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A 12-week feeding trial was conducted to quantify the dietary lysine requirement of juvenile silver pompano with an initial average weight of 6.28 g reared in indoor recirculatory system. Six treatment diets were designed with isonitrogenous, isolipidic and isoenergetic diets. (42% CP, 6% CL and 4.28 kcal g −1 GE) were formulated with graded levels of lysine (1.52, 1.85, 2.21, 2.49, 2.74 and 2.98 g/100 g, dry diet). Equal amino acid nitrogen was maintained by replacing lysine with nonessential amino acid mixture. Fish were randomly stocked, in triplicate groups, in 180 L indoor glass rectangular tanks with recirculatory system and fed to apparent satiation over two feedings at 10:00 and 16:00 h daily during the experimental period. The results indicated that there were significant differences in growth and feed utilization among the treatments. Fish fed diets with lysine in different treatments showed high survival rate (95-100%). Maximum weight gain (WG), specific growth rate (SGR) and protein efficiency ratio (PER) occurred at 2.21% dietary lysine. The hepatosomatic index (HSI), viscerosomatic index (VSI) and crude protein content in whole body were significantly affected by dietary lysine levels. There were significant differences (P < .05) in total serum protein levels and erythrocyte count in fish fed diets with different dietary lysine levels. No significant differences were observed in the levels of serum glucose, triglycerides and creatinine levels among the treatments. In the present study, optimization of fitted quadratic regression of weight gain%, SGR, PER and FER on lysine in diet revealed that the optimum lysine requirement of silver pompano was in the range of 2.40-2.45% of dry diet (5.71-5.83% of dietary crude protein).

Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is statistically significant. To identify differentially expressed genes between two conditions, it is important to find statistical distributional property of the data to approximate the nature of differential genes. In the present study, the focus is mainly to investigate the differential gene expression analysis for sequence data based on compound distribution model. This approach was applied in RNA-seq count data of Arabidopsis thaliana and it has been found that compound Poisson distribution is more appropriate to capture the variability as compared with Poisson distribution. Thus, fitting of appropriate distribution to gene expression data provides statistically sound cutoff values for identifying differentially expressed genes.