Cucumber SUPERMAN Has Conserved Function in Stamen and Fruit Development and a Distinct Role in Floral Patterning

This is the published version. Copyright 2014 Public Library of Science.The Arabidopsis SUPERMAN (SUP) gene encodes a C2H2 type zinc finger protein that is required for maintaining the boundaries between stamens and carpels, and for regulating development of ovule outer integument. Orthologs of SUP have been characterized in bisexual flowers as well as dioecious species, but it remains elusive in monoecious plants with unisexual flowers on the same individual. Here we isolate the SUP ortholog in Cucumis sativus L (CsSUP), a monoecious vegetable. CsSUP is predominantly expressed in female specific organs: the female flower buds and ovules. Ectopic expression of CsSUP in Arabidopsis can partially complement the fruit development in sup-5 mutant, and its over-expression in wide-type leads to reduced silique length, suppressed stamen development and distorted petal patterning. Our data suggest that CsSUP plays conserved as well as distinct roles during flower and fruit development, and it may function in the boundaries and ovules to balance petal patterning, stamen and ovule development in Arabidopsis

The Regulatory Landscape of a Core Maize Domestication Module Controlling Bud Dormancy and Growth Repression

Many domesticated crop plants have been bred for increased apical dominance, displaying greatly reduced axillary branching compared to their wild ancestors. In maize, this was achieved through selection for a gain-of-function allele of the TCP transcription factor teosinte branched1 (tb1). The mechanism for how a dominant Tb1 allele increased apical dominance, is unknown. Through ChIP seq, RNA seq, hormone and sugar measurements on 1 mm axillary bud tissue, we identify the genetic pathways putatively regulated by TB1. These include pathways regulating phytohormones such as gibberellins, abscisic acid and jasmonic acid, but surprisingly, not auxin. In addition, metabolites involved in sugar sensing such as trehalose 6-phosphate were increased. This suggests that TB1 induces bud suppression through the production of inhibitory phytohormones and by reducing sugar levels and energy balance. Interestingly, TB1 also putatively targets several other domestication loci, including teosinte glume architecture1, prol1.1/grassy tillers1, as well as itself. This places tb1 on top of the domestication hierarchy, demonstrating its critical importance during the domestication of maize from teosinte

Boundary domain genes were recruited to suppress bract growth and promote branching in maize

Grass inflorescence development is diverse and complex and involves sophisticated but poorly understood interactions of genes regulating branch determinacy and leaf growth. Here, we use a combination of transcript profiling and genetic and phylogenetic analyses to investigate tasselsheath1 (tsh1) and tsh4, two maize genes that simultaneously suppress inflorescence leaf growth and promote branching. We identify a regulatory network of inflorescence leaf suppression that involves the phase change gene tsh4 upstream of tsh1 and the ligule identity gene liguleless2 (lg2). We also find that a series of duplications in the tsh1 gene lineage facilitated its shift from boundary domain in nongrasses to suppressed inflorescence leaves of grasses. Collectively, these results suggest that the boundary domain genes tsh1 and lg2 were recruited to inflorescence leaves where they suppress growth and regulate a nonautonomous signaling center that promotes inflorescence branching, an important component of yield in cereal grasses

Genome-resolved metagenomics reveals role of iron metabolism in drought-induced rhizosphere microbiome dynamics

Recent studies have demonstrated that drought leads to dramatic, highly conserved shifts in the root microbiome. At present, the molecular mechanisms underlying these responses remain largely uncharacterized. Here we employ genome-resolved metagenomics and comparative genomics to demonstrate that carbohydrate and secondary metabolite transport functionalities are overrepresented within drought-enriched taxa. These data also reveal that bacterial iron transport and metabolism functionality is highly correlated with drought enrichment. Using time-series root RNA-Seq data, we demonstrate that iron homeostasis within the root is impacted by drought stress, and that loss of a plant phytosiderophore iron transporter impacts microbial community composition, leading to significant increases in the drought-enriched lineage, Actinobacteria. Finally, we show that exogenous application of iron disrupts the drought-induced enrichment of Actinobacteria, as well as their improvement in host phenotype during drought stress. Collectively, our findings implicate iron metabolism in the root microbiome’s response to drought and may inform efforts to improve plant drought tolerance to increase food security

Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules

ObjectiveTo develop and validate the model for predicting benign and malignant ground-glass nodules (GGNs) based on the whole-lung baseline CT features deriving from deep learning and radiomics.MethodsThis retrospective study included 385 GGNs from 3 hospitals, confirmed by pathology. We used 239 GGNs from Hospital 1 as the training and internal validation set; 115 and 31 GGNs from Hospital 2 and Hospital 3 as the external test sets 1 and 2, respectively. An additional 32 stable GGNs from Hospital 3 with more than five years of follow-up were used as the external test set 3. We evaluated clinical and morphological features of GGNs at baseline chest CT and extracted the whole-lung radiomics features simultaneously. Besides, baseline whole-lung CT image features are further assisted and extracted using the convolutional neural network. We used the back-propagation neural network to construct five prediction models based on different collocations of the features used for training. The area under the receiver operator characteristic curve (AUC) was used to compare the prediction performance among the five models. The Delong test was used to compare the differences in AUC between models pairwise.ResultsThe model integrated clinical-morphological features, whole-lung radiomic features, and whole-lung image features (CMRI) performed best among the five models, and achieved the highest AUC in the internal validation set, external test set 1, and external test set 2, which were 0.886 (95% CI: 0.841-0.921), 0.830 (95%CI: 0.749-0.893) and 0.879 (95%CI: 0.712-0.968), respectively. In the above three sets, the differences in AUC between the CMRI model and other models were significant (all P < 0.05). Moreover, the accuracy of the CMRI model in the external test set 3 was 96.88%.ConclusionThe baseline whole-lung CT features were feasible to predict the benign and malignant of GGNs, which is helpful for more refined management of GGNs

