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Quantitative Comparisons between genotypes and model species

基因型与模式物种之间的定量比较

基本信息

批准号：
8883575
负责人：
Lauren M. MCINTYRE
金额：
$ 29.38万
依托单位：
UNIVERSITY OF FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-17 至 2017-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8883575
关键词：
Affect Aggressive behavior Alcohol dependence Alcoholism Alcohols Alleles Allelic Imbalance Behavior Biological Assay Biological Models Complex Courtship Data Disease Drosophila genus Ecology Environment Equation Ethanol Euphoria Evolution Exposure to Female Fertility GABA Receptor Genes Genetic Genetic Polymorphism Genetic Variation Genotype Goals Head Health Heritability Human Impotence Individual Intoxication Locomotion Maps Measures Mediating Medical Genetics Methodology Modeling Molecular Mutation Nature Outcome Pathway interactions Phenotype Population Predictive Value Quality of life Receptor Gene Regulation Resolution Sedation procedure Structure System Testing Translating Ursidae Family Variant alcohol exposure alcohol response alcohol risk aldehyde dehydrogenases base design fascinate genome wide association study human disease improved indexing insight male men&apos s group novel predictive modeling sex skills species difference therapeutic target trait transcriptome sequencing vapor

项目摘要

Identifying the genetic basis of variation in complex traits is a grand challenge. Genome-wide association studies suggest that many alleles with small effects may be responsible for many common diseases. When allelic effects are individually small, identification of these alleles is a daunting task. A mutation may not cause disease in a single molecular step, but instead interact with other mutations or cascade through intermediate molecular pathways eventually resulting in disease traits. Identifying the networks which underlie variation in disease traits and understanding how perturbations in these networks affect phenotypes may be a more efficient approach to identifying therapeutic targets. We propose to test this approach by building predictive genotype to phenotype models for complex behaviors in D. melanogaster and D.simulans (courtship and locomotion) assayed under standard conditions and during ethanol exposure (a model for environmental perturbations or disease states). By moving beyond descriptive studies in single populations to causative directional models which are predictive in novel conditions, shared and specific network structures will be identified. Networks which do not differ between sexes, species or environmental conditions are good candidates for comparison to other model systems or to humans. Highly conserved regulatory relationships are most likely critical for viability or fertility. Divergence in the regulation of individual genes or changes in network structure highlight the possible evolution of regulatory interactions among genes and identify candidate polymorphisms, genes and networks which may contribute to the evolution of novel traits, such as increased ethanol tolerance. Alcohol dependency affects approximately 18 million people in the USA, impacting health and quality of life. Ethanol has severe effects on human behavior, resulting in euphoria and sedation. In addition, intoxication can increase aggression, cause impotence, and decrease sexual inhibition and locomotor skills. The effects of alcohol and risk for alcoholism have a strong and complex genetic component, but are also mediated by the environment. While there are some large effect loci (e.g. ADH, ALDH and GABA receptor genes), much of the heritability remains unexplained. Drosophila have similar responses to ethanol, with courtship and locomotion affected by exposure. We will bring the power of Drosophila genetics to bear on this problem with an in depth examination of two species and their response to ethanol. We will directly test the hypothesis that conserved networks correspond to a higher degree of translatability of prediction of phenotypic outcomes across species. In addition, we will determine how robust these predictions are to gene by environment effects by exposing both populations to ethanol.

识别复杂性状变异的遗传基础是一个巨大的挑战。全基因组关联研究表明，许多影响较小的等位基因可能会导致许多常见病。当等位基因的影响单独很小时，识别这些等位基因是一种艰巨的任务。突变可能不会在单个分子步骤中导致疾病，而是相互作用与其他突变或通过中间分子通路的级联最终导致在疾病特征上。确定疾病特征变异的基础网络和了解这些网络中的扰动如何影响表型可能是更有效的确定治疗靶点的方法。我们建议通过以下方式测试此方法：预测黑腹潜蝇复杂行为的表型模型的基因型别在标准条件下和乙醇条件下测定拟青霉的求偶和运动。暴露(环境扰动或疾病状态的模型)。通过超越单种群对致病方向模型的描述性研究将确定新的条件、共享和特定的网络结构。这样做的网络没有性别、物种或环境条件的差异是很好的候选人与其他模型系统或人类进行比较。高度保守的监管关系是很可能对生存能力或生育能力至关重要。个体基因或基因调控上的分歧网络结构的变化突显了监管相互作用的可能演变基因，并确定候选多态、基因和网络可能有助于新特征的进化，例如提高了对酒精的耐受性。酒精依赖影响美国约有1800万人，影响着健康和生活质量。乙醇有严重影响人的行为，导致兴奋和镇静。此外，醉酒会增加攻击性，导致阳萎，减少性抑制和运动技能。酒精的影响和酒精中毒的风险具有强大而复杂的遗传成分，但也受到环境的影响。虽然存在一些大的效应位点(例如，ADH， ALDH和GABA受体基因)，许多遗传性仍未解释。果蝇对酒精也有类似的反应，求爱和移动都会受到暴露的影响。我们会利用果蝇遗传学的力量来解决这个问题，并深入研究两个物种及其对乙醇的反应。我们将直接检验守恒的假设网络对应于表型结果预测的更高的可译性跨物种。此外，我们将通过以下方式确定这些预测的健壮性通过将两个种群都暴露在乙醇中而对环境产生影响。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

SHH Protein Variance in the Limb Bud Is Constrained by Feedback Regulation and Correlates with Altered Digit Patterning.

DOI：
10.1534/g3.116.033019
发表时间：
2017-03-10
期刊：
G3 (Bethesda, Md.)
影响因子：
0
作者：
Zhang R;Lee C;Lawson LY;Svete LJ;McIntyre LM;Harfe BD
通讯作者：
Harfe BD

Purification of transcripts and metabolites from Drosophila heads.

DOI：
10.3791/50245
发表时间：
2013-03-15
期刊：
Journal of visualized experiments : JoVE
影响因子：
0
作者：
Jensen K;Sanchez-Garcia J;Williams C;Khare S;Mathur K;Graze RM;Hahn DA;McIntyre LM;Rincon-Limas DE;Fernandez-Funez P
通讯作者：
Fernandez-Funez P

A cost-effective method for high-throughput construction of illumina sequencing libraries.