A conditional knockout resource for the genome-wide study of mouse gene function

Gene targeting in embryonic stem cells has become the principal technology for manipulation of the mouse genome, offering unrivalled accuracy in allele design and access to conditional mutagenesis. To bring these advantages to the wider research community, large-scale mouse knockout programmes are producing a permanent resource of targeted mutations in all protein-coding genes. Here we report the establishment of a high-throughput gene-targeting pipeline for the generation of reporter-tagged, conditional alleles. Computational allele design, 96-well modular vector construction and high-efficiency gene-targeting strategies have been combined to mutate genes on an unprecedented scale. So far, more than 12,000 vectors and 9,000 conditional targeted alleles have been produced in highly germline-competent C57BL/6N embryonic stem cells. High-throughput genome engineering highlighted by this study is broadly applicable to rat and human stem cells and provides a foundation for future genome-wide efforts aimed at deciphering the function of all genes encoded by the mammalian genome.     

Identification of a serotonin/glutamate receptor complex implicated in psychosis

The psychosis associated with schizophrenia is characterized by alterations in sensory processing and perception. Some antipsychotic drugs were identified by their high affinity for serotonin 5-HT2A receptors (2AR). Drugs that interact with metabotropic glutamate receptors (mGluR) also have potential for the treatment of schizophrenia. The effects of hallucinogenic drugs, such as psilocybin and lysergic acid diethylamide, require the 2AR and resemble some of the core symptoms of schizophrenia. Here we show that the mGluR2 interacts through specific transmembrane helix domains with the 2AR, a member of an unrelated G-protein-coupled receptor family, to form functional complexes in brain cortex. The 2AR-mGluR2 complex triggers unique cellular responses when targeted by hallucinogenic drugs, and activation of mGluR2 abolishes hallucinogen-specific signalling and behavioural responses. In post-mortem human brain from untreated schizophrenic subjects, the 2AR is upregulated and the mGluR2 is downregulated, a pattern that could predispose to psychosis. These regulatory changes indicate that the 2AR-mGluR2 complex may be involved in the altered cortical processes of schizophrenia, and this complex is therefore a promising new target for the treatment of psychosis.     

Histone arginine methylation regulates pluripotency in the early mouse embryo

It has been generally accepted that the mammalian embryo starts its development with all cells identical, and only when inside and outside cells form do differences between cells first emerge. However, recent findings show that cells in the mouse embryo can differ in their developmental fate and potency as early as the four-cell stage. These differences depend on the orientation and order of the cleavage divisions that generated them. Because epigenetic marks are suggested to be involved in sustaining pluripotency, we considered that such developmental properties might be achieved through epigenetic mechanisms. Here we show that modification of histone H3, through the methylation of specific arginine residues, is correlated with cell fate and potency. Levels of H3 methylation at specific arginine residues are maximal in four-cell blastomeres that will contribute to the inner cell mass (ICM) and polar trophectoderm and undertake full development when combined together in chimaeras. Arginine methylation of H3 is minimal in cells whose progeny contributes more to the mural trophectoderm and that show compromised development when combined in chimaeras. This suggests that higher levels of H3 arginine methylation predispose blastomeres to contribute to the pluripotent cells of the ICM. We confirm this prediction by overexpressing the H3-specific arginine methyltransferase CARM1 in individual blastomeres and show that this directs their progeny to the ICM and results in a dramatic upregulation of Nanog and Sox2. Thus, our results identify specific histone modifications as the earliest known epigenetic marker contributing to development of ICM and show that manipulation of epigenetic information influences cell fate determination.     

Mass-balance ecosystem model of the East China Sea

Using the Ecopath mass-balance trophodynamic model, this paper analyzed the trophic levels, flows, food web structure and ecosystem maturity of the East China Sea, and identified ecologically important functional groups in the ecosystem. The model is based on fishery resource surveys of the East China Sea in 2000, studies on diet composition and global databases such as FishBase and the Sea Around Us Project Database. The results showed that trophic levels of the functional groups are between 2.86 and 4.37, with an average of 3.32. Anchocy (Engraulis japonicus), small fishes and benthic crustaceans such as shrimps and crabs are important groups in terms of the trophic structure and flow dynamics in the East China Sea. Energy flows of most groups are between specific trophic levels, except file fish (Thamnaconus spp.), pomfret (Pampus spp.) and cephalopods. Trophic transfer efficiency of levels II, III, IV and more than V are 11.8%, 21.1%, 17.4% and 22.1–22.5%, respectively. Effects of fishery – the largest ‘consumer’ of the ecosystem – are much stronger than those exerted by biological groups in the system. The model suggests that the current fishery can further reduce the complexity of the ecosystem. Evaluations of the system indices suggest that maturity of the ecosystem is low. The conclusion of this model indicates that it was the overfishing that caused the ecosystem of the East China Sea declined, which should be taken into account as a critical reference for fisheries management in the future.     

Bayesian Analysis of Asymmetric Stochastic Conditional Duration Model

This paper proposes Markov chain Monte Carlo methods to estimate the parameters and log durations of the correlated or asymmetric stochastic conditional duration models. Following the literature, instead of fitting the models directly, the observation equation of the models is first subjected to a logarithmic transformation. A correlation is then introduced between the transformed innovation and the latent process in an attempt to improve the statistical fits of the models. In order to perform one‐step‐ahead in‐sample and out‐of‐sample duration forecasts, an auxiliary particle filter is used to approximate the filter distributions of the latent states. Simulation studies and application to the IBM transaction dataset illustrate that our proposed estimation methods work well in terms of parameter and log duration estimation. Copyright © 2014 John Wiley & Sons, Ltd.