Automated platform for high-throughput genetic analyses in C. elegans

用于线虫高通量遗传分析的自动化平台

基本信息

批准号：
10382437
负责人：
Christopher Fang-Yen
金额：
$ 37.4万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-15 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10382437
关键词：
Adopted Adult Aging Alleles Anatomy Animal Model Animals Apoptosis Automation Behavioral Benchmarking Biological Models Biological Phenomena Biology Caenorhabditis elegans Cell Death Cell Lineage Communities Computer software Consumption Custom Development Drug Screening Generations Genes Genetic Genetic Crosses Genetic Models Genetic Screening Goals Image Individual Language Mammals Manuals Maps Measurement Measures Methods Microfluidics Molecular Monitor Movement Nematoda Nervous system structure Neurobiology Optics Other Genetics Phenotype Physiology Population Procedures Process Productivity Protocols documentation RNA Interference Research Research Personnel Robot Robotics Running Sleep Study models System Techniques Technology Testing Time Transgenes Visual Work arm axon guidance base cost design experimental study flexibility gene discovery genetic analysis genetic manipulation genome sequencing graphical user interface loss of function machine vision mobile computing mutant open source operation optogenetics real-time images robotic system success tool whole genome

项目摘要

PROJECT SUMMARY The roundworm C. elegans is one of the most widely studied and powerful genetic model organisms in biology. Many experiments in C. elegans genetics require time-consuming and low throughput manual procedures. For example, the forward genetic screen, through which genes influencing a phenotype are found by identification of mutants, often involves assessment of tens of thousands of individual animals. Full exploitation of C. elegans as a model system will benefit tremendously from automation. We will develop automated methods for performing genetic screens and many other tasks routinely done in C. elegans labs. The key components of the system will be a moving-camera machine vision system for monitoring individual worms on various substrates, and a robotic arm capable of transferring individual worms from one plate to another. To test and refine our methods, we will apply our automation system to perform a saturation genetic screen for modifiers of developmentally-timed sleep, which has molecular and behavioral similarities to sleep in mammals.

项目概要线虫是世界上研究最广泛、最强大的遗传模型生物之一。生物学。线虫遗传学的许多实验需要耗时且低通量的手动操作程序。例如，正向遗传筛选，通过它发现影响表型的基因通过识别突变体，通常需要对数以万计的个体动物进行评估。满的利用线虫作为模型系统将极大地受益于自动化。我们将开发用于执行遗传筛选和线虫实验室中常规完成的许多其他任务的自动化方法。该系统的关键组件将是一个移动摄像机机器视觉系统，用于监控个人各种基质上的蠕虫，以及能够将单个蠕虫从一个盘子转移到一个机器人手臂其他。为了测试和完善我们的方法，我们将应用我们的自动化系统来执行饱和遗传筛选发育定时睡眠的修饰因子，其与睡眠在分子和行为上相似哺乳动物。