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XopJ is a Xanthomonas type III effector protein that promotes bacterial virulence on susceptible pepper plants through the inhibition of the host cell proteasome and a resultant suppression of salicylic acid (SA) - dependent defense responses. We show here that Nicotiana benthamiana leaves transiently expressing XopJ display hypersensitive response (HR) -like symptoms when exogenously treated with SA. This apparent avirulence function of XopJ was further dependent on effector myristoylation as well as on an intact catalytic triad, suggesting a requirement of its enzymatic activity for HR-like symptom elicitation. The ability of XopJ to cause a HR-like symptom development upon SA treatment was lost upon silencing of SGT1 and NDR1, respectively, but was independent of EDS1 silencing, suggesting that XopJ is recognized by an R protein of the CC-NBS-LRR class. Furthermore, silencing of NPR1 abolished the elicitation of HR-like symptoms in XopJ expressing leaves after SA application. Measurement of the proteasome activity indicated that proteasome inhibition by XopJ was alleviated in the presence of SA, an effect that was not observed in NPR1 silenced plants. Our results suggest that XopJ - triggered HR-like symptoms are closely related to the virulence function of the effector and that XopJ follows a two-signal model in order to elicit a response in the non-host plant N. benthamiana.
Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub optimal irradiation. This review covers recent applications of omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality.
Bioturbation contributes to soil formation and ecosystem functioning. With respect to the active transport of matter by voles, bioturbation may be considered as a very dynamic process among those shaping soil formation and biogeochemistry. The present study aimed at characterizing and quantifying the effects of bioturbation by voles on soil water relations and carbon and nitrogen stocks. Bioturbation effects were examined based on a field set up in a luvic arenosol comprising of eight 50 x 50 m enclosures with greatly different numbers of common vole (Microtus arvalis L., ca. 35-150 individuals ha(-1) mth(-1)). Eleven key soil variables were analyzed: bulk density, infiltration rate, saturated hydraulic conductivity, water holding capacity, contents of soil organic carbon (SOC) and total nitrogen (N), CO2 emission potential, C/N ratio, the stable isotopic signatures of C-13 and N-15, and pH. The highest vole densities were hypothesized to cause significant changes in some variables within 21 months. Results showed that land history had still a major influence, as eight key variables displayed an additional or sole influence of topography. However, the delta N-15 at depths of 10-20 and 20-30 cm decreased and increased with increasing vole numbers, respectively. Also the CO2 emission potential from soil collected at a depth of 15-30 cm decreased and the C/N ratio at 5-10 cm depth narrowed with increasing vole numbers. These variables indicated the first influence of voles on the respective mineralization processes in some soil layers. Tendencies of vole activity homogenizing SOC and N contents across layers were not significant. The results of the other seven key variables did not confirm significant effects of voles. Thus overall, we found mainly a first response of variables that are indicative for changes in biogeochemical dynamics but not yet of those representing changes in pools.
40Ar/39Ar in situ UV laser ablation of white mica, Rb–Sr mineral isochrons and zircon fission track dating were applied to determine ages of very low- to low-grade metamorphic processes at 3.5±0.4 kbar, 280±30°C in the Avalonian Mira terrane of SE Cape Breton Island (Nova Scotia). The Mira terrane comprises Neoproterozoic volcanic-arc rocks overlain by Cambrian sedimentary rocks. Crystallization of metamorphic white mica was dated in six metavolcanic samples by 40Ar/39Ar spot age peaks between 396±3 and 363±14 Ma. Rb–Sr systematics of minerals and mineral aggregates yielded two isochrons at 389±7 Ma and 365±8 Ma, corroborating equilibrium conditions during very low- to low-grade metamorphism. The dated white mica is oriented parallel to foliations produced by sinistral strike-slip faulting and/or folding related to the Middle–Late Devonian transpressive assembly of Avalonian terranes during convergence and emplacement of the neighbouring Meguma terrane. Exhumation occurred earlier in the NW Mira terrane than in the SE. Transpression was related to the closure of the Rheic Ocean between Gondwana and Laurussia by NW-directed convergence. The 40Ar/39Ar spot age spectra also display relict age peaks at 477–465 Ma, 439 Ma and 420–428 Ma attributed to deformation and fluid access, possibly related to the collision of Avalonia with composite Laurentia or to earlier Ordovician–Silurian rifting. Fission track ages of zircon from Mira terrane samples range between 242±18 and 225±21 Ma and reflect late Palaeozoic reburial and reheating close to previous peak metamorphic temperatures under fluid-absent conditions during rifting prior to opening of the Central Atlantic Ocean.
