Genevestigator transcriptome meta-analysis and biomarker search using rice and barley gene expression databases
Genevestigator transcriptome meta-analysis and biomarker search using rice and barley gene expression databases
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DOI：
10.1093/mp/ssn048
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发表时间：
2008-09-01
期刊：
影响因子：
27.5
通讯作者：
Gruissem, Wilhelm
中科院分区：
文献类型：
--
作者：
Zimmermann, Philip;Laule, Oliver;Gruissem, Wilhelm
广泛使用微阵列技术来研究植物转录组已经导致了重要的发现和覆盖广泛的不同组织，发育阶段，扰动和基因型的分析数据的积累。查询大量的微阵列实验可以提供通过分析单个实验无法获得的见解。然而，这样的荟萃分析在数据可比性和标准化、系统的样本注释和分析工具方面提出了重大挑战。Genevestigator使用一个大型的精选表达数据库和一套专门开发的分析工具来解决这些问题，这些工具可以通过互联网访问。基于大量的拟南芥数据，这种组合已经被证明在植物研究领域是有用的（Grennan，2006）。在这里，我们提出了Genevestigator水稻和大麦基因表达数据库，其中包含质量控制和良好的注释使用本体的微阵列实验的释放。数据库目前包括病理学、植物营养、非生物胁迫、激素处理、基因型和空间或时间分析等实验，但随着更多实验数据的出现，预计将涵盖广泛的研究领域。模式物种水稻和大麦的转录组荟萃分析预计将提供可用于谷物功能基因组学和生物技术应用的结果。
The wide-spread use of microarray technologies to study plant transcriptomes has led to important discoveries and to an accumulation of profiling data covering a wide range of different tissues, developmental stages, perturbations, and genotypes. Querying a large number of microarray experiments can provide insights that cannot be gained by analyzing single experiments. However, such a meta-analysis poses significant challenges with respect to data comparability and normalization, systematic sample annotation, and analysis tools. Genevestigator addresses these issues using a large curated expression database and a set of specifically developed analysis tools that are accessible over the internet. This combination has already proven to be useful in the area of plant research based on a large set of Arabidopsis data (Grennan, 2006). Here, we present the release of the Genevestigator rice and barley gene expression databases that contain quality-controlled and well annotated microarray experiments using ontologies. The databases currently comprise experiments from pathology, plant nutrition, abiotic stress, hormone treatment, genotype, and spatial or temporal analysis, but are expected to cover a broad variety of research areas as more experimental data become available. The transcriptome meta-analysis of the model species rice and barley is expected to deliver results that can be used for functional genomics and biotechnological applications in cereals.