Gene Function Expression Profile of Faba bean (Vicia faba) Seeds

Faba bean (Vicia faba L) is one of the important grain crops worldwide and its genome, the largest among grain legumes (approx. 13.4 Gb), has yet to be sequenced. Comprehensive knowledge of genes expressed in the crop's large seeds would not only help drive new gene c improvements in the crop but also aid its future genome characteriza on. Here, we applied high throughput RNA- Seq (Quan ca on) technology to compare gene expression pro les of seeds recovered from six faba bean varie es with divergent agronomic and seed quality a ributes. We iden ed a total of 47,621 Unigenes across all genotypes and a mean count of 38,712 per genotype, total genes length 27605508bp. Comparison between expression levels in lines possessing contras ng phenotypes allowed us to iden fy candidate genes that may be associated with key traits. In all pairwise comparisons of genotypes, pairwise up-regulated plus down-regulated di erences varied between 8,661 and 12,337 genes and co-expressed genes uctuated between 30,239 and 35,884. Overall, there was a mean of 24.2% genes that were di eren ally expressed between pairs of genotypes. They were similar of GO pro les generated between the two phenotypic traits (Hydra on Capacity and Pea seed-borne mosaic virus (PSbMV) pools and comparison of the GO pro les generated by all pairs of individual genotypes. This is the rst comprehensive analysis of gene expression gene c pro le on faba bean seeds.publishersversionPeer reviewe

Experimental analysis of defrosting and heating performance of a solar-assisted heat pump integrated phase change energy storage

This thesis investigates a novel solar-assisted heat pump integrated phase change energy storage system. The defrosting performance of this system was studied experimentally and the results were compared with two traditionally used methods: reverse cycle defrosting (RCD) method and hot gas bypass defrosting (HGBD) method. The results show that the phase change energy storage system has superior performance compared with traditional defrosting methods. The indoor temperature drop recorded was relatively small and the defrosting time was 75% of the RCD system and 53% of HGBD system. The phase change energy storage system increased the condensation temperature which consequently increased the temperature difference of heat transfer resulting in higher conductivity in the defrosting progress. Compared with the method of RCD and the method of HGBD, the recovery time of the system was shortened by 90 and 160 seconds, respectively. The system works with low-temperature heat source and circulating water, which considerably reduces energy consumption, thereby improving the performance of the defrosting system. A further experimental study was also conducted on the heating performance and the results also indicated that the value of COP can reach up to 3.6 in daytime, and the indoor temperature can be stably maintained above 18°C throughout the day

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID‐19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran’s Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.ResultsWe found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92–0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.ConclusionsOur study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

Helicopter Autorotation Trajectory Planning Method Using Functional Tensor-Train-Based Dynamic Programming Algorithms

Helicopter autorotation trajectory planning problems have been dealt within computationally expensive optimal control algorithms. This paper presents an efficient helicopter autorotation trajectory planning method, using functional tensor-train- (FT-) based dynamic programming (DP) algorithms. The autorotation trajectory planning method is shown real-time feasible, which involves general helicopter autorotation dynamics at the same time. To validate the dynamic feasibility of the trajectories, a trajectory-tracking controller using active disturbance rejection control (ADRC) is designed to ensure a helicopter model tracks the trajectories. Finally, a helicopter autorotation simulation with a six-degree-of-freedom high-fidelity multibody-based helicopter model is demonstrated for validation

Identification of immune-related biomarkers and construction of regulatory network in patients with atherosclerosis

Abstract Background More and more evidence has established the crucial roles of the innate and adaptive immune systems in driving atherosclerosis-associated chronic inflammation in arterial blood vessels. Thus, the goal of this research was to determine immune-related biomarkers in atherosclerosis. Methods In this study, we conducted analysis on the mRNA expression profile of atherosclerosis obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) between atherosclerosis and control samples and immune-related genes (IRGs) were intersected to obtain differentially expressed immune-related genes (DEIRGs). The protein–protein interaction (PPI) network was created by STRING database and hub genes were identified by the MCODE plug-in. Furthermore, the receiver operating characteristic (ROC) curve was executed to verify the diagnostic value of the hub genes, and microRNA (miRNA)-gene-transcription factor (TF) regulatory networks were used to explain the regulatory mechanism of hub genes in atherosclerosis. Finally, qRT-PCR was performed to identify the mRNA levels of the target genes. Results A total of 199 overlapping genes were screened out as DEIRGs by intersecting the DEGs and IRGs. Then, 6 hub genes with high diagnostic value (IFIH1, IFIT1, IFIT2, IFIT3, ISG15 and OAS3) were identified via PPI network and ROC curve. Finally, miRNA-gene-TF networks revealed the regulatory mechanism of diagnostic genes.We used the carotid artery of AS patients and normal human carotid artery plaque samples for qRT-PCR verification, and the results showed that the hub gene had the same trend. Conclusion Our study identified IFIH1, IFIT1, IFIT2, IFIT3, ISG15 and OAS3 as immune-related hub genes of atherosclerosis. These genes may serve as potential therapeutic targets for atherosclerosis patients