Setting the PAS, the role of circadian PAS domain proteins during environmental adaptation in plants
(2015)
The per-ARNT-sim (PAS) domain represents an ancient protein module that can be found across all kingdoms of life. The domain functions as a sensing unit for a diverse array of signals, including molecular oxygen, small metabolites, and light. In plants, several PAS domain-containing proteins form an integral part of the circadian clock and regulate responses to environmental change. Moreover, these proteins function in pathways that control development and plant stress adaptation responses. Here, we discuss the role of PAS domain-containing proteins in anticipation, and adaptation to environmental changes in plants.
Introduction
The transition from cross-fertilisation (outcrossing) to self-fertilisation (selfing) frequently coincides with changes towards a floral morphology that optimises self-pollination, the selfing syndrome. Population genetic studies have reported the existence of both outcrossing and selfing populations in Arabis alpina (Brassicaceae), which is an emerging model species for studying the molecular basis of perenniality and local adaptation. It is unknown whether its selfing populations have evolved a selfing syndrome.
Methods
Using macro-photography, microscopy and automated cell counting, we compared floral syndromes (size, herkogamy, pollen and ovule numbers) between three outcrossing populations from the Apuan Alps and three selfing populations from the Western and Central Alps (Maritime Alps and Dolomites). In addition, we genotyped the plants for 12 microsatellite loci to confirm previous measures of diversity and inbreeding coefficients based on allozymes, and performed Bayesian clustering.
Results and Discussion
Plants from the three selfing populations had markedly smaller flowers, less herkogamy and lower pollen production than plants from the three outcrossing populations, whereas pistil length and ovule number have remained constant. Compared to allozymes, microsatellite variation was higher, but revealed similar patterns of low diversity and high Fis in selfing populations. Bayesian clustering revealed two clusters. The first cluster contained the three outcrossing populations from the Apuan Alps, the second contained the three selfing populations from the Maritime Alps and Dolomites.
Conclusion
We conclude that in comparison to three outcrossing populations, three populations with high selfing rates are characterised by a flower morphology that is closer to the selfing syndrome. The presence of outcrossing and selfing floral syndromes within a single species will facilitate unravelling the genetic basis of the selfing syndrome, and addressing which selective forces drive its evolution.
Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale.
This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.
The organic-carbon (OC) pool accumulated in Arctic permafrost (perennially frozen ground) equals the carbon stored in the modern atmosphere. To give an idea of how Yedoma region permafrost could respond under future climatic warming, we conducted a study to quantify the organic-matter quality (here defined as the intrinsic potential to be further transformed, decomposed, and mineralized) of late Pleistocene (Yedoma) and Holocene (thermokarst) deposits on the Buor-Khaya Peninsula, northeast Siberia. The objective of this study was to develop a stratigraphic classified organic-matter quality characterization. For this purpose the degree of organic-matter decomposition was estimated by using a multiproxy approach. We applied sedimentological (grain-size analyses, bulk density, ice content) and geochemical parameters (total OC, stable carbon isotopes (delta C-13),total organic carbon : nitrogen (C / N) ratios) as well as lipid biomarkers (n-alkanes, n-fatty acids, hopanes, triterpenoids, and biomarker indices, i.e., average chain length, carbon preference index (CPI), and higher-plant fatty-acid index (HPFA)). Our results show that the Yedoma and thermokarst organic-matter qualities for further decomposition exhibit no obvious degradation-depth trend. Relatively, the C / N and delta C-13 values and the HPFA index show a significantly better preservation of the organic matter stored in thermokarst deposits compared to Yedoma deposits. The CPI data suggest less degradation of the organic matter from both deposits, with a higher value for Yedoma organic matter. As the interquartile ranges of the proxies mostly over-lap, we interpret this as indicating comparable quality for further decomposition for both kinds of deposits with likely better thermokarst organic-matter quality. Supported by principal component analyses, the sediment parameters and quality proxies of Yedoma and thermokarst deposits could not be unambiguously separated from each other. This revealed that the organic-matter vulnerability is heterogeneous and depends on different decomposition trajectories and the previous decomposition and preservation history. Elucidating this was one of the major new contributions of our multiproxy study. With the addition of biomarker data, it was possible to show that permafrost organic-matter degradation likely occurs via a combination of (uncompleted) degradation cycles or a cascade of degradation steps rather than as a linear function of age or sediment facies. We conclude that the amount of organic matter in the studied sediments is high for mineral soils and of good quality and therefore susceptible to future decomposition. The lack of depth trends shows that permafrost acts like a giant freezer, preserving the constant quality of ancient organic matter. When undecomposed Yedoma organic matter is mobilized via thermokarst processes, the fate of this carbon depends largely on the environmental conditions; the carbon could be preserved in an undecomposed state till refreezing occurs. If modern input has occurred, thermokarst organic matter could be of a better quality for future microbial decomposition than that found in Yedoma deposits.
Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive-and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.
Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity.
In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min.
The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.