Meta-Analysis of Gene Expression Signatures Reveals Hidden Links among Diverse Biological Processes in Arabidopsis

The model plant Arabidopsis has been well-studied using high-throughput genomics technologies, which usually generate lists of differentially expressed genes under various conditions. Our group recently collected 1065 gene lists from 397 gene expression studies as a knowledgebase for pathway analysis. Here we systematically analyzed these gene lists by computing overlaps in all-vs.-all comparisons. We identified 16,261 statistically significant overlaps, represented by an undirected network in which nodes correspond to gene lists and edges indicate significant overlaps. The network highlights the correlation across the gene expression signatures of the diverse biological processes. We also partitioned the main network into 20 sub-networks, representing groups of highly similar expression signatures. These are common sets of genes that were co-regulated under different treatments or conditions and are often related to specific biological themes. Overall, our result suggests that diverse gene expression signatures are highly interconnected in a modular fashion.模式植物拟南芥（Arabidopsis）已通过高通量基因组学技术得到了充分研究，这类技术通常可在不同实验条件下生成差异表达基因列表。本研究团队近期从397项基因表达研究中收集了1065个基因列表，以此构建用于通路分析的知识库。本研究通过全对全比对计算基因列表间的重叠情况，对这些基因列表进行了系统性分析。本研究共鉴定出16261个具有统计学显著性的基因列表重叠关系，并将其构建为无向网络：其中节点代表基因列表，边则代表存在显著性重叠。该网络清晰展现了不同生物学过程的基因表达特征之间的相关性。本研究还将主网络划分为20个子网络，每个子网络对应一组高度相似的基因表达特征。这些子网络中的基因集合在不同处理或实验条件下呈现共调控特征，且通常与特定的生物学主题相关。综上，本研究结果表明，多样的基因表达特征以模块化的方式高度相互关联。