Transcriptome changes during fruit development and ripening of sweet orange (Citrus sinensis)

<p>Abstract</p> <p>Background</p> <p>The transcriptome of the fruit pulp of the sweet orange variety Anliu (WT) and that of its red fleshed mutant Hong Anliu (MT) were compared to understand the dynamics and differential expression of genes expressed during fruit development and ripening.</p> <p>Results</p> <p>The transcriptomes of WT and MT were sampled at four developmental stages using an Illumina sequencing platform. A total of 19,440 and 18,829 genes were detected in MT and WT, respectively. Hierarchical clustering analysis revealed 24 expression patterns for the set of all genes detected, of which 20 were in common between MT and WT. Over 89% of the genes showed differential expression during fruit development and ripening in the WT. Functional categorization of the differentially expressed genes revealed that cell wall biosynthesis, carbohydrate and citric acid metabolism, carotenoid metabolism, and the response to stress were the most differentially regulated processes occurring during fruit development and ripening.</p> <p>Conclusion</p> <p>A description of the transcriptomic changes occurring during fruit development and ripening was obtained in sweet orange, along with a dynamic view of the gene expression differences between the wild type and a red fleshed mutant.</p

Comparative transcripts profiling reveals new insight into molecular processes regulating lycopene accumulation in a sweet orange (Citrus sinensis) red-flesh mutant

<p>Abstract</p> <p>Background</p> <p>Interest in lycopene metabolism and regulation is growing rapidly because accumulative studies have suggested an important role for lycopene in human health promotion. However, little is known about the molecular processes regulating lycopene accumulation in fruits other than tomato so far.</p> <p>Results</p> <p>On a spontaneous sweet orange bud mutant with abnormal lycopene accumulation in fruits and its wild type, comparative transcripts profiling was performed using Massively Parallel Signature Sequencing (MPSS). A total of 6,877,027 and 6,275,309 reliable signatures were obtained for the wild type (WT) and the mutant (MT), respectively. Interpretation of the MPSS signatures revealed that the total number of transcribed gene in MT is 18,106, larger than that in WT 17,670, suggesting that newly initiated transcription occurs in the MT. Further comparison of the transcripts abundance between MT and WT revealed that 3,738 genes show more than two fold expression difference, and 582 genes are up- or down-regulated at 0.05% significance level by more than three fold difference. Functional assignments of the differentially expressed genes indicated that 26 reliable metabolic pathways are altered in the mutant; the most noticeable ones are carotenoid biosynthesis, photosynthesis, and citrate cycle. These data suggest that enhanced photosynthesis and partial impairment of lycopene downstream flux are critical for the formation of lycopene accumulation trait in the mutant.</p> <p>Conclusion</p> <p>This study provided a global picture of the gene expression changes in a sweet orange red-flesh mutant as compared to the wild type. Interpretation of the differentially expressed genes revealed new insight into the molecular processes regulating lycopene accumulation in the sweet orange red-flesh mutant.</p

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

In Wireless Sensor Networks (WSN), maintaining a high coverage and extending the network lifetime are two conflicting crucial issues considered by real world service providers. In this paper, we consider the coverage optimization problem in WSN with three objectives to strike the balance between network life-time and coverage. These include minimizing the energy consumption, maximizing the coverage rate and maximizing the equilibrium of energy consumption. Two improved hybrid multi-objective evolutionary algorithms, namely Hybrid-MOEA/D-I and Hybrid-MOEA/D-II, have been proposed. Based on the well-known multi-objective evolutionary algorithm based on decomposition (MOEA/D), Hybrid-MOEA/D-Ihybrids a genetic algorithm and a differential evolutionary algorithm to effectively optimize sub-problems of the multi-objective optimization problem in WSN. By integrating a discrete particle swarm algorithm, we further enhance solutions generated by Hybrid-MOEA/D-I in a new Hybrid-MOEA/D-II algorithm. Simulation results show that the proposed Hybrid-MOEA/D-I and Hybrid-MOEA/D-II algorithms have a significant better performance compared with existing algorithms in the literature in terms of all the objectives concerned

New insights into the evolution of subtilisin-like serine protease genes in Pezizomycotina