Onset of wake meandering for a floating offshore wind turbine under side-to-side motion

Wind turbine wakes, being convectively unstable, may behave as an amplifier of upstream perturbations and make downstream turbines experience strong inflow fluctuations. In this work, we investigate the effects of the side-to-side motion of a floating offshore wind turbine (FOWT) on wake dynamics using large-eddy simulation and linear stability analysis (LSA). When the inflow turbulence intensity is low, simulation results reveal that the turbine motion with certain Strouhal numbers St = fD/U-infinity is an element of (0.2, 0.6) (where f is the motion frequency, D is the rotor diameter, and U-infinity is the incoming wind speed), which overlap with the Strouhal numbers of wake meandering induced by the shear layer instability, can lead to wake meandering with amplitudes being one order of magnitude larger than the FOWT motion for the most unstable frequency. For high inflow turbulence intensity, on the other hand, the onset of wake meandering is dominated by the inflow turbulence. The probability density function of the spanwise instantaneous wake centres is observed being non-Gaussian and closely related to that of the side-to-side motion. This complements the existing wake meandering mechanisms, that the side-to-side motion of an FOWT can be a novel origin for the onset of wake meandering. It is also found that LSA can predict the least stable frequencies and the amplification factor with acceptable accuracy for motion amplitude 0.01D. Effects of nonlinearity are observed when motion amplitude increases to 0.04D, for which the most unstable turbine oscillations shift slightly to lower frequencies and the amplification factor decreases

Predictive capability of actuator disk models for wakes of different wind turbine designs

To evaluate the predictive capability of the actuator disk (AD) models in simulating wakes of different wind turbine designs, we compare the results of the AD simulation with those of the actuator surface (AS) simulation for the EOLOS, NREL and a variant of the NREL (i.e., NREL-V) wind turbine designs. Two types of AD models are considered, i.e., the AD-R and AD-NR models corresponding to the AD model with and without rotational effects, respectively. For the AD models, the force coefficients are both obtained from the corresponding AS simulations. The results from the AD simulation are compared with those of AS simulations. It is observed that the velocity profiles predicted by the AD models agree well with the AS predictions. For the turbulent kinetic energy and the Reynolds shear stress, differences appear at far wake locations (7D, and 9D downwind of the turbine where D is the rotor diameter) for both the EOLOS and the NREL-V turbines. In case of the NREL turbine, on the other hand, there is an overall good agreement except in 3D downwind to the turbine. Furthermore, the modes obtained by using the proper orthogonal decomposition from the AD and AS simulations are also presented and compared with each other, indicating that the distribution of the mode energy, and the location and features of the mode patterns differ for different turbine designs. (c) 2022 Elsevier Ltd. All rights reserved

Characteristics of wind turbine wakes for different blade designs

In this work, we investigate the characteristics of wind turbine wakes for three different blade designs (i.e. the NREL-Ori, NREL-Root and NREL-Tip designs, where the NREL-Ori refers to the baseline offshore 5 MW wind turbine designed by the US National Renewable Energy Laboratory) under turbulent inflows using large-eddy simulations with the actuator surface model. The load on the blade is higher near the blade root/tip for the NREL-Root/NREL-Tip designs when compared with the NREL-Ori design, while their thrust coefficients are the same. The results show that the blade designs influence the velocity deficit in the near wake, turbulence kinetic energy and wake meandering (both amplitude and frequency). In the near-wake region, the magnitude of the velocity deficit from the NREL-Root design is higher. As for the turbulence kinetic energy, its maximum in the near wake is higher for the NREL-Tip design, while in the far wake, it is higher for the NREL-Root design. Analyses of the instantaneous spanwise wake centre positions show higher meandering amplitude for the NREL-Root design, with the magnitudes of the low-frequency components approximately the same as the other two designs under the same inflow. The dominant meandering frequencies from different designs are different, with lower values for the NREL-Root design for which the vortex structures near the hub of low frequency play leading roles, and higher values for the NREL-Tip design for which the flow structures of high frequency in the tip shear layer are more important

Statistics of Wind Farm Wakes for Different Layouts and Ground Roughness

In this work, wakes of wind farms are investigated using large-eddy simulation with an actuator disk model for the wind turbine. The effects of streamwise turbine spacings, number of wind turbine rows and roughness lengths of ground surface on the characteristics of wind farm wakes are examined. The simulation results showed that the effects of S-x (streamwise turbine spacings) are mainly located in the near wake of wind farm (less than 20 rotor diameters downstream from the last row of the wind farm), where the turbulence intensity is higher for smaller values of S-x. In the far wake of wind farms (more than 90 rotor diameters downstream from the last row of the wind farm), the streamwise velocity deficit as well as the Reynolds stresses from cases with different streamwise turbine spacings are close to each other. For cases with more wind turbine rows (N-row) and larger roughness length of ground surface (k0), faster velocity recovery and higher turbulence intensity are observed. Terms in the budget equation for mean kinetic energy (MKE) are examined. The analyses showed that the vertical MKE transport via mean convection and turbulence convection plays a dominant role in the velocity recovery in wind farm wakes, being different from the wind farm region where streamwise MKE flux due to mean convection also plays a role. Lastly, an analytical model for the velocity deficit in wind farm wake is proposed based on the Emeis model. Improvements on the model predictions are observed for all the simulated cases. The velocity deficit at one downstream location of the wind farm needs to be given is one major limitation of the analytical model of this type