High throughput imaging and quantitative phenotyping for behavioural genomics

行为基因组学的高通量成像和定量表型分析

• 批准号: 1810437
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1810437
• 关键词: throughput; imaging; quantitative; phenotyping; behavioural

Many behavioural traits, including those underlying psychiatric disorders, are heritable, but identifying the associated genes remains challenging. With the rapid development of genome sequencing technology, the bottleneck is no longer knowledge of gene variants, but an insufficient description of their impact on phenotype. Advances in imaging, computer vision, and machine learning are now converging and will make it possible to perform automatic and quantitative phenotyping at a scale commensurate with genomics. We are taking a combined experimental and computational approach using the nematode worm C. elegans as a model that will reveal genes and gene networks that control behaviour that have been missed in manual screens.Students in the lab will have the opportunity to use cutting edge imaging and analysis methods to pursue their interests in behavioural genomics and/or to contribute to the development of the next generation of phenotyping technology. There is an emphasis on discovering the molecular mechanisms of nervous system function through novel analyses of behaviours including spontaneous locomotion, feeding, collective behaviour, and decision making. Students will also have the opportunity to develop skills in molecular biology, microscopy, and/or quantitative genetics.

许多行为特征，包括那些潜在的精神疾病，是可遗传的，但识别相关基因仍然具有挑战性。随着基因组测序技术的快速发展，瓶颈不再是基因变异的知识，而是对其对表型影响的描述不足。成像、计算机视觉和机器学习的进步正在融合，这将使在与基因组学相称的规模上执行自动和定量表型分析成为可能。我们正在采用实验和计算相结合的方法，以线虫C. elegans为模型，揭示人工筛选中遗漏的控制行为的基因和基因网络。实验室的学生将有机会使用尖端的成像和分析方法来追求他们在行为基因组学方面的兴趣和/或为下一代表型技术的发展做出贡献。重点是通过对自发运动、进食、集体行为和决策等行为的新颖分析，发现神经系统功能的分子机制。学生还将有机会发展分子生物学、显微镜和/或定量遗传学方面的技能。