predisposition; Quantitative Genetics; Quantitative Trait Loci; Recovery; Regulator Genes; Risk; Sampling; Stream; Stress; System; Technology; Testing; Time; Variant; causal variant; farmers markets; fitness; genetic approach; genetic architecture; genetic variant; genome wide association study; genome-wide; human disease; life history; male; molecular phenotype; nervous system development; novel; pleiotropism; precision medicine; rare variant; response; sex; trait

PROJECT SUMMARY Risk for most human diseases is attributable to segregating alleles at many interacting genes with environmentally sensitive effects. Future developments towards personalized precision medicine require a predictive understanding of how DNA sequence variants give rise to phenotypic variation through modulation of regulatory gene networks. This is challenging in human populations because variants associated with complex traits are embedded in relatively large local linkage disequilibrium (LD) blocks, within which segregating molecular polymorphisms are not independent. Thus, these variants are not necessarily causal, but could be in LD with the true common or rare causal variant(s) within the same LD block. Furthermore, the majority of variants associated with complex traits are in intergenic regions, up- or down-stream of coding regions, or in introns. These variants are presumably regulatory and affect variation in gene expression. Formally proving the causal relationships between molecular genetic variation, genetic variation in gene expression and other intermediate molecular phenotypes, and genetic variation in quantitative trait phenotypes is not possible in human populations. The Drosophila melanogaster Genetic Reference Panel (DGRP) was generated in our laboratories and consists of 205 inbred, sequenced lines derived from single inseminated females collected from the Raleigh, NC Farmer’s Market. We have used the DGRP to perform genome wide association (GWA) mapping for many organismal quantitative traits as well as genome wide gene expression, which has generated testable hypotheses about the genotype-phenotype map, including sex-, genetic background- and environment-specific effects. The precision of GWA mapping in the DGRP is excellent because of rapid local decline of LD with physical distance. Here, we propose to test these hypotheses using CRISPR/Cas9 mediated precise allelic replacement to functionally validate (1) additive, epistatic and environment-specific effects of common variants that affect chill coma recovery time; (2) pleiotropic, epistatic and environment-specific effects of rare variants; and (3) novel transcribed regions (NTRs) and cis-trans transcriptional networks, and evaluate their effects on genome-wide expression and quantitative traits. These proposed studies will enable us to evaluate the direct and pleiotropic effects of common and rare variants, in both genic and intergenic regions, that are shared and distinct between males and females, both with respect to organismal quantitative trait phenotypes as well as genome wide gene expression. We will be able to explicitly evaluate the existence and magnitude of epistatic interactions for organismal phenotypes and gene expression traits and create “designer” genotypes between epistatically interacting alleles in defined genetic backgrounds. These studies will greatly advance our understanding of how subtle naturally occurring molecular variation impacts gene expression and organismal phenotypes.

项目总结 大多数人类疾病的风险可归因于在许多相互作用的基因上分离等位基因 对环境敏感的影响。未来个性化精准医疗的发展需要 对DNA序列变异如何通过调节引起表型变异的预测性理解 调控基因网络。这在人类群体中是具有挑战性的，因为与 复杂的性状被嵌入到相对较大的局部连锁不平衡(LD)块中，其中 分离的分子多态不是独立的。因此，这些变体不一定是因果的， 但可能与真正常见或罕见的因果变异(S)在同一LD区块内。此外， 大多数与复杂性状相关的变异位于基因间区，即编码的上游或下游 区域，或内含子。这些变异可能是调节性的，并影响基因表达的变异。 形式化证明分子遗传变异、基因遗传变异之间的因果关系 数量性状表型的表达和其他中间分子表型及遗传变异 在人类群体中是不可能的。果蝇黑腹果蝇遗传参考小组(DGRP)是 在我们的实验室中产生，由205个近交系组成，测序系来自单次受精 从北卡罗来纳州罗利农贸市场收集的雌性动物。我们已经使用DGRP进行了全基因组分析 许多生物数量性状的关联(GWA)作图以及基因组范围的基因表达， 它已经产生了关于基因-表型图谱的可测试的假设，包括性别-遗传 特定于背景和环境的效果。DGRP中的GWA制图精度很高 这是因为Ld随物理距离的局部快速下降。在这里，我们建议使用以下方法来检验这些假设 CRISPR/Cas9介导的精确等位基因替换功能验证(1)加性、上位性和 影响冷昏迷恢复时间的常见变种对环境的特定影响；(2)多效性，上位性 稀有变异的环境特异性效应；以及(3)新的转录区域(NTR)和顺式反式 转录网络，并评估它们对全基因组表达和数量性状的影响。这些 拟议的研究将使我们能够评估常见和罕见变异的直接和多效性影响，在 基因和基因间隔区，在男性和女性之间共享和区别，两者都是尊重的 到生物数量性状表型以及全基因组的基因表达。我们将能够 明确评估生物表型和基因的上位性交互作用的存在和大小 在已定义的基因中，在上位性互作等位基因之间表达性状并创造“设计型”基因型 背景。这些研究将极大地促进我们对微妙的自然发生的分子的理解 变异会影响基因表达和生物表型。