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.

确定复杂性状变异的遗传基础是一个巨大的挑战。全基因组协会研究表明，许多具有小作用的等位基因可能是许多原因常见疾病。当等位基因效应分别很小时，这些等位基因的识别是艰巨的任务。突变可能不会在单个分子步骤中引起疾病，而是相互作用通过其他突变或通过中间分子途径级联反应最终导致在疾病特征中。确定疾病特征和疾病特征差异的网络和了解这些网络中的扰动如何影响表型可能更有效识别治疗靶标的方法。我们建议通过构建来测试这种方法 D. melanogaster和 d.simulans（求爱和运动）在标准条件下和乙醇期间分析暴露（环境扰动或疾病状态的模型）。通过超越在单个人群中的描述性研究，可预测的导致定向模型将确定新颖的条件，共享和特定的网络结构。网络做性别，物种或环境条件之间没有区别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最可能对生存或生育至关重要。调节单个基因或网络结构的变化突出了调节互动之间可能演变基因并确定可能有助于候选的多态性，基因和网络新型特征的演变，例如乙醇耐受性的提高。酒精依赖性影响美国约有1800万人影响健康和生活质量。乙醇具有对人类行为的严重影响，导致欣快和镇静。另外，醉酒可以提高侵略性，引起阳ot，并降低性抑制和运动能力。酒精和酒精中毒的风险具有强大而复杂的遗传成分，但也是由环境调节的。虽然有一些巨大的效应基因座（例如ADH， ALDH和GABA受体基因），许多遗传力仍然无法解释。果蝇对乙醇有类似的反应，并受到暴露影响的求爱和运动。我们将将果蝇遗传学的力量置于这个问题上，深入研究两个物种及其对乙醇的反应。我们将直接检验保守的假设网络对应于表型结果预测的更高程度的转换性跨物种。此外，我们将确定这些预测对基因的鲁棒性如何通过将两个种群暴露于乙醇中来影响环境。

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

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

DOI：
10.1101/pdb.prot074187
发表时间：
2013-09-01
期刊：
Cold Spring Harbor protocols
影响因子：
0
作者：
Dunham JP;Friesen ML
通讯作者：
Friesen ML

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

Threshold response to stochasticity in morphogenesis.

对形态发生随机性的阈值响应。