Correcting for link loss in causal network inference caused by regulator interference

Motivation: There are a number of algorithms to infer causal regulatory networks from time-series (gene expression) data. Here we analyse the phenomena of regulator interference, where regulators with similar dynamics mutually suppress both the probability of regulating a target and the associated link strength; for instance interference between two identical strong regulators reduces link probabilities by about 50%. Results: We construct a robust method to define an interference corrected causal network based on an analysis of the conditional link probabilities that recovers links lost through interference. On a large real network (Streptomyces coelicolor, phosphate depletion) we demonstrate that significant interference can occur between regulators with a correlation as low as 0.865, losing an estimated 34% of links by interference. However, levels of interference cannot be predicted from the correlation between regulators alone and are data specific. Validating against known networks we show that high numbers of functional links are lost by regulator interference. Performance against other methods on DREAM4 data is excellent. Availability: The method is implemented in R and is publically available as the NIACS package at: http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software

Using cell type specific transcriptomics to understand how Arabidopsis roots respond to Sinorhizobium meliloti.

Roots are key organs for the uptake of nutrients in plants. Leguminous plants form nodules, providing a niche for symbiotic nitrogen-fixing bacteria, enabling plants to colonize nitrogen depleted soils. Lateral root formation shares genetic regulation, as well as developmental features, with nodulation. This led us to investigate whether shared genetic control can be revealed in lateral root development responses of Arabidopsis thaliana to rhizobia. The phenotypic response of Arabidopsis to Sinorhizobium meliloti was analyzed. Arabidopsis lateral root length was found to be shorter, indicating a potential link between bacterial perception and lateral root development, even in a non symbiotic host plant. To gain more insight, a transcriptome time series was carried out. The response of Arabidopsis to Sinorhizobium inoculation compared to the response of nitrogen treatment were analyzed. In order to identify highly localized, yet important minimal regulatory cues and maximize the spatial specificity of the data, this analysis was carried out in isolated cortical and pericycle cells. Combined, in response to the two treatments approximately a 20% of the Arabidopsis genome is differentially expressed during the first 48 hours. Bioinformatic tools (clustering and network inference) were used to obtain a chronology of different responses, highlighting which metabolic processes change over time and identify potential gene regulatory mechanisms. The data and approach presented here present a unique analysis of the response to Sinorhizobium and nitrogen treatment and open the way to further tissue specific analysis of transcriptional regulation in plants. The similarities and differences between the response to Sinorhizobium (a potentially neutral bacteria) and Ralstonia (a pathogen of Arabidopsis roots) were evaluated using an analysis of gene expression at two early time points after inoculation. There was significant overlap in transcriptional response to both treatments, as well as striking differences: we find pathogen defense genes in the response to Sinorhizobium, rather than Ralstonia. We also find a core of 11 auxin responsive genes that have similar differential expression between treatments. Our results show that Rhizobium has a distinct transcriptional and phenotypic effect on Arabidopsis roots that is distinct from a pathogenic interaction. Several network hub genes are proposed as potential targets for further studying this effect

Analyzing the molecular basis of plant root responses to the environment

As sessile organisms, plants must be able to adapt to and exploit their environment in order to survive. A key aspect of this is the ability of plants to remodel their root system architecture in order to carry out the essential functions of providing anchorage and nutrient and water uptake from the surrounding soil. Soil typically contains a huge variety of microorganisms which will likely include species which are potentially harmful or beneficial to the plant, as well as a range of abiotic conditions. One way in which plants can adapt their root systems in response to their environment is via the formation of new lateral roots. Lateral roots generally emerge perpendicularly to the primary root or other lateral roots and increase the surface area of the root system and the range of exploration. Genes involved in the regulation of lateral root formation in Arabidopsis thaliana were investigated by using fluorescence activated cell sorting over a timecourse. Gene expression changes over time in response to nitrogen application or Sinorhizobium meliloti inoculation, both of which are associated with the regulation of lateral root development, were investigated in cells of the pericycle, from which lateral roots derive, and an overlaying cell type, the cortex. Gene expression was found to be highly cell-type specific between the two cell types and this was conserved during environmental responses. The formation of root nodules by legumes represents another quintessential example of a modification of the root to adapt to the environment. During conditions of nitrogen starvation, the plant can form structures on the root which can be colonized by symbiotic nitrogen-fixing bacteria in the soil called rhizobia. In the nodule, atmospheric nitrogen is reduced by the bacteria and utilized by the host plant. The intersection between plant defence responses and symbiosis was investigated in the model legume Medicago truncatula to try and identify genes involved in distinguishing rhizobia as symbionts rather than as pathogens. Putative novel markers of defence and symbiosis were identified that may underpin this transition