Reverse Engineering Quantitative Genetic Variation

逆向工程定量遗传变异

基本信息

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
项目类别：
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

项目摘要

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.

项目概要大多数人类疾病的风险归因于许多相互作用基因的等位基因与环境敏感效应的未来发展需要个性化精准医疗。预测性了解 DNA 序列变异如何通过调节引起表型变异这在人类群体中具有挑战性，因为变异与复杂性状嵌入相对较大的局部连锁不平衡（LD）块中，其中分离的分子多态性不是独立的，因此，这些变异不一定是因果关系。但可能与同一 LD 块内真正常见或罕见的因果变异处于 LD 中。此外，大多数与复杂性状相关的变异位于基因间区域，编码的上游或下游这些变异可能是调节性的并影响基因表达的变异。正式证明分子遗传变异、基因遗传变异之间的因果关系表达和其他中间分子表型，以及数量性状表型的遗传变异果蝇遗传参考面板 (DGRP) 是不可能的。在我们的实验室中产生，由 205 个来自单次授精的近交、测序品系组成从北卡罗来纳州罗利农贸市场收集的雌性我们使用 DGRP 进行全基因组分析。许多生物数量性状以及全基因组基因表达的关联（GWA）图谱，它产生了关于基因型-表型图的可检验的假设，包括性别、遗传 DGRP 中的 GWA 映射的精度非常出色。由于 LD 随物理距离的局部快速下降，我们建议使用这些假设来检验。 CRISPR/Cas9 介导精确的等位基因替换，以在功能上验证 (1) 加性、上位性和 (2) 多效性、上位性和罕见变异的环境特异性影响；以及（3）新的转录区域（NTR）和顺反式转录网络，并评估它们对全基因组表达和数量性状的影响。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，基因和基因间区域，在男性和女性之间共享和不同，都尊重我们将能够了解生物数量性状表型以及全基因组基因表达。明确评估生物表型和基因上位相互作用的存在和程度表达特征并创建“设计者”基因型，在定义的遗传中上位等位基因之间相互作用这些研究将极大地增进我们对自然发生的分子的微妙程度的理解。变异影响基因表达和生物表型。