Transgenic models as tools for studying the regulation of human renin expression

Transgenic mice and rats have become popular tools to study the regulation of gene expression and the consequences of protein over-production. Over the past decade, numerous transgenic models have been developed to study the mechanisms of human renin gene expression and the participation of the renin-angiotensin system in the development of hypertension. Herein we will provide an overview of what has been learned from the use of transgenic models for studying the human renin gene.     

Mouse models of human single gene disorders. I: Nontransgenic mice.

Mouse models of human genetic disorders provide a valuable resource for investigating the pathogenesis of genetic disease and for testing potential therapies. The high degree of resolution of linkage mapping in the mouse allows mutant phenotypes to be mapped precisely which, combined with the accurate definition of areas of homology between the mouse and human genomes, greatly facilitates the identification of mouse models. We describe here mouse models of human single gene disorders dividing them into three categories depending on the information available; phenotypic similarities, comparative mapping and identification of the underlying genetic lesion.     

Empirical Bayesian models for analysing molecular serotyping microarrays

Background  

Microarrays offer great potential as a platform for molecular diagnostics, testing clinical samples for the presence of numerous biomarkers in highly multiplexed assays. In this study applied to infectious diseases, data from a microarray designed for molecular serotyping of Streptococcus pneumoniae was used, identifying the presence of any one of 91 known pneumococcal serotypes from DNA extracts. This microarray incorporated oligonucleotide probes for all known capsular polysaccharide synthesis genes and required a statistical analysis of the microarray intensity data to determine which serotype, or combination of serotypes, were present within a sample based on the combination of genes detected.     

Genetic mouse models to investigate cell cycle regulation

Early studies on cell cycle regulation were based on experiments in model systems (Yeast, Xenopus, Starfish, Drosophila) and have shaped the way we understand many events that control the cell cycle. Although these model systems are of great value, the last decade was highlighted by studies done in human cells and using in vivo mouse models. Mouse models are irreplaceable tools for understanding the genetics, development, and survival strategies of mammals. New developments in generating targeting vectors and mutant mice have improved our approaches to study cell cycle regulation and cancer. Here we summarize the most recent advances of mouse model approaches in dissecting the mechanisms of cell cycle regulation and the relevance to human disease. W. Li and S. Kotoshiba contributed equally.     

Mouse models as tools for dissecting disorders of lipoprotein metabolism

The overexpression of proteins as transgenes or by adenovirus-mediated gene transfer as well as the disruption of genes by homologous DNA recombination in the mouse provide powerful tools to dissect the role of individual proteins in complex biological pathways. These and similar techniques have been widely used to characterize the function of most of the players involved in lipoprotein metabolism. These models are expected to greatly advance the finding of new therapeutic strategies for the treatment of disorders of lipoprotein metabolism.     

Transgenic animals as models for human disease

Transgenic animals, especially mice, have been used quite extensively as models for various human diseases. At first, the level of scientific inquiry was driven by the need to establish the model. In many cases, these models may be considered quite crude because of their limitations. More recently, transgenic models of disease have become more refined and are currently being used to study the pathological mechanisms behind the disease rather than to just provide a model of the disease. Using some examples from the recent literature, we will document the current level and complexity of inquiry using transgenic animals. New techniques and techniques that may prove promising will be discussed. This revised version was published online in August 2006 with corrections to the Cover Date.     

Stochastic models for inferring genetic regulation from microarray gene expression data

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information.     

Genetic linkage studies of human neurodegenerative disorders.

Recombinant DNA technology has the ability to delineate the causes of several neurodegenerative disorders. Genetic linkage studies have been used successfully to localize gene defects and it is likely that in the near future the exact loci will be determined.     

Genetic dissection of gene regulation in multiple mouse tissues

The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.     

Mouse models for psychiatric disorders

Genes involved in psychiatric disorders are difficult to identify, and those that have been proposed so far remain ambiguous. As it is unrealistic to expect the development of, say, a ‘schizophrenic’ or ‘autistic’ mouse, mice are unlikely to have the same role in gene identification in psychiatry as circling mice did in the discovery of human deafness genes. However, many psychiatric disorders are associated with intermediate phenotypes that can be modeled and studied in mice, including physiological or anatomical brain changes and behavioral traits. Mouse models help to evaluate the effect of a human candidate gene mutation on an intermediate trait, and to identify new candidate genes. Once a gene or pathway has been identified, mice are also used to study the interplay of different genes in that system.