Plasticity of rosette size in response to nitrogen availability is controlled by an RCC1-family protein

Nitrogen (N) is fundamental to plant growth, development and yield. Genes underlying N utilization and assimilation are well-characterized, but mechanisms underpinning plasticity of different phenotypes in response to N remain elusive. Here, using Arabidopsis thaliana accessions, we dissected the genetic architecture of plasticity in early and late rosette diameter, flowering time and yield, in response to three levels of N in the soil. Furthermore, we found that the plasticity in levels of primary metabolites were related with the plasticities of the studied traits. Genome-wide association analysis identified three significant associations for phenotypic plasticity, one for early rosette diameter and two for flowering time. We confirmed that the gene At1g19880, hereafter named as PLASTICITY OF ROSETTE TO NITROGEN 1 (PROTON1), encoding for a regulator of chromatin condensation 1 (RCC1) family protein, conferred plasticity of rosette diameter in response to N. Treatment of PROTON1 T-DNA line with salt implied that the reduced plasticity of early rosette diameter was not a general growth response to stress. We further showed that plasticities of growth and flowering-related traits differed between environmental cues, indicating decoupled genetic programs regulating these traits. Our findings provide a prospective to identify genes that stabilize performance under fluctuating environments.Peer reviewe

Enhance the Efficiency of Heuristic Algorithm for Maximizing Modularity Q

Modularity Q is an important function for identifying community structure in complex networks. In this paper, we prove that the modularity maximization problem is equivalent to a nonconvex quadratic programming problem. This result provide us a simple way to improve the efficiency of heuristic algorithms for maximizing modularity Q. Many numerical results demonstrate that it is very effective.Comment: 9 pages, 3 figure

Size reduction of complex networks preserving modularity

The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.Comment: 14 pages, 2 figure

Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

Introduction: To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism. Objective: This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues. Methods: The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses. Results: Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism. Conclusions: Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.Fil: Nunes Nesi, Adriano. Max Planck Institute Of Molecular Plant Physiology; Alemania. Universidade Federal de Viçosa.; BrasilFil: Alseekh, Saleh. Center Of Plant Systems Biology And Biotechnology; Bulgaria. Max Planck Institute Of Molecular Plant Physiology; AlemaniaFil: de Oliveira Silva, Franklin Magnum. Universidade Federal de Viçosa.; BrasilFil: Omranian, Nooshin. Max Planck Institute Of Molecular Plant Physiology; Alemania. Center Of Plant Systems Biology And Biotechnology; BulgariaFil: Lichtenstein, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Mirnezhad, Mohammad. Leiden University; Países BajosFil: Romero González, Roman R.. Leiden University; Países BajosFil: Sabio y Garcia, Julia Veronica. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Conte, Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Leiss, Kirsten A.. Leiden University; Países BajosFil: Klinkhamer, Peter G. L.. Leiden University; Países BajosFil: Nikoloski, Zoran. University of Potsdam; Alemania. Max Planck Institute of Molecular Plant Physiology; AlemaniaFil: Carrari, Fernando Oscar. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias Castelar. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Fernie, Alisdair R.. Max Planck Institute of Molecular Plant Physiology; Alemania. Center of Plant System Biology and Biotechnology; Bulgari

Modelización del estado de vacunación contra la COVID-19 y del cumplimiento de las medidas sociales y de salud pública, Región del Mediterráneo Oriental y Argelia

