How does the brand image affect the Norwegian salmon export to China?

Masteroppgave i International business and marketing (MSc

Characterization of Duck (Anas platyrhynchos) Short Tandem Repeat Variation by Population-Scale Genome Resequencing

Short tandem repeats (STRs) are usually associated with genetic diseases and gene regulatory functions, and are also important genetic markers for analysis of evolutionary, genetic diversity and forensic. However, for the majority of STRs in the duck genome, their population genetic properties and functional impacts remain poorly defined. Recent advent of next generation sequencing (NGS) has offered an opportunity for profiling large numbers of polymorphic STRs. Here, we reported a population-scale analysis of STR variation using genome resequencing in mallard and Pekin duck. Our analysis provided the first genome-wide duck STR reference including 198,022 STR loci with motif size of 2–6 base pairs. We observed a relatively uneven distribution of STRs in different genomic regions, which indicates that the occurrence of STRs in duck genome is not random, but undergoes a directional selection pressure. Using genome resequencing data of 23 mallard and 26 Pekin ducks, we successfully identified 89,891 polymorphic STR loci. Intensive analysis of this dataset suggested that shorter repeat motif, longer reference tract length, higher purity, and residing outside of a coding region are all associated with an increase in STR variability. STR genotypes were utilized for population genetic analysis, and the results showed that population structure and divergence patterns among population groups can be efficiently captured. In addition, comparison between Pekin duck and mallard identified 3,122 STRs with extremely divergent allele frequency, which overlapped with a set of genes related to nervous system, energy metabolism and behavior. The evolutionary analysis revealed that the genes containing divergent STRs may play important roles in phenotypic changes during duck domestication. The variation analysis of STRs in population scale provides valuable resource for future study of genetic diversity and genome evolution in duck

Messenger RNA Sequencing and Pathway Analysis Provide Novel Insights Into the Susceptibility to Salmonella enteritidis Infection in Chickens

Salmonella enteritidis (SE) is a foodborne pathogen that negatively affects both animal and human health. Controlling poultry SE infection will have great practical significance for human public health, as poultry are considered to be important sources and carriers of the disease. In this study, the splenic transcriptomes of challenged-susceptible (S), challenged-resistant (R) and non-challenged (C) chicks (3-days old, specific-pathogen-free White Leghorn) were characterized in order to identify the immune-related gene markers and pathways. A total of 934 significant differentially expressed genes (DEGs) were identified in comparisons among the C, R and S birds. First reported here, the DEGs involved in the Forkhead box O (FoxO) signaling pathway, especially FoxO3, were identified as potential markers for host resistance to SE infection. The challenged-susceptible birds exhibited strong activation of the FoxO signaling pathway, which may be a major defect causing immune cell apoptosis as part of SE-induced pathology; these S birds also showed weak activation of mitogen-activated protein kinase (MAPK)-related genes, contrasting with strong splenic activation in the R birds. Interestingly, suppression of several pathways in the immune response against Salmonella, including cytokine-cytokine receptor interaction and Jak-STAT, was only found in S birds and there was evidence of cross-talk among these pathways, perhaps contributing to susceptibility to Salmonella infection. These findings will help facilitate understanding resistance and susceptibility to SE infection in the earliest phases of the host immune response through Salmonella-induced pathways, provide new approaches to develop strategies for SE prevention and treatment, and may enhance innate resistance by genetic selection in animals

A curvature sensor based on twisted single-mode-multimode-single-mode hybrid optical fiber structure

An optical fiber curvature sensor based on a twisted multimode fiber (MMF) sandwiched between two single-mode fibers (SMF) is proposed and investigated theoretically and experimentally. The measured transmission spectrum exhibits good agreement with theoretical predictions. Compared with a traditional single-mode-multimode-single-mode fiber structure sensor, the proposed configuration offers a higher average curvature sensitivity of -2.42 nm/m -1 over a curvature measurement range of 0-1.7390 m -1 and -7.09 dB/m -1 at an operating wavelength of 1537 nm. The temperature sensitivity of this sensor has been determined as 0.01 nm/°C over a wavelength range of 1535-1550 nm and circa 0.007 dB/°C at the wavelength of 1537 nm, over a measured temperature range of 21-121 °C

Transcriptome Profiling to Identify Genes Involved in Mesosulfuron-Methyl Resistance in Alopecurus aequalis

