HORMONOMETER: A Tool for Discerning Transcript Signatures of Hormone Action in the Arabidopsis Transcriptome    

Abstract

Plant hormones regulate growth and responses to environmental change. Hormone action ultimately modifies cellular physiological processes and gene activity. To facilitate transcriptome evaluation of novel mutants and environmental responses, there is a need to rapidly assess the possible contribution of hormone action to changes in the levels of gene transcripts. We developed a vector-based algorithm that rapidly compares lists of transcripts yielding correlation values. The application as described here, called HORMONOMETER, was used to analyze hormone-related activity in a transcriptome of Arabidopsis (Arabidopsis thaliana). The veracity of the resultant analysis was established by comparison with cognate and noncognate hormone transcriptomes as well as with mutants and selected plant-environment interactions. The HORMONOMETER accurately predicted correlations between hormone action and biosynthetic mutants for which transcriptome data are available. A high degree of correlation was detected between many hormones, particularly at early time points of hormone action. Unforeseen complexity was detected in the analysis of mutants and in plant-herbivore interactions. The HORMONOMETER provides a diagnostic tool for evaluating the physiological state of being of the plant from the point of view of transcripts regulated by hormones and yields biological insight into the multiple response components that enable plant adaptation to the environment. A Web-based interface has been developed to facilitate external interfacing with this platform.

Singlet Oxygen Signatures Are Detected Independent of Light or Chloroplasts in Response to Multiple Stresses

“…The actual maximum correlation value and signal size is assembled in Supplemental Table S1 and ranged from 0.62 for 1 h OG application to a high of 0.85 for 309 flg22 treatment. Such correlation values can be considered highly significant (Volodarsky et al, 2009;Rosenwasser et al, 2011Rosenwasser et al, , 2013 and point to the involvement of a singlet oxygen-like signature in those data sets.…”

“…Both the direction and strength of the fold induction of each gene were compared and summed over all matching genes in the index to yield a correlation value. The methodology is identical to that used for discerning hormone footprints (Volodarsky et al, 2009). The correlation values are presented graphically as a heat map in which the x axis shows the ROS indices and the y axis shows the examined transcriptomes (Fig.…”

Plant Immunity: It’s the Hormones Talking, But What Do They Say?

“…Major challenges for future research lie in understanding how complex multidimensional signal interactions are regulated during the interaction of plants with multiple organisms, and why they steer the immune response toward a particular defense output. Because of the high level of complexity, the bioinformatics and systems biology tools that become increasingly available (Volodarsky et al, 2009;Pitzschke and Hirt, 2010) will be extremely valuable in this respect. Recently, Wang et al (2008) and Tsuda et al (2009) provided nice examples of the power of a systems approach.…”

Dynamic maize responses to aphid feeding are revealed by a time series of transcriptomic and metabolomic assays

“…Identification of plant hormone signatures based on transcriptomic data. The analysis was conducted using the Hormonometer program (Volodarsky et al, 2009). Red shading indicates a positive correlation between the maize aphid treatment and a particular hormone response; blue shading indicates a negative correlation.…”

“…S3) suggested that maize defense signaling pathways are differentially regulated by aphid feeding. To identify the transcriptional signatures of hormonal responses in aphidinfested maize plants, we used the Hormonometer program (http://hormonometer.weizmann.ac.il/ hormonometer), which compares the variation in gene expression with indexed data sets of hormone treatments (Volodarsky et al, 2009). We evaluated the similarity in expression profiles elicited by aphid herbivory to the application of the plant hormones methyl jasmonate, 1-aminocyclopropane-1-carboxylic acid (a metabolic precursor of ethylene), abscisic acid, indole-3-acetic acid, cytokinin (zeatin), brassinosteroid, GA 3 , and salicylic acid.…”