<p>Abstract</p> <p>Background</p> <p>Subtilisin-like serine proteases play an important role in pathogenic fungi during the penetration and colonization of their hosts. In this study, we perform an evolutionary analysis of the subtilisin-like serine protease genes of subphylum Pezizomycotina to find if there are similar pathogenic mechanisms among the pathogenic fungi with different life styles, which utilize subtilisin-like serine proteases as virulence factors. Within Pezizomycotina, nematode-trapping fungi are unique because they capture soil nematodes using specialized trapping devices. Increasing evidence suggests subtilisin-like serine proteases from nematode-trapping fungi are involved in the penetration and digestion of nematode cuticles. Here we also conduct positive selection analysis on the subtilisin-like serine protease genes from nematode-trapping fungi.</p> <p>Results</p> <p>Phylogenetic analysis of 189 subtilisin-like serine protease genes from Pezizomycotina suggests five strongly-supported monophyletic clades. The subtilisin-like serine protease genes previously identified or presumed as endocellular proteases were clustered into one clade and diverged the earliest in the phylogeny. In addition, the cuticle-degrading protease genes from entomopathogenic and nematode-parasitic fungi were clustered together, indicating that they might have overlapping pathogenic mechanisms against insects and nematodes. Our experimental bioassays supported this conclusion. Interestingly, although they both function as cuticle-degrading proteases, the subtilisin-like serine protease genes from nematode-trapping fungi and nematode-parasitic fungi were not grouped together in the phylogenetic tree. Our evolutionary analysis revealed evidence for positive selection on the subtilisin-like serine protease genes of the nematode-trapping fungi.</p> <p>Conclusions</p> <p>Our study provides new insights into the evolution of subtilisin-like serine protease genes in Pezizomycotina. Pezizomycotina subtilisins most likely evolved from endocellular to extracellular proteases. The entomopathogenic and nematode-parasitic fungi likely share similar properties in parasitism. In addition, our data provided better understanding about the duplications and subsequent functional divergence of subtilisin-like serine protease genes in Pezizomycotina. The evidence of positive selection detected in the subtilisin-like serine protease genes of nematode-trapping fungi in the present study suggests that the subtilisin-like serine proteases may have played important roles during the evolution of pathogenicity of nematode-trapping fungi against nematodes.</p

Multi-Feature Collaborative Fusion Network with Deep Supervision for SAR Ship Classification

Multi-feature SAR ship classification aims to build models that can process, correlate, and fuse information from both handcrafted and deep features. Although handcrafted features provide rich expert knowledge, current fusion methods inadequately explore the relatively significant role of handcrafted features in conjunction with deep features, the imbalances in feature contributions, and the cooperative ways in which features learn. In this paper, we propose a novel multi-feature collaborative fusion network with deep supervision (MFCFNet) to effectively fuse handcrafted features and deep features for SAR ship classification tasks. Specifically, our framework mainly includes two types of feature extraction branches, a knowledge supervision and collaboration module, and a feature fusion and contribution assignment module. The former module improves the quality of the feature maps learned by each branch through auxiliary feature supervision and introduces a synergy loss to facilitate the interaction of information between deep features and handcrafted features. The latter module utilizes an attention mechanism to adaptively balance the importance among various features and assign the corresponding feature contributions to the total loss function based on the generated feature weights. We conducted extensive experimental and ablation studies on two public datasets, OpenSARShip-1.0 and FUSAR-Ship, and the results show that MFCFNet is effective and outperforms single deep feature and multi-feature models based on previous internal FC layer and terminal FC layer fusion. Furthermore, our proposed MFCFNet exhibits better performance than the current state-of-the-art methods

Transitional Zone Index and Intravesical Prostatic Protrusion in Benign Prostatic Hyperplasia Patients: Correlations according to Treatment Received and Other Clinical Data

Purpose: The aim of this research was to assess the value of the transitional zone index (TZI) and intravesical prostatic protrusion (IPP) from transrectal ultrasonography in evaluating the severity and progression of disease by analyzing the relationship between the 2 parameters and symptoms, clinical history, and urodynamics in benign prostatic hyperplasia (BPH) patients undergoing different treatment. Materials and Methods: A total of 203 patients receiving medication and 162 patients who underwent transurethral resection of the prostate because of BPH were enrolled in this retrospective analysis. The clinical history and subjective and objective examination results of all patients were recorded and compared after being classified by TZI and IPP level. Linear regression was used to find correlations between IPP, TZI, and urodynamics. Results: The 2 parameters were found to differ significantly between patients receiving medication and patients undergoing surgical therapy (p&lt;0.05). PSA, maximum flow rate (Qmax), detrusor pressure at Qmax (PdetQmax), and the bladder outlet obstruction index (BOOI) differed according to various TZI levels (p&lt;0.05). In addition, the voiding symptom score, Qmax, and BOOI of subgroups with various IPP levels were also significantly different (p&lt;0.05). Both TZI and IPP had significant effects on Qmax, BOOI, and PdetQmax (p&lt;0.05) and the incidence of acute urinary retention (p=0.000). Conclusions: The results demonstrated that both TZI and IPP had favorable value for assessing severity and progression in patients with BPH. Further studies are needed to confirm whether the two parameters have predictive value in the efficacy of BPH treatment and could be considered as factors in the selection of therapy