Non-target-site resistance (NTSR) to herbicides is a worldwide concern for weed control. However, as the dominant NTSR mechanism in weeds, metabolic resistance is not yet well-characterized at the genetic level. For this study, we have identified a shortawn foxtail (Alopecurus aequalis Sobol.) population displaying both TSR and NTSR to mesosulfuron-methyl and fenoxaprop-P-ethyl, yet the molecular basis for this NTSR remains unclear. To investigate the mechanisms of metabolic resistance, an RNA-Seq transcriptome analysis was used to find candidate genes that may confer metabolic resistance to the herbicide mesosulfuron-methyl in this plant population. The RNA-Seq libraries generated 831,846,736 clean reads. The de novo transcriptome assembly yielded 95,479 unigenes (averaging 944 bp in length) that were assigned putative annotations. Among these, a total of 29,889 unigenes were assigned to 67 GO terms that contained three main categories, and 14,246 unigenes assigned to 32 predicted KEGG metabolic pathways. Global gene expression was measured using the reads generated from the untreated control (CK), water-only control (WCK), and mesosulfuron-methyl treatment (T) of R and susceptible (S). Contigs that showed expression differences between mesosulfuron-methyl-treated R and S biotypes, and between mesosulfuron-methyl-treated, water-treated and untreated R plants were selected for further quantitative real-time PCR (qRT-PCR) validation analyses. Seventeen contigs were consistently highly expressed in the resistant A. aequalis plants, including four cytochrome P450 monooxygenase (CytP450) genes, two glutathione S-transferase (GST) genes, two glucosyltransferase (GT) genes, two ATP-binding cassette (ABC) transporter genes, and seven additional contigs with functional annotations related to oxidation, hydrolysis, and plant stress physiology. These 17 contigs could serve as major candidate genes for contributing to metabolic mesosulfuron-methyl resistance; hence they deserve further functional study. This is the first large-scale transcriptome-sequencing study to identify NTSR genes in A. aequalis that uses the Illumina platform. This work demonstrates that NTSR is likely driven by the differences in the expression patterns of a set of genes. The assembled transcriptome data presented here provide a valuable resource for A. aequalis biology, and should facilitate the study of herbicide resistance at the molecular level in this and other weed species

Widely Targeted Metabolomics Revealed the Dynamic Changes of Metabolites during the Formation of Goose Fatty Liver

To understand the composition and dynamic changes of metabolites during the formation of goose fatty liver, the metabolite profiles of goose liver at three overfeeding stages were analyzed using widely targeted metabolomics. Three 70-day-old Landes geese with similar body conditions from the same batch were selected randomly for slaughter at the early (day 7), middle (day 16) and late (day 25) overfeeding stages, separately. The tip of the larger liver lobe was collected for widely targeted metabolomic analysis. The results showed that: (1) a total of 1 153 metabolites belonging to 19 classes including amino acids, organic acids, nucleotides and lipids were detected in the liver of geese at the three overfeeding stages; (2) principal component analysis (PCA) showed significant differences in the metabolic profiles of goose liver at the three stages, and identified 142 and 92 differential metabolites at the early versus middle stage, and the middle versus late stage, respectively, the major ones being amino acids and their derivatives, as well as organic acids and their derivatives; and (3) Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis indicated that the pathways involved in fatty acid biosynthesis, vitamin B6 metabolism, linoleic acid metabolism, lysine degradation, arginine biosynthesis, arachidonic acid metabolism and amino acid biosynthesis changed significantly during the formation of goose fatty liver. This study found that most of the differential metabolites were involved in fatty acid synthesis during goose fatty liver formation. Moreover, the contents of transport-related metabolites showed a continuous increasing trend. Findings in this study will not only enrich the theoretical knowledge of poultry liver metabolism, but also provide a theoretical basis for the precise nutritional regulation and efficient production of high-quality goose fatty liver

The water lily genome and the early evolution of flowering plants

Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms1–3. Here we report the 409-megabase genome sequence of the blue-petal water lily (Nymphaea colorata). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The N. colorata genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in N. colorata might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in N. colorata. The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the N. colorata genome sheds light on the early evolution of angiosperms.Supplementary Tables: This file contains Supplementary Tables 1-21.National Natural Science Foundation of China, the open funds of the State Key Laboratory of Crop Genetics and Germplasm Enhancement (ZW201909) and State Key Laboratory of Tree Genetics and Breeding, the Fujian provincial government in China, the European Union Seventh Framework Programme (FP7/2007-2013) under European Research Council Advanced Grant Agreement and the Special Research Fund of Ghent University.http://www.nature.com/naturecommunicationsam2021BiochemistryGeneticsMicrobiology and Plant Patholog

Coordinated Approach Fusing RCMDE and Sparrow Search Algorithm-Based SVM for Fault Diagnosis of Rolling Bearings

We propose a novel fault-diagnosis approach for rolling bearings by integrating variational mode decomposition (VMD), refined composite multiscale dispersion entropy (RCMDE), and support vector machine (SVM) optimized by a sparrow search algorithm (SSA). Firstly, VMD was selected from various signal decomposition methods to decompose the original signal. Then, the signal features were extracted by RCMDE as the input of the diagnosis model. Compared with multiscale sample entropy (MSE) and multiscale dispersion entropy (MDE), RCMDE proved to be superior. Afterwards, SSA was used to search the optimal parameters of SVM to identify different faults. Finally, the proposed coordinated VMD–RCMDE–SSA–SVM approach was verified and evaluated by the experimental data collected by the wind turbine drivetrain diagnostics simulator (WTDS). The results of the experiments demonstrate that the proposed approach not only identifies bearing fault types quickly and effectively but also achieves better performance than other comparative methods