Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

Release of bud dormancy in perennial woody plants is a temperature-dependent process and thus flowering in these species is heavily affected by climate change. The lack of cold winters in temperate growing regions often results in reduced flowering and low fruit yields. This is likely to decrease the availability of fruits and nuts of the Prunus spp. in the near future. In order to maintain high yields, it is crucial to gain detailed knowledge on the molecular mechanisms controlling the release of bud dormancy. Here, we studied these mechanisms using sweet cherry (Prunus avium L.), a crop where the agrochemical hydrogen cyanamide (HC) is routinely used to compensate for the lack of cold winter temperatures and to induce flower opening. In this work, dormant flower buds were sprayed with hydrogen cyanamide followed by deep RNA sequencing, identifying three main expression patterns in response to HC. These transcript level results were validated by quantitative real time polymerase chain reaction and supported further by phytohormone profiling (ABA, SA, IAA, CK, ethylene, JA). Using these approaches, we identified the most up-regulated pathways: the cytokinin pathway, as well as the jasmonate and the hydrogen cyanide pathway. Our results strongly suggest an inductive effect of these metabolites in bud dormancy release and provide a stepping stone for the characterization of key genes in bud dormancy release.

BackgroundOver the last decade network enrichment analysis has become popular in computational systems biology to elucidate aberrant network modules. Traditionally, these approaches focus on combining gene expression data with protein-protein interaction (PPI) networks. Nowadays, the so-called omics technologies allow for inclusion of many more data sets, e.g. protein phosphorylation or epigenetic modifications. This creates a need for analysis methods that can combine these various sources of data to obtain a systems-level view on aberrant biological networks.ResultsWe present a new release of KeyPathwayMiner (version 4.0) that is not limited to analyses of single omics data sets, e.g. gene expression, but is able to directly combine several different omics data types. Version 4.0 can further integrate existing knowledge by adding a search bias towards sub-networks that contain (avoid) genes provided in a positive (negative) list. Finally the new release now also provides a set of novel visualization features and has been implemented as an app for the standard bioinformatics network analysis tool: Cytoscape.ConclusionWith KeyPathwayMiner 4.0, we publish a Cytoscape app for multi-omics based sub-network extraction. It is available in Cytoscape’s app store http://apps.cytoscape.org/apps/keypathwayminer or via http://keypathwayminer.mpi-inf.mpg.de.