Summary: In their natural environment, plants are exposed to biotic or abiotic stresses that occur sequentially or simultaneously. Plant responses to these stresses have been studied widely and have been well characterised in simplified systems involving single plant species facing individual stress. Temperature elevation is a major abiotic driver of climate change and scenarios have predicted an increase in the number and severity of epidemics. In this context, here we review the available data on the effect of heat stress on plant–pathogen interactions. Considering 45 studies performed on model or crop species, we discuss the possible implications of the optimum growth temperature of plant hosts and pathogens, mode of stress application and temperature variation on resistance modulations. Alarmingly, most identified resistances are altered under temperature elevation, regardless of the plant and pathogen species. Therefore, we have listed current knowledge on heat‐dependent plant immune mechanisms and pathogen thermosensory processes, mainly studied in animals and human pathogens, that could help to understand the outcome of plant–pathogen interactions under elevated temperatures. Based on a general overview of the mechanisms involved in plant responses to pathogens, and integrating multiple interactions with the biotic environment, we provide recommendations to optimise plant disease resistance under heat stress and to identify thermotolerant resistance mechanisms.

Brassicaceae hydathode anatomy affects infection by the adapted vascular pathogen Xanthomonas campestris pv campestris.

Harnessing natural genetic variation is an established alternative to artificial genetic variation for investigating the molecular dialog between partners in plant pathosystems. Herein, we review the successes of genome-wide association studies (GWAS) in both plants and pathogens. While GWAS in plants confirmed that the genetic architecture of disease resistance is polygenic, dynamic during the infection kinetics, and dependent on the environment, GWAS shortened the time of identification of quantitative trait loci (QTLs) and revealed both complex epistatic networks and a genetic architecture dependent upon the geographical scale. A similar picture emerges from the few GWAS in pathogens. In addition, the ever-increasing number of functionally validated QTLs has revealed new molecular plant defense mechanisms and pathogenicity determinants. Finally, we propose recommendations to better decode the disease triangle.

Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome‐wide association mapping approach, this study aims to identify in Arabidopsis thaliana the genetic bases of robust resistance mechanisms to the devastating pathogen Ralstonia solanacearum under heat stress. A local mapping population was phenotyped against the R. solanacearum GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome‐wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin SOLO DANCERS gene was validated by a reverse genetic approach as involved in QDR to R. solanacearum at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.

Plant mutants for genes encoding subunits of mitochondrial complex I (CI; NADH:ubiquinone oxidoreductase), the first enzyme of the respiratory chain, display various phenotypes depending on growth conditions. Here, we examined the impact of photoperiod, a major environmental factor controlling plant development, on two Arabidopsis (Arabidopsis thaliana) CI mutants: a new insertion mutant interrupted in both ndufs8.1 and ndufs8.2 genes encoding the NDUFS8 subunit and the previously characterized ndufs4 CI mutant. In the long day (LD) condition, both ndufs8.1 and ndufs8.2 single mutants were indistinguishable from Columbia-0 at phenotypic and biochemical levels, whereas the ndufs8.1 ndufs8.2 double mutant was devoid of detectable holo-CI assembly/activity, showed higher alternative oxidase content/activity, and displayed a growth retardation phenotype similar to that of the ndufs4 mutant. Although growth was more affected in ndufs4 than in ndufs8.1 ndufs8.2 under the short day (SD) condition, both mutants displayed a similar impairment of growth acceleration after transfer to LD compared with the wild type. Untargeted and targeted metabolomics showed that overall metabolism was less responsive to the SD-to-LD transition in mutants than in the wild type. The typical LD acclimation of carbon and nitrogen assimilation as well as redox-related parameters was not observed in ndufs8.1 ndufs8. Similarly, NAD(H) content, which was higher in the SD condition in both mutants than in Columbia-0, did not adjust under LD. We propose that altered redox homeostasis and NAD(H) content/redox state control the phenotype of CI mutants and photoperiod acclimation in Arabidopsis.

C to U editing is one of the post-transcriptional steps which are required for the proper expression of chloroplast and mitochondrial genes in plants. It depends on several proteins acting together which include the PLS-class pentatricopeptide repeat proteins (PPR). DYW2 was recently shown to be required for the editing of many sites in both organelles. In particular almost all the sites associated with the E+ subfamily of PPR proteins are depending on DYW2, suggesting that DYW2 is required for the function of E+-type PPR proteins. Here we strengthened this link by identifying 16 major editing sites controlled by 3 PPR proteins: OTP90, a DYW-type PPR and PGN and MEF37, 2 E+-type PPR proteins. A re-analysis of the DYW2 editotype showed that the 49 sites known to be associated with the 18 characterized E+-type PPR proteins all depend on DYW2. Considering only the 288 DYW2-dependent editing sites as potential E+-type PPR sites, instead of the 795 known editing sites, improves the performances of binding predictions systems based on the PPR code for E+-type PPR proteins. However, it does not compensate for poor binding predictions.