Genome-wide analysis of the SET DOMAIN GROUP family in grapevine

The SET DOMAIN GROUP (SDG) proteins represent an evolutionarily-conserved family of epigenetic regulators present in eukaryotes and are putative candidates for the catalysis of lysine methylation in histones. Plant genomes analyses of this family have been performed in arabidopsis, maize, and rice and functional studies have shown that SDG genes are involved in the control of plant development. In this work, we describe the identification and structural characterization of SDG genes in the Vitis vinifera genome. This analysis revealed the presence of 33 putative SDG genes that can be grouped into different classes, as it has been previously described for plants. In addition to the SET domain, the proteins identified possessed other domains in the different classes. As part of our study regarding the growth and development of grapevine, we selected eight genes and their expression levels were analyzed in representative vegetative and reproductive organs of this species. The selected genes showed different patterns of expression during inflorescence and fruit development, suggesting that they participate in these processes. Furthermore, we showed that the expression of selected SDGs changes during viral infection, using as a model Grapevine Leafroll Associated Virus 3-infected symptomatic grapevine leaves and fruits. Our results suggest that developmental changes caused by this virus could be the result of alterations in SDG expression.     

Growth-induced mass flows in fungal networks

Cord-forming fungi form extensive networks that continuously adapt to maintain an efficient transport system. As osmotically driven water uptake is often distal from the tips, and aqueous fluids are incompressible, we propose that growth induces mass flows across the mycelium, whether or not there are intrahyphal concentration gradients. We imaged the temporal evolution of networks formed by Phanerochaete velutina, and at each stage calculated the unique set of currents that account for the observed changes in cord volume, while minimizing the work required to overcome viscous drag. Predicted speeds were in reasonable agreement with experimental data, and the pressure gradients needed to produce these flows are small. Furthermore, cords that were predicted to carry fast-moving or large currents were significantly more likely to increase in size than cords with slow-moving or small currents. The incompressibility of the fluids within fungi means there is a rapid global response to local fluid movements. Hence velocity of fluid flow is a local signal that conveys quasi-global information about the role of a cord within the mycelium. We suggest that fluid incompressibility and the coupling of growth and mass flow are critical physical features that enable the development of efficient, adaptive biological transport networks.     

Phagocytic function in cyclists: correlation with catecholamines and cortisol.

Flow cytometer measurements were made of the basal variations in peripheral blood functional monocytes and granulocytes over the course of a training season (January to November) of a cycling team. Parallel determinations were made of plasma concentration of catecholamines (chromatography) and cortisol (RIA) in a search for neuroendocrine markers. The results showed the greatest phagocytic capacity to occur in the central months (March, May, and July), coinciding with the greatest number and highest level of competitive events with good correlation with a peak in epinephrine during these months (r(2) = 0.998 for monocytes and r(2) = 0.674 for granulocytes). No good correlations were found between phagocytosis and norepinephrine or cortisol. The highest values for phagocytosis and epinephrine concentration were found in May. These results suggest that blood epinephrine concentration could be a good neuroendocrine marker of sportspeople's phagocytic response.     

Modelling the effect of forest cover on shallow landslides at the river basin scale

The potential for reducing the occurrence of shallow landslides through targeted reforestation of critical parts of a river basin is explored through mathematical modelling. Through the systematic investigation of land management options, modelling allows the optimum strategies to be selected ahead of any real intervention in the basin. Physically based models, for which the parameters can be evaluated using physical reasoning, offer particular advantages for predicting the effects of possible future changes in land use and climate. Typically a physically based landslide model consists of a coupled hydrological model (for soil moisture) and a geotechnical slope stability model, along with an impact model, such as basin sediment yield. An application of the SHETRAN model to the 65.8-km² Guabalcón basin in central Ecuador demonstrates a technique for identifying the areas of a basin most susceptible to shallow landsliding and for quantifying the effects of different vegetation covers on landslide incidence. Thus, for the modelled scenario, increasing root cohesion from 300 to 1500 Pa causes a two-thirds reduction in the number of landslides. Useful information can be obtained even on the basis of imperfect data availability but model output should be interpreted carefully in the light of parameter uncertainty.     

A predictive model for freshwater bioassessment (Mondego River,Portugal)

We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands. Handling editor: K. Martens     

Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

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