Plant responses to insects and wounding involve substantial transcriptional reprogramming that integrates hormonal, metabolic, and physiological events. The ability to respond differentially to various stresses, including wounding, generally involves hormone signaling and trans-acting regulatory factors. Evidence of the importance of transcription factors (TFs) in responses to insects is also accumulating. However, the relationships among hormone signaling, TF activity, and ability to respond specifically to different insects are uncertain. We examined transcriptional and hormonal changes in Arabidopsis thaliana after herbivory by larvae of two lepidopteran species, Spodoptera exigua (Hübner) and Pieris rapae L. over a 24-hour time course. Transcriptional responses to the two insects differed and were frequently weaker or absent in response to the specialist P. rapae. Using microarray analysis and qRT-PCR, we found 141 transcription factors, including many AP2/ERFs (Ethylene Response Factors) and selected defense-related genes, to be differentially regulated in response to the two insect species or wounding. Jasmonic Acid (JA), JA-isoleucine, and ethylene production by Arabidopsis plants increased after attack by both insect species. However, the amounts and timing of ethylene production differed between the two herbivory treatments. Our results support the hypothesis that the different responses to these two insects involve modifications of JA-signaling events and activation of different subsets of ERF transcription factors, resulting in different degrees of divergence from responses to wounding alone.

Background: Accurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics. It can also be vital in determining the effect of a treatment, genotype, or environmental condition on plant growth or susceptibility to insects or pathogens. Although techniques for characterizing complex phenotypes have been developed, most are not cost effective or are too imprecise or subjective to reliably differentiate subtler differences in complex traits like growth, color change, or disease resistance. Results: We designed an inexpensive imaging protocol that facilitates automatic quantification of two-dimensional visual phenotypes using computer vision and image processing algorithms applied to standard digital images. The protocol allows for non-destructive imaging of plants in the laboratory and field and can be used in suboptimal imaging conditions due to automated color and scale normalization. We designed the web-based tool PhenoPhyte for processing images adhering to this protocol and demonstrate its ability to measure a variety of two-dimensional traits (such as growth, leaf area, and herbivory) using images from several species (Arabidopsis thaliana and Brassica rapa). We then provide a more complicated example for measuring disease resistance of Zea mays to Southern Leaf Blight. Conclusions: PhenoPhyte is a new cost-effective web-application for semi-automated quantification of two-dimensional traits from digital imagery using an easy imaging protocol. This tool’s usefulness is demonstrated for a variety of traits in multiple species. We show that digital phenotyping can reduce human subjectivity in trait quantification, thereby increasing accuracy and improving precision, which are crucial for differentiating and quantifying subtle phenotypic variation and understanding gene function and/or treatment effects.