Annotating genes of known and unknown function by large-scale coexpression analysis
Annotating genes of known and unknown function by large-scale coexpression analysis
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DOI：
10.1104/pp.108.117366
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发表时间：
2008-05-01
期刊：
影响因子：
7.4
通讯作者：
Girke, Thomas
中科院分区：
文献类型：
--
作者：
Horan, Kevin;Jang, Charles;Girke, Thomas
真核生物基因组中约40%的蛋白质是未知功能蛋白（PUFs）。它们的功能表征仍然是现代生物学的主要挑战之一。在这项研究中，我们确定了PUF编码基因从拟南芥（拟南芥）使用的序列相似性，基于结构域的组合，和经验的方法。对1，310个公开可用的Affytek芯片进行了大规模基因表达分析，以将鉴定的PUF基因与已知功能的调控网络和生物过程相关联。为了产生高质量的结果，该研究仅限于具有重复样品的表达集。首先，全基因组聚类和聚类的基因功能富集分析使我们能够将1，541个PUF基因与已知功能蛋白质（PKF）的紧密共表达基因相关联。其中超过70%可以被分配到比当前Gene Ontology版本中可用的更具体的生物过程注释。在所获得的集群中，最高度代表性的功能类别是核糖体组装，光合作用和细胞壁途径。有趣的是，大多数PUF基因似乎受到与大多数PKF基因相同的调控网络的控制，因为富含PUF基因的簇非常罕见。第二，大规模差异表达基因的分析，以确定一个全面的一套非生物胁迫反应基因。该分析导致269个PKF和104个PUF基因的鉴定，其响应于各种各样的非生物胁迫，而608个PKF和206个PUF基因主要响应于特定的胁迫处理。所提供的共表达和差异表达基因数据代表了指导未来PUF和PKF基因功能表征实验的重要资源。最后，公共植物基因表达数据库（http：//bioweb.ucr.edu/PED）的开发作为本项目的一部分，为本研究的大量基因表达数据提供有效的访问和挖掘工具。
About 40% of the proteins encoded in eukaryotic genomes are proteins of unknown function (PUFs). Their functional characterization remains one of the main challenges in modern biology. In this study we identified the PUF encoding genes from Arabidopsis ( Arabidopsis thaliana) using a combination of sequence similarity, domain-based, and empirical approaches. Large-scale gene expression analyses of 1,310 publicly available Affymetrix chips were performed to associate the identified PUF genes with regulatory networks and biological processes of known function. To generate quality results, the study was restricted to expression sets with replicated samples. First, genome-wide clustering and gene function enrichment analysis of clusters allowed us to associate 1,541 PUF genes with tightly coexpressed genes for proteins of known function (PKFs). Over 70% of them could be assigned to more specific biological process annotations than the ones available in the current Gene Ontology release. The most highly overrepresented functional categories in the obtained clusters were ribosome assembly, photosynthesis, and cell wall pathways. Interestingly, the majority of the PUF genes appeared to be controlled by the same regulatory networks as most PKF genes, because clusters enriched in PUF genes were extremely rare. Second, large-scale analysis of differentially expressed genes was applied to identify a comprehensive set of abiotic stress-response genes. This analysis resulted in the identification of 269 PKF and 104 PUF genes that responded to a wide variety of abiotic stresses, whereas 608 PKF and 206 PUF genes responded predominantly to specific stress treatments. The provided coexpression and differentially expressed gene data represent an important resource for guiding future functional characterization experiments of PUF and PKF genes. Finally, the public Plant Gene Expression Database (http://bioweb.ucr.edu/PED) was developed as part of this project to provide efficient access and mining tools for the vast gene expression data of this study.