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Accumulating evidence indicates a close relationship between oxidative stress and growth rate in fish. However, the underlying mechanisms of this relationship remain unclear. This study evaluated the combined effect of dietary antioxidants and growth hormone (GH) on the liver and the muscle redox status of Atlantic salmon. There were two sequential experimental phases (EP) termed EP1 and EP2, each lasting for 6 weeks. In EP1, Atlantic salmon were fed either low-(L, 230 mg/kg ascorbic acid (Asc), 120 mg/kg α-tocopherol (α-TOH)), or high-(H, 380 mg/kg Asc, 210 mg/kg α-TOH)vitamin diets. The vitamins were supplemented as stable forms and the feeding was continued in EP2. In EP2, half of the fish were implanted with 3 μL per g body weight of recombinant bovine GH (Posilac®, 1 mg rbGH g BW−1) suspended in sesame oil, while the other half were held in different tanks and sham-implanted with similar volumes of the sesame oil vehicle. Here, we show that increasing high levels of vitamin C and E (diet H) increased their content in muscle and liver during EP1. GH implantation decreased vitamin C and E levels in both liver and muscle but increased malondialdehyde (MDA) levels only in the liver. GH also affected many genes and pathways of antioxidant enzymes and the redox balance. Among the most consistent were the upregulation of genes coding for the NADPH oxidase family (NOXs) and downregulation of the oxidative stress response transcription factor, nuclear factor-erythroid 2-related factor 2 (nrf2), and its downstream target genes in the liver. We verified that GH increases the growth rate until the end of the trail and induces an oxidative effect in the liver and muscle of Atlantic salmon. Dietary antioxidants do lower oxidative stress but have no effect on the growth rate. The present study is intended as a starting point to understand the potential interactions between growth and redox signaling in fish.

Micronutrients (vitamins and minerals) have been less well studied compared to macronutrients (fats, proteins, and carbohydrates) although they play important roles in growth, metabolism, and maintenance of tissues. Hence, there is growing interest to understand the influence of micronutrients across various aspects in nutritional research. In the last two decades, aquaculture feeds have been shifted to containing more plant-based materials to meet the increasing demand and maintain the sustainability in the industry. In cultured fish, changing raw materials in feeds alters the requirement levels of micronutrients. A recent whole life cycle feeding trial of Atlantic salmon (Salmo salar) with graded levels of micronutrient packages has concluded that the levels of several B-vitamins and microminerals need to be increased from the current recommendation levels for optimal growth and fish welfare when plant-based diets are used. Here, we show the effect of micronutrient supplementation on transcriptional and epigenetic regulation by using liver samples from the same feeding trial. Specifically, our aim is to reveal the mechanisms of altered cell metabolism, which results in improved growth performance by micronutrient surpluses, at gene expression and DNA methylation levels. Our results strongly indicate that micronutrient supplementation suppresses gene expression in lipid metabolism in a dose-dependent manner and broadly affects DNA methylation in cell adhesion and cell signalling. In particular, it increases DNA methylation levels on the acetyl-CoA carboxylase alpha promoter in a concentration-dependent manner, which further suggests that acetyl-CoA carboxylase alpha is an upstream epigenetic regulator controlling its downstream lipid biosynthesis activities. This study demonstrates a comprehensive analysis to reveal an important role of micronutrients in lipid metabolism through epigenetic control of gene expression.

The Atlantic salmon aquaculture industry relies on adjustments of female broodstock spawning season to meet the demand for delivery of embryos outside the natural spawning season. Earlier results from zebrafish have shown that parental micronutrient status program offspring metabolism. Therefore, the main hypothesis of this study was to investigate if out-of-season (off-season) broodstock (spawning in June, in land-based recirculation systems) and their offspring deviate in micronutrient status when compared to broodstock and offspring from normal spawning season. Both seasons of female Atlantic salmon broodstock were fed the same diet and starved for approximately the same time interval prior to spawning. We compared nutrients related to the 1C metabolism (vitamin B12, folate, vitamin B6, methionine), free amino acids (FAAs) and lipid classes in broodstock muscle and liver tissues, and during offspring ontogeny. In general, the off-season broodstock showed higher levels of folate, vitamin B6 and selected FAAs in muscle tissue, and higher levels of folate and lipids (cholesterol and sphingomyelin) in liver tissue compared to normal-season. Furthermore, embryos from off-season had reduced amounts of all the measured lipid classes, like cholesterol and sphingomyelin, and lower levels of one type of folate and changes in FAAs and N-metabolites. We discovered significant differences between the seasons in mRNA levels of genes controlling fatty acid synthesis and 1C metabolism in both broodstock liver and offspring. Moreover, for genes controlling the methylation of DNA; both maintenance and de novo DNA methyltransferases (DNMTs) were expressed at higher levels in off-season compared to normal-season offspring. Our results show, in general that normal spawning season broodstock allocated more nutrients to eggs than off-season. Our results indicate a potential for improved maturation for off-season group to obtain a higher offspring growth potential, and this argues for a reassessment of the nutritional influence from broodstock to offspring and the consequences through nutritional programming.

