PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process.

The Plant Resistance Genes database (PRGdb; http://prgdb.org/prgdb4/) has been greatly expanded, keeping pace with the increasing amount of available knowledge and data (sequenced proteomes, cloned genes, public analysis data, etc.). The easy-to-use style of the database website has been maintained, while an updated prediction tool, more data and a new section have been added. This new section will contain plant resistance transcriptomic experiments, providing additional easy-to-access experimental information. DRAGO3, the tool for automatic annotation and prediction of plant resistance genes behind PRGdb, has been improved in both accuracy and sensitivity, leading to more reliable predictions. PRGdb offers 199 reference resistance genes and 586.652 putative resistance genes from 182 sequenced proteomes. Compared to the previous release, PRGdb 4.0 has increased the number of reference resistance genes from 153 to 199, the number of putative resistance genes from 177K from 76 proteomes to 586K from 182 sequenced proteomes. A new section has been created that collects plant-pathogen transcriptomic data for five species of agricultural interest. Thereby, with these improvements and data expansions, PRGdb 4.0 aims to serve as a reference to the plant scientific community and breeders worldwide, helping to further study plant resistance mechanisms that contribute to fighting pathogens.

Genomic and metabolic profiling of two tomato contrasting cultivars for tolerance to Tuta absoluta.

MAIN CONCLUSION: Dissimilar patterns of variants affecting genes involved in response to herbivory, including those leading to difference in VOC production, were identified in tomato lines with contrasting response to Tuta absoluta. Tuta absoluta is one of the most destructive insect pest affecting tomato production, causing important yield losses both in open field and greenhouse. The selection of tolerant varieties to T. absoluta is one of the sustainable approaches to control this invasive leafminer. In this study, the genomic diversity of two tomato varieties, one tolerant and the other susceptible to T. absoluta infestation was explored, allowing us to identify chromosome regions with highly dissimilar pattern. Genes affected by potential functional variants were involved in several processes, including response to herbivory and secondary metabolism. A metabolic analysis for volatile organic compounds (VOCs) was also performed, highlighting a difference in several classes of chemicals in the two genotypes. Taken together, these findings can aid tomato breeding programs aiming to develop tolerant plants to T. absoluta.

Comparison of Tomato Transcriptomic Profiles Reveals Overlapping Patterns in Abiotic and Biotic Stress Responses.

Until a few years ago, many studies focused on the transcriptomic response to single stresses. However, tomato cultivations are often constrained by a wide range of biotic and abiotic stress that can occur singularly or in combination, and several genes can be involved in the defensive mechanism response. Therefore, we analyzed and compared the transcriptomic responses of resistant and susceptible genotypes to seven biotic stresses (Cladosporium fulvum, Phytophthora infestans, Pseudomonas syringae, Ralstonia solanacearum, Sclerotinia sclerotiorum, Tomato spotted wilt virus (TSWV) and Tuta absoluta) and five abiotic stresses (drought, salinity, low temperatures, and oxidative stress) to identify genes involved in response to multiple stressors. With this approach, we found genes encoding for TFs, phytohormones, or participating in signaling and cell wall metabolic processes, participating in defense against various biotic and abiotic stress. Moreover, a total of 1474 DEGs were commonly found between biotic and abiotic stress. Among these, 67 DEGs were involved in response to at least four different stresses. In particular, we found RLKs, MAPKs, Fasciclin-like arabinogalactans (FLAs), glycosyltransferases, genes involved in the auxin, ET, and JA pathways, MYBs, bZIPs, WRKYs and ERFs genes. Detected genes responsive to multiple stress might be further investigated with biotechnological approaches to effectively improve plant tolerance in the field.