Multi-Omics Study on the Molecular Mechanisms of Tetraodon Nigroviridis Resistance to Exogenous Vibrio Parahaemolyticus Infection

Vibrio parahaemolyticus is an important marine pathogen that causes inflammation and even death in teleost fishes. It has brought significant economic losses to the aquaculture industry as well as high risks to the sustainable development of marine fisheries. In the present study, the fish Tetraodon nigroviridis and the bacterial pathogen Vibrio parahaemolyticus were used to explore the molecular mechanisms underlying the immune response of T. nigroviridis to V. parahaemolyticus exogenous infection. The microRNA (miRNA)–mRNA–protein omics and corresponding experimental validation, followed by comparative analysis, revealed several differentially expressed genes involved in various components of the immune system, including the following: complement system, chemokines, lysosomes, phagocytes, B-cell receptor signaling pathway, T-cell receptor signaling pathway, Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, and phospholipid metabolism, among others. Especially, the complements component 3 (C3) gene and protein expression levels were significantly higher after V. parahaemolyticus infection, and miRNAs targeting C3, including mir-6089-y, mir-460-y, and mir-1584-x, were significantly down-regulated. The gene and protein expression levels of complement 1 subunit qA (C1qA) were significantly down-regulated, while mir-203 targeting C1qA was significantly up-regulated. Overall, four complement genes (C1qA, IG, C3, and C5), which are key genes in the classical pathway of complement system activation for inflammatory response, were identified. Evolutionary analysis suggested that T. nigroviridis, acquired an increased ability to recognize pathogens by evolving a more complex complement system than terrestrial vertebrates. In addition, quantitative real-time polymerase chain reaction showed high consistency with the obtained multi-omics results, indicating the reliability of the sequencing data generated in the present study. In summary, our findings can serve as a fundamental basis for further in-depth multi-omics studies on the inflammatory processes of aquatic pathogens hindering fish sustainable production

Developing Single Nucleotide Polymorphisms for Identification of Cod Products by RAD-Seq

The increase in the rate of seafood fraud, particularly in the expensive fishes, forces us to verify the identity of marine products. Meanwhile, the definition of cod lacks consistency at the international level, as few standards and effective application methods are capable of accurately detecting cod species. Genetic fingerprinting is important for both certifying authenticity and traceability of fish species. In this study, we developed a method that combines DNA barcoding and the restriction-site associated DNA sequencing (RAD-Seq) approach for the identification of cod products. We first obtained 6941 high-quality single nucleotide polymorphism (SNP)s from 65.6 gigabases (Gb) of RAD-Seq raw data, and two sequences that contain SNPs were finally used to successfully identify three different cod product species, which are Atlantic cod (Gadus morhua), Greenland turbot (Reinhardtius hippoglossoides), and Patagonian toothfish (Dissostichus eleginoides). This SNP-based method will help us to identify the products, which are sold under the name of “Xue Yu” (Cod) in China, and works in parallel with existing fish identification techniques to establish an efficient framework to detect and prevent fraud at all points of the seafood supply chain

A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA

A challenge for face recognition is variation, such as due to lighting or facial expression differences. To solve this problem, we fuses bidirectional two-dimensional linear discriminant analysis (2DLDA) feature by adaboost technique and propose a novel recognition method called AB2DLDA in this paper. This method can perform well with small number of samples. In this paper, firstly we analyze complementarity for vertical direction of 2DLDA and horizontal direction of E2DLDA. Then we use adaboost to design a classifier, which improves recognition performance by fusing 2DLDA and E2DLDA. Finally, our method is tested on AR face databases. Experimental results show that our method functions with good recognition accuracy and robustness

Network Structure and Properties of Lithium Aluminosilicate Glass

Based on lithium aluminosilicate glass, the composition of glass was optimized by replacing SiO2 with B2O3, and the influence of glass composition on structure and performance was studied. With the increase in B2O3 concentrations from 0 to 6.5 mol%, Al2O3 always existed in the form of four-coordinated [AlO4] in the network structure, and B2O3 mainly entered the network in the form of four-coordinated [BO4]. The content of Si-O-Si linkages (Q4(0Al)) was always dominant. The incorporation of boron oxide improved the overall degree of polymerization and connectivity of the lithium aluminosilicate glass network structure. An increase in the degree of network polymerization led to a decrease in the thermal expansion coefficient of the glass and an increase in Vickers hardness and density. The durability of the glass in hydrofluoric acid and NaOH and KOH solutions was enhanced overall

Chromosome-Level Genome Assembly and Transcriptome Comparison Analysis of Cephalopholis sonnerati and Its Related Grouper Species

The tomato hind, Cephalopholis sonnerati, is a bottom-dwelling coral reef fish, which is widely distributed in the Indo-Pacific and Red Sea. C. sonnerati also features complex social structures and behaviour mechanisms. Here, we present a high-quality, chromosome-level genome assembly for C. sonnerati that was derived using PacBio sequencing and Hi-C technologies. A 1043.66 Mb genome with an N50 length of 2.49 Mb was assembled, produced containing 795 contigs assembled into 24 chromosomes. Overall, 97.2% of the complete BUSCOs were identified in the genome. A total of 26,130 protein-coding genes were predicted, of which 94.26% were functionally annotated. Evolutionary analysis revealed that C. sonnerati diverged from its common ancestor with E. lanceolatus and E. akaara approximately 41.7 million years ago. In addition, comparative genome analyses indicated that the expanded gene families were highly enriched in the sensory system. Finally, we found the tissue-specific expression of 8108 genes. We found that these tissue-specific genes were highly enriched in the brain. In brief, the high-quality, chromosome-level reference genome will provide a valuable genome resource for studies of the genetic conservation, resistance breeding, and evolution of C. sonnerati

An SNP-Based Genetic Map and QTL Mapping for Growth Traits in the Red-Spotted Grouper (Epinephelus akaara)

The red-spotted grouper (Epinephelus akaara) is one of the most commercially important aquatic species in China. However, its seedstock has low larval survival rates, and its stability is confronted with the danger of overexploitation. In this study, a high-density genetic map was constructed using 3435 single nucleotide polymorphisms (SNPs) from 142 first generation (F1) full-sib offspring and two parents of a red-spotted grouper population. The total genetic length of the map was 2300.12 cM with an average intermarker distance of 0.67 cM. Seventeen genome-wide significant quantitative trait loci (QTLs) for growth-related traits were detected on 24 linkage groups, including 5 QTLs for full length, 7 QTLs for body length, and 5 QTLs for body weight. The contribution values of explained phenotypic variance ranged from 10.7% to 12.9%. Moreover, 13 potential candidate genes for growth-related traits were identified. Collectively, these findings will be useful for conducting marker-assisted selection of the red-spotted grouper in future studies