MicroRNAs (miRNAs) play a key role in regulating mRNA expression, and individual miRNAs have been proposed as diagnostic and therapeutic candidates. The identification of such candidates is complicated by the involvement of multiple miRNAs and mRNAs as well as unknown disease topology of the miRNAs. Here, we investigated if disease-associated miRNAs regulate modules of disease-associated mRNAs, if those miRNAs act complementarily or synergistically, and if single or combinations of miRNAs can be targeted to alter module functions. We first analyzed publicly available miRNA and mRNA expression data for five different diseases. Integrated target prediction and network-based analysis showed that the miRNAs regulated modules of disease-relevant genes. Most of the miRNAs acted complementarily to regulate multiple mRNAs. To functionally test these findings, we repeated the analysis using our own miRNA and mRNA expression data from CD4+ T cells from patients with seasonal allergic rhinitis. This is a good model of complex diseases because of its well-defined phenotype and pathogenesis. Combined computational and functional studies confirmed that miRNAs mainly acted complementarily and that a combination of two complementary miRNAs, miR-223 and miR-139-3p, could be targeted to alter disease-relevant module functions, namely, the release of type 2 helper T-cell (Th2) cytokines. Taken together, our findings indicate that miRNAs act complementarily to regulate modules of disease-related mRNAs and can be targeted to alter disease-relevant functions.

Summary The precision–recall plot is more informative than the ROC plot when evaluating classifiers on imbalanced datasets, but fast and accurate curve calculation tools for precision–recall plots are currently not available. We have developed Precrec, an R library that aims to overcome this limitation of the plot. Our tool provides fast and accurate precision–recall calculations together with multiple functionalities that work efficiently under different conditions. Availability and Implementation Precrec is licensed under GPL-3 and freely available from CRAN (https://cran.r-project.org/package=precrec). It is implemented in R with C ++. Supplementary information Supplementary data are available at Bioinformatics online.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that can regulate many genes by base pairing to sites in mRNAs. The functionality of miRNAs overlaps that of short interfering RNAs (siRNAs), and many features of miRNA targeting have been revealed experimentally by studying miRNA-mimicking siRNAs. This review outlines the features associated with animal miRNA targeting and describes currently available prediction tools., Comment: A review paper on miRNA targets, 7 pages

Background: Despite experiments showing that the number of microRNA (miRNA) target sites is critical for miRNA targeting, most existing methods focus on identifying individual miRNA target sites and do not model contributions of multiple target sites to miRNA regulation. To address this possible fault, we developed a miRNA target prediction model that recognizes the individual characteristics of functional binding sites and the global characteristics of miRNA-targeted mRNAs. Results: Benchmark experiments showed that this two-step model generally had a higher overall performance than other established miRNA target prediction algorithms and that the model was especially suited to identify true miRNA targets among genes that all contain conserved target sites. Conclusions: This improved performance could partly be explained by the model not relying on conservation when predicting targets. The critical factors for the model’s performance, however, were mRNA-level features that characterized the number and strength of individual target sites within the mRNA. The model is available for online predictions or as pre-computed predictions on the human genome http://tare.medisin.ntnu.no/mirna_target. © 2010 Saito and Sætrom; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background MicroRNA (miRNA) target genes tend to have relatively long and conserved 3' untranslated regions (UTRs), but to what degree these characteristics contribute to miRNA targeting is poorly understood. Different high-throughput experiments have, for example, shown that miRNAs preferentially regulate genes with both short and long 3' UTRs and that target site conservation is both important and irrelevant for miRNA targeting. Results We have analyzed several gene context-dependent features, including 3' UTR length, 3' UTR conservation, and messenger RNA (mRNA) expression levels, reported to have conflicting influence on miRNA regulation. By taking into account confounding factors such as technology-dependent experimental bias and competition between transfected and endogenous miRNAs, we show that two factors - target gene expression and competition - could explain most of the previously reported experimental differences. Moreover, we find that these and other target site-independent features explain about the same amount of variation in target gene expression as the target site-dependent features included in the TargetScan model. Conclusions Our results show that it is important to consider confounding factors when interpreting miRNA high throughput experiments and urge special caution when using microarray data to compare average regulatory effects between groups of genes that have different average gene expression levels.