Machine vision analysis of C.elegans phenotypic patterns

描述(申请人提供)：线虫具有强大的遗传学，描述良好的神经系统，以及完整的基因组序列；因此，它非常适合在分子和细胞水平上分析行为和发育。特别是，能够从功能上将特定基因的影响映射到特定的行为后果，这使得使用基因分析来从功能上剖析神经系统功能鲜为人知的方面背后的分子机制成为可能。然而，许多在神经元功能中起关键作用的基因对行为的影响对普通观察者来说似乎非常微妙或难以准确描述。因此，为了充分发挥线虫在神经系统功能遗传分析中的潜力，有必要开发复杂的方法来快速和一致地定量检测突变表型，特别是与行为相关的突变表型。 这项拟议工作的目标是开发计算机视觉工具，以定量描述线虫突变或药物治疗引起的表型模式。通过使精确地表征具有异常运动或排卵的突变体的行为表型成为可能，这些工具将特别有助于将特定的神经传递缺陷与特征的行为模式相关联。这些分析工具还将用于生成一个全面的数据库，其中包含一大组突变菌株的复杂行为数据。这个数据库将使识别对行为或发育有类似影响的突变体和药物治疗组成为可能。随着已知突变的表型数据的积累，最终应该可以记录未知突变或药物治疗的动物，并对未表征基因的功能和未表征药物的靶标做出知情的初始假设。

DESCRIPTION (provided by applicant): The nematode C. elegans has powerful genetics, a well-described nervous system, and a complete genome sequence; thus, it is well suited to analysis of behavior and development at the molecular and cellular levels. In particular, the ability to functionally map the influence of particular genes to specific behavioral consequences makes it possible to use genetic analysis to functionally dissect the molecular mechanisms underlying poorly understood aspects of nervous system function. However, many genes with critical roles in neuronal function have effects on behavior that to a casual observer appear very subtle or difficult to describe precisely. Therefore, to fully realize the potential of C. elegans for the genetic analysis of nervous system function, it is necessary to develop sophisticated methods for the rapid and consistent quantitation of mutant phenotypes, especially those related to behavior. The goal of this proposed work is to develop computer vision tools for quantitatively characterizing the phenotypic patterns caused by mutations or pharmacological treatments in C. elegans. By making it possible to precisely characterize the behavioral phenotypes of mutants with abnormal locomotion or egglaying, these tools will be particularly useful for correlating specific neurotransmission defects with characteristic behavioral patterns. These analytical tools will also be used to generate a comprehensive database containing complex behavioral data on a large set of mutant strains. This database will make it possible to identify groups of mutants and pharmacological treatments that have similar effects on behavior or development. With the accumulation of increasing phenotypic data on known mutants, it should ultimately be possible to record from unknown mutant or drug-treated animals and make informed initial hypotheses about the functions of uncharacterized genes and the targets of uncharacterized drugs.