Microarray Analysis of Olfactory Receptor Expression

描述（由申请人提供）：嗅觉受体（OR）占小鼠基因组的近2%，反映了超过1200个个体基因。这个惊人的数字既代表了一个实验机会，也代表了一个技术挑战。在单个组织中表达的如此大量的基因之间的比较研究可以提供从受体-配体结构-功能关系到刺激编码策略到基因表达调控的问题的见解。然而，与超过1000个基因的家族一起工作的技术要求超出了分子生物学和生理学的大多数标准实践。全基因组测序和高密度微阵列基因表达测定的出现是这些障碍的可行解决方案，并且可以提供重要的前端数据，其可以通过标准的低通量技术进一步追求。此外，这些高通量技术本身通常可以产生信息丰富的数据和新的见解。在这里，我们建议将我们的生物信息学为基础的数据挖掘工作扩展到动态功能的研究与一个新的定制设计的高密度微阵列，使我们能够同时监测所有嗅觉受体（OR）基因的表达水平。这将使我们能够将整个基因组的生物信息学工作扩展到动态基因表达和调控的评价。

DESCRIPTION (provided by applicant): Olfactory receptors (ORs) represent nearly 2% of the mouse genome, reflecting something over 1200 individual genes. This remarkable number represents both an experimental opportunity and a technical challenge. Comparative studies among such a large number of genes expressed in a single tissue can offer insights in questions ranging from receptor-ligand structure-function relations to stimulus coding strategies to regulation of gene expression. However the technical demands of working with a family of over 1000 genes are beyond most standard practices of molecular biology and physiology. The advent of whole genome sequencing and high density microarray gene expression assays are a viable solution to these obstacles, and can provide important front end data that can be pursued further by standard, low throughput techniques. Additionally these high throughput techniques can themselves often produce informative data and new insights. Here we propose to extend our bioinformatics based data mining efforts into dynamic functional studies with a new custom-designed high density microarray that will allow us to monitor expression levels of all olfactory receptor (OR) genes simultaneously. This will allow us to extend the bioinformatics work on the whole genome to an appreciation of dynamic gene expression and regulation.