Mähler Niklas, Cheregi Otilia, Funk Christiane, Netotea Sergiu, Hvidsten Torgeir R
Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
Department of Chemistry, Umeå University, Umeå, Sweden.
PLoS One. 2014 Nov 24;9(11):e113496. doi: 10.1371/journal.pone.0113496. eCollection 2014.
Despite being a highly studied model organism, most genes of the cyanobacterium Synechocystis sp. PCC 6803 encode proteins with completely unknown function. To facilitate studies of gene regulation in Synechocystis, we have developed Synergy (http://synergy.plantgenie.org), a web application integrating co-expression networks and regulatory motif analysis. Co-expression networks were inferred from publicly available microarray experiments, while regulatory motifs were identified using a phylogenetic footprinting approach. Automatically discovered motifs were shown to be enriched in the network neighborhoods of regulatory proteins much more often than in the neighborhoods of non-regulatory genes, showing that the data provide a sound starting point for studying gene regulation in Synechocystis. Concordantly, we provide several case studies demonstrating that Synergy can be used to find biologically relevant regulatory mechanisms in Synechocystis. Synergy can be used to interactively perform analyses such as gene/motif search, network visualization and motif/function enrichment. Considering the importance of Synechocystis for photosynthesis and biofuel research, we believe that Synergy will become a valuable resource to the research community.
尽管集胞藻PCC 6803是一种经过深入研究的模式生物，但该蓝藻的大多数基因编码的蛋白质功能完全未知。为了便于对集胞藻中的基因调控进行研究，我们开发了Synergy（http://synergy.plantgenie.org），这是一个整合了共表达网络和调控基序分析的网络应用程序。共表达网络是从公开的微阵列实验中推断出来的，而调控基序则使用系统发育足迹法进行识别。结果表明，自动发现的基序在调控蛋白的网络邻域中比在非调控基因的邻域中富集的频率要高得多，这表明这些数据为研究集胞藻中的基因调控提供了一个可靠的起点。同样，我们提供了几个案例研究，证明Synergy可用于在集胞藻中找到生物学上相关的调控机制。Synergy可用于交互式地执行诸如基因/基序搜索、网络可视化和基序/功能富集等分析。考虑到集胞藻在光合作用和生物燃料研究中的重要性，我们相信Synergy将成为研究界的宝贵资源。
