BackgroundSystematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE) are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish.ResultsRNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution.ConclusionThis study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host-pathogen interactions and evolutionary history of immunogenetics from fish to mammals.

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We study the impact of the US quantitative easing (QE) on both the emerging and advanced economies, estimating a global vector error-correction model (GVECM) and conducting counterfactual analyses. We focus on the effects of reductions in the US term and corporate spreads. First, US QE measures reducing the US corporate spread appear to be more important than lowering the US term spread. Second, US QE measures might have prevented episodes of prolonged recession and deflation in the advanced economies. Third, the estimated effects on the emerging economies have been diverse but often larger than those recorded in the US and other advanced economies. The heterogeneous effects from US QE measures indicate unevenly distributed benefits and costs.

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China has a dual-track interest-rate system: bank deposit and lending rates are regulated while money and bond rates are market-determined. The central bank also imposes an indicative target, which may not be binding at all times, for total credit in the banking system. We develop and calibrate a theoretical model to illustrate the conduct of monetary policy within the framework of dualtrack interest rates and a juxtaposition of price-and quantity-based policy instruments. We model the transmission of monetary policy instruments to market interest rates, which, together with the quantitative credit target in the banking system, ultimately are the means by which monetary policy affects the real economy. The model shows that market interest rates are most sensitive to changes in the benchmark deposit interest rates, significantly responsive to changes in the reserve requirements, but not particularly reactive to open market operations. These theoretical results are verified and supported by both linear and GARCH models using daily money and bond market data. Overall, the findings of this study help us to understand why the central bank conducts monetary policy in China the way it does, using a combination of price and quantitative instruments with differing degrees of potency in terms of their influence on the cost of credit.