Objective To study the link between coronavirus disease 2019 (COVID-19) vaccination status and adherence to public health and social measures in Members of the Eastern Mediterranean Region and Algeria. Methods We analysed two rounds of a large, cross-country, repeated cross-sectional mobile phone survey in June–July 2021 and October–November 2021. The rounds included 14 287 and 14 131 respondents, respectively, from 23 countries and territories. Questions covered knowledge, attitudes and practices around COVID-19, and demographic, employment, health and vaccination status. We used logit modelling to analyse the link between self-reported vaccination status and individuals’ practice of mask wearing, physical distancing and handwashing. We used propensity score matching as a robustness check. Findings Overall, vaccinated respondents (8766 respondents in round 2) were significantly more likely to adhere to preventive measures than those who were unvaccinated (5297 respondents in round 2). Odds ratios were 1.5 (95% confidence interval, CI: 1.3–1.8) for mask wearing; 1.5 (95% CI: 1.3–1.7) for physical distancing; and 1.2 (95% CI: 1.0–1.4) for handwashing. Similar results were found on analysing subsamples of low-and middle-income countries. However, in high-income countries, where vaccination coverage is high, there was no significant link between vaccination and preventive practices. The association between vaccination status and adherence to public health advice was sustained over time, even though self-reported vaccination coverage tripled over 5 months (19.4% to 62.3%; weighted percentages). Conclusion Individuals vaccinated against COVID-19 maintained their adherence to preventive health measures. Nevertheless, reinforcement of public health messages is important for the public’s continued compliance with preventive measures

Fast unfolding of communities in large networks

We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks. .Comment: 6 pages, 5 figures, 1 table; new version with new figures in order to clarify our method, where we look more carefully at the role played by the ordering of the nodes and where we compare our method with that of Wakita and Tsurum

EFSA Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids (CEF); Scientific Opinion on Flavouring Group Evaluation 96 (FGE.96): Consideration of 88 flavouring substances considered by EFSA for which EU production volumes / anticipated production volumes have been submitted on request by DG SANCO. Addendum to FGE. 51, 52, 53, 54, 56, 58, 61, 62, 63, 64, 68, 69, 70, 71, 73, 76, 77, 79, 80, 83, 84, 85 and 87

Overgrowth disorders are a heterogeneous group of conditions characterized by increased growth parameters and other variable clinical features such as intellectual disability and facial dysmorphism1. To identify new causes of human overgrowth, we performed exome sequencing in ten proband-parent trios and detected two de novo DNMT3A mutations. We identified 11 additional de novo mutations by sequencing DNMT3A in a further 142 individuals with overgrowth. The mutations alter residues in functional DNMT3A domains, and protein modeling suggests that they interfere with domain-domain interactions and histone binding. Similar mutations were not present in 1,000 UK population controls (13/152 cases versus 0/1,000 controls; P < 0.0001). Mutation carriers had a distinctive facial appearance, intellectual disability and greater height. DNMT3A encodes a DNA methyltransferase essential for establishing methylation during embryogenesis and is commonly somatically mutated in acute myeloid leukemia2, 3, 4. Thus, DNMT3A joins an emerging group of epigenetic DNA- and histone-modifying genes associated with both developmental growth disorders and hematological malignancie

EZH2 Depletion Blocks the Proliferation of Colon Cancer Cells

The Enhancer of Zeste 2 (EZH2) protein has been reported to stimulate cell growth in some cancers and is therefore considered to represent an interesting new target for therapeutic intervention. Here, we investigated a possible role of EZH2 for the growth control of colon cancer cells. RNA interference (RNAi)-mediated intracellular EZH2 depletion led to cell cycle arrest of colon carcinoma cells at the G1/S transition. This was associated with a reduction of cell numbers upon transient transfection of synthetic EZH2-targeting siRNAs and with inhibition of their colony formation capacity upon stable expression of vector-borne siRNAs. We furthermore tested whether EZH2 may repress the growth-inhibitory p27 gene, as reported for pancreatic cancer. However, expression analyses of colon cancer cell lines and colon cancer biopsies did not reveal a consistent correlation between EZH2 and p27 levels. Moreover, EZH2 depletion did not re-induce p27 expression in colon cancer cells, indicating that p27 repression by EZH2 may be cell- or tissue-specific. Whole genome transcriptome analyses identified cellular genes affected by EZH2 depletion in colon cancer cell lines. They included several cancer-associated genes linked to cellular proliferation or invasion, such as Dag1, MageD1, SDC1, Timp2, and Tob1. In conclusion, our results demonstrate that EZH2 depletion blocks the growth of colon cancer cells. These findings might provide benefits for the treatment of colon cancer