Evolving multigenic extensions to lifespan

进化多基因延长寿命

基本信息

批准号：
8895557
负责人：
Hang Lu
金额：
$ 21.55万
依托单位：
GEORGIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2017-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8895557
关键词：
Adverse drug effect Aging Animal Model Animals Architecture Automation Biological Biological Models Caenorhabditis elegans Code Collaborations Complex Complex Genetic Trait Coupled DNA Sequence Alteration Data Development Disease Drug Targeting Engineering Generations Genes Genetic Genetic Epistasis Genetic Screening Genetic Transcription Genome Genomics Goals Hereditary Disease Heritability Heterogeneity Human Image Image Analysis Individual Knowledge Life Longevity Measures MicroRNAs Microfluidic Microchips Microfluidics Molecular Mutagenesis Mutation Nematoda Noise Phenotype Physiological Population Preparation Process Quantitative Genetics Reagent Reporter Research Research Proposals Resources Risk Scheme Sorting - Cell Movement System Techniques Technology Tissues Variant Work base deep sequencing design directed evolution fluorescence imaging gene interaction genetic variant image processing imaging platform improved innovation interest juvenile animal mature animal mutant new technology next generation sequencing novel novel strategies pressure public health relevance quantitative imaging research study software systems system analysis (computer)tool trait young adult

项目摘要

DESCRIPTION: Most biological traits including common diseases have a strong but poorly understood genetic basis. There is general interest in identifying these genetic factors as they can be used to identify individuals that are at risk for a particular disease and as experimental handles to identify novel therapies. Despite an incredible outlay of resources, the majority of causative genetic variants remain unidentified due to the underlying complexity of the genetic architectures of most diseases. Fundamental study of complex genetic traits in model organisms should identify general principles and approaches that can be used to identify causative genetic variants in human traits. In this research proposal, we are developing an unprecedented system in C. elegans to generate multigenic states in model organisms by evolving fluorescent reporters of phenotypes of interest. We will develop an automated microfluidic, fluorescent imaging and computer analysis system to rapidly measure, segment, and describe the expression of a transcriptional reporter in a tissue-specific manner. We will then use this imaging/sorting system to apply selective pressure to evolve multigenic changes to expression over multiple generations. As proof of principal, we will apply this approach to a transcriptional reporter that predicts lifespan in younger animals to evolve longer-lived animals. Causative mutations can then be rapidly identified using next-generation sequencing and carefully studied in the context of known genetic and cellular networks. This work will improve our understanding of aging, and in general transform our approaches in model organisms towards the understanding of biological traits in complex genetic diseases.

描述：包括常见疾病在内的大多数生物学特征都有很强但知之甚少的遗传基础。人们普遍兴趣识别这些遗传因素，因为它们可以用来识别有特定疾病风险的人，并作为实验性手柄鉴定新疗法。尽管资源不可思议，但由于大多数疾病的遗传体系结构的潜在复杂性，大多数病因遗传变异仍然不明。模型生物中复杂遗传特征的基本研究应确定可用于鉴定人类特征中严重遗传变异的一般原理和方法。在这项研究建议中，我们正在秀丽隐杆线虫中开发一个前所未有的系统，以通过发展感兴趣的表型的荧光记者来在模型生物体中产生多基因态。我们将开发一个自动化的微流体，荧光成像和计算机分析系统，以快速测量，细分和描述转录报告基因以组织特异性方式的表达。然后，我们将使用此成像/排序系统施加选择性压力，以在多代的表达中发展多基因变化。作为本金的证明，我们将将这种方法应用于转录报告基因，该记者预测年轻动物的寿命以进化寿命更长的动物。然后，可以使用下一代测序快速识别致病突变，并在已知的遗传和细胞网络的背景下仔细研究。这项工作将提高我们对衰老的理解，并一般而言将我们在模型生物体中的方法转变为对复杂遗传疾病中生物学特征的理解。