Hypothesis generation for plant biology: enabling cyberinfrastructure and experimental validation

2000年模式生物拟南芥基因组序列的发表是植物生物学中的一个重大事件，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个预测的基因产物中，迄今为止只有约60%的基因产物的功能得到了预测或实验鉴定。国际AtGenExpress的努力提供了一个参考集的数千个基因表达数据集，这些数据集来自在不同条件和处理下收获的野生型和突变体植物材料，以指导研究人员对其感兴趣的基因的潜在基因功能进行研究。许多其他的数据集最近已经变得可用（代谢组学，蛋白质组学，遗传变异，表观遗传学等）。并且这些也可以用于假设生成/函数预测。拟南芥反向遗传学的大集合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，并进一步发展其在植物生物学中的应用，我在这次拨款申请中提出了一个双管齐下的信息和生物学为基础的方法。首先，基于实验室的植物研究人员，包括我的实验室，必须拥有可供使用的工具，以利用正在积累的大量信息。用户友好的界面，查询数据集和显示结果是必须的。我的实验室已经在其流行的生物阵列资源中提供了几个这样的工具，包括电子荧光象形图（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顺式元件的Promomer。用于生成假设的其他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我们的工具的实验验证，使用反向遗传学，生物化学和分子生物学方法的组合。

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.