Genetic Basis of Genotype-by-Environment Interactions Underlying Physiological Mo

生理学中基因型与环境相互作用的遗传基础

• 批准号: 8162018
• 负责人: Alison Motsinger-Reif
• 金额: $ 28.57万
• 依托单位: UNIVERSITY OF ALABAMA IN TUSCALOOSA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-05 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8162018
• 关键词: Alleles; Back; Biological Models; Carbohydrates; Cardiovascular Diseases; Chromosome Mapping; Collection; Communities; Complex; Complex Genetic Trait; Development; Diet; Disease; Drosophila genus; Drosophila melanogaster; Environment; Failure; Fatty acid glycerol esters; Frequencies; Gene Expression; Genes; Genetic; Genetic Complementation Test; Genetic Models; Genetic Variation; Genome; Genomics; Genotype; Goals; Heterozygote; Human; Inbreeding; Individual; Life Style; Link; Lipids; Maps; Measures; Metabolic Pathway; Metabolic syndrome; Microarray Analysis; Molecular Profiling; Non-Insulin-Dependent Diabetes Mellitus; North Carolina; Pathway interactions; Phenotype; Physiological; Population; Population Genetics; Population Sizes; Quantitative Trait Loci; RNA Interference; Recombinants; Resources; Robin bird; Sampling; Scheme; Site; Structure; Surveys; Symptoms; Testing; Time; Universities; Variant; Weight; Work; base; fly; follow-up; gene complementation; genetic variant; improved; metabolomics; research study; tool; trait

DESCRIPTION (provided by applicant): Diseases linked to Metabolic Syndrome (MetS) such at type-2 diabetes and cardiovascular disease are rapidly increasing due to the influences of a modern Westernized-life style, but the genetic, environmental, and physiological mechanisms linking the symptoms of Metabolic-syndrome remain to be elucidated. Large scale studies to systematically assess how genotype interacts with the environment to cause complex disease are very difficult in humans, but such studies are relatively tractable in genetic models systems such as Drosophila melanogaster. We have shown previously that that there is a very substantial contribution of genotype-by-environment interactions to the phenotypic variation observed for MetS-like symptoms in a naturally genetically variable population of D. melanogaster. We have also been able to demonstrate clear correlations between metabolomic and gene expression profiles and these symptoms as they vary across diet. Finally, we have shown that genetic variance in some of these traits increase with a perturbing high fat diet, indicating the exposure of cryptic genetic variation for these symptoms could contribute to increases in disease. In this study we will build off the community resources for complex genetic trait analysis of the Macdonald-Long synthetic recombinant inbred line (RIL) population and the Drosophila Genomic Reference Panel (DGRP) to map the genetic basis of genotype-by-diet interactions. First, using the 1700 Macdonald-Long Advanced Intercross synthetic RILs, we will map the genetic basis of MetS-like symptoms and the regions controlling genotype-by- environment interactions contributing to these symptoms to within 1 cM of the causal locus when the flies are raised on a "normal" verses "high fat" diet. We should be able to estimate both the effect size and population frequency of causative alleles. Second, based of the phenotypes measured in the F1 RIL population, 200 lines demonstrating the largest genotype-by-diet interaction effects will be selected for metabolomic and expression profiling. Metabolomic profiling will identify several hundred primary metabolite and whole genome expression profiles will be generated by microarray analysis. We will characterize the metabolomic and expression module structure that drives the genotype-by-environment interactions and link those pathways back to specific genetic variants. Finally, we will attempt to replicate the findings from the synthetic RIL population through association mapping in the natural variants represented in the 192 lines of the DGRP. The ultimate goal of this work is to identify genomic regions, metabolic pathways, physiological mechanisms, and dietary influences likely to be of importance to Metabolic Syndrome in humans. PUBLIC HEALTH RELEVANCE: Diseases linked to Metabolic Syndrome (MetS) such at type-2 diabetes and cardiovascular disease are rapidly increasing due to the influences of a modern Westernized-life style, but the genetic, environmental, and physiological mechanisms linking the symptoms of Metabolic-syndrome remain to be elucidated. Large scale studies to systematically assess how genotype interacts with the environment to cause complex disease are very difficult in humans, but such studies are relatively tractable in genetic models systems such as Drosophila melanogaster. The ultimate goal of this work is to identify genomic regions, metabolic pathways, physiological mechanisms, and dietary influences likely to be of importance to MetS in humans.

描述(申请人提供)：由于现代西化生活方式的影响，与代谢综合征(METS)相关的疾病如2型糖尿病和心血管疾病正在迅速增加，但与代谢综合征症状相关的遗传、环境和生理机制仍有待阐明。在人类身上，要系统地评估基因如何与环境相互作用导致复杂疾病的大规模研究是非常困难的，但在黑腹果蝇等遗传模型系统中，这样的研究相对容易。我们以前已经证明，在自然遗传可变的黑腹果蝇种群中，对观察到的甲硫氨酸样症状的表型变异有非常重要的贡献，即基因与环境的相互作用。我们还能够证明代谢和基因表达谱与这些症状之间的明显相关性，因为它们在不同的饮食中不同。最后，我们已经证明，随着令人不安的高脂肪饮食，这些特征中的一些性状的遗传变异会增加，这表明暴露于这些症状的神秘遗传变异可能会导致疾病的增加。在这项研究中，我们将建立社区资源，用于Macdonald-Long人工合成重组近交系(RIL)群体和果蝇基因组参考小组(DGRP)的复杂遗传特性分析，以绘制基因与饮食相互作用的遗传基础图。首先，使用1700 Macdonald-Long Advanced Intercross人工合成RILS，我们将绘制出当果蝇以“正常”与“高脂肪”饮食饲养时，蛋氨酸样症状的遗传基础以及控制导致这些症状的基因型与环境交互作用的区域到距离因果位置不到1厘米的地方。我们应该能够估计致病等位基因的效应大小和种群频率。其次，根据在F1 RIL群体中测量的表型，将选择200个表现出最大的基因型-饮食互作效应的品系进行代谢组和表达谱分析。代谢组分析将识别数百种主要代谢物，并将通过微阵列分析生成整个基因组表达谱。我们将描述驱动基因与环境相互作用的代谢和表达模块结构，并将这些途径与特定的遗传变异联系起来。最后，我们将试图通过在DGRP的192行中表示的自然变体中的关联图谱来复制来自合成RIL群体的发现。这项工作的最终目标是确定基因组区域、代谢途径、生理机制和饮食影响可能对人类代谢综合征具有重要意义。 公共卫生相关性：由于现代西化生活方式的影响，与代谢综合征(METS)相关的疾病，如2型糖尿病和心血管疾病，正在迅速增加，但与代谢综合征症状相关的遗传、环境和生理机制仍有待阐明。在人类身上，要系统地评估基因如何与环境相互作用导致复杂疾病的大规模研究是非常困难的，但在黑腹果蝇等遗传模型系统中，这样的研究相对容易。这项工作的最终目标是确定基因组区域、代谢途径、生理机制和饮食影响，这些可能对人类的Met具有重要意义。