Hypothesis generation for plant biology: enabling cyberinfrastructure and experimental validation

2000年模式生物拟南芥（Arabidopsis thaliana）基因组序列的发表是植物生物学的一个重大事件，并已被证明是植物研究许多不同领域的研究人员的宝贵资源。然而，在27,411个被预测的基因产物中，迄今为止只有约60%的功能被预测或通过实验确定。国际AtGenExpress项目提供了一套参考数据集，其中包括在不同条件和处理下收获的野生型和突变型植物材料的数千个基因表达数据集，以指导研究人员研究他们感兴趣的基因的潜在基因功能。最近出现了许多其他数据集（代谢组学、蛋白质组学、遗传变异、表观遗传学等），这些数据集也可用于假设生成/功能预测。大量收集拟南芥反向遗传学允许快速实验测试在硅产生的假设。为了充分利用这些植物生物学资源，并进一步发展它们在植物生物学中的应用，我在这项拨款申请中提出了一个信息学和生物学双管齐下的方法。首先，实验室里的植物研究人员，包括我的实验室，必须拥有可供他们使用的工具，以利用正在积累的大量信息。查询数据集和显示结果的用户友好界面是必须的。我的实验室已经在其受欢迎的生物阵列资源上提供了几个这样的工具，包括电子荧光象形文字（eFP）浏览器，用于在所有数据集中识别共表达基因的Expression Angler，以及用于识别共表达基因中的顺式元件的promer。其他用于假设生成的网络基础设施正在开发中，包括ePlant。我提出的研究的另一个方面将集中在使用反向遗传学，生物化学和分子生物学方法相结合的工具的实验验证上。

The publication of the genomic sequence of the model organism Arabidopsis thaliana in 2000 was a significant event in plant biology, and has proved to be a valuable resource to investigators in many different areas of plant research. Of the 27,411 predicted gene products, however, only ~60% have had their function predicted or identified experimentally to date. The international AtGenExpress effort has provided a reference set of thousands of gene expression data sets from both wild-type and mutant plant material harvested under diverse conditions and treatments to guide researchers towards potential gene functions for their genes of interest. Many other data sets have become available recently (metabolomic, proteomic, genetic variation, epigenetic etc.) and these can also be used for hypothesis generation/function prediction. Large collections for Arabidopsis reverse genetics allow rapid experimental testing of in silico-generated hypotheses. To fully take advantage of these plant biology resources and further their development for use in plant biology, I am proposing a two-pronged informatic and biology-based approach in this grant application. First, it is imperative that lab-based plant researchers, including my lab, have the tools at their disposal to make use of the enormous amount of information that is being accumulated. User-friendly interfaces for querying the data sets and displaying the results are a must. My lab has already made available several such tools at its popular Bio-Array Resource, including an electronic Fluorescent Pictograph (eFP) Browser, Expression Angler for identifying coexpressed genes across all data sets, and Promomer for identifying cis-elements in coexpressed genes. Other cyberinfrastructure for hypothesis generation is in development including an ePlant. The other aspect of my proposed research will focus on experimental validation of our tools using a combination of reverse genetics, biochemistry, and molecular biological methods.