Evidence that differential gene expression between the halophyte, Thellungiella halophila , and Arabidopsis thaliana is responsible for higher levels of the compatible osmolyte proline and tight control of Na + uptake in T. halophila SURYA ABSTRACTSalt-sensitive glycophytes and salt-tolerant halophytes employ common mechanisms to cope with salinity, and it is hypothesized that differences in salt tolerance arise because of changes in the regulation of a basic set of salt tolerance genes. We explored the expression of genes involved in two key salt tolerance mechanisms in Arabidopsis thaliana and the halophytic A. thaliana relative model system (ARMS), Thellungiella halophila . Salt overly sensitive 1 (SOS1) is a plasma membrane Na + /H + antiporter that retrieves and loads Na + ions from and into the xylem. Shoot SOS1 transcript was more strongly induced by salt in T. halophila while root SOS1 was constitutively higher in unstressed T. halophila . This is consistent with a lower salt-induced rise in T. halophila xylem sap Na + concentration than in A. thaliana . Thellungiella halophila contained higher unstressed levels of the compatible osmolyte proline than A. thaliana , while under salt stress, T. halophila accumulated more proline mainly in shoots. Expression of the A. thaliana ortholog of proline dehydrogenase (PDH), involved in proline catabolism, was undetectable in T. halophila shoots. The PDH enzyme activity was lower and T. halophila seedlings were hypersensitive to exogenous proline, indicating repression of proline catabolism in T. halophila . Our results suggest that differential gene expression between glycophytes and halophytes contributes to the salt tolerance of halophytes.

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g(-1) for soluble sugars, 6-533 (mean = 94) mg g(-1) for starch and 53-649 (mean = 153) mg g(-1) for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R(2) = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g(-1) for total NSC, compared with the range of laboratory estimates of 596 mg g(-1). Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.

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Hexokinase (HXK) is a sugar-phosphorylating enzyme involved in sugar-sensing. It has recently been shown that HXK in guard cells mediates stomatal closure and coordinates photosynthesis with transpiration in the annual species tomato and Arabidopsis. To examine the role of HXK in the control of the stomatal movement of perennial plants, we generated citrus plants that express Arabidopsis HXK1 (AtHXK1) under KST1, a guard cell-specific promoter. The expression of KST1 in the guard cells of citrus plants has been verified using GFP as a reporter gene. The expression of AtHXK1 in the guard cells of citrus reduced stomatal conductance and transpiration with no negative effect on the rate of photosynthesis, leading to increased water-use efficiency. The effects of light intensity and humidity on stomatal behavior were examined in rooted leaves of the citrus plants. The optimal intensity of photosynthetically active radiation and lower humidity enhanced stomatal closure of AtHXK1-expressing leaves, supporting the role of sugar in the regulation of citrus stomata. These results suggest that HXK coordinates photosynthesis and transpiration and stimulates stomatal closure not only in annual species, but also in perennial species.

Aim-Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition.Location-224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Europe PMC Funders Author Manuscripts Europe PMC Funders Author ManuscriptsMethods-Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables.Results-Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm).Main conclusions-Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.