Microarray,SAGE and their applications to cardiovascular diseases

The wealth of DNA data generated by the human genome project coupling with recently invented high-throughput gene expression profiling techniques has dramatically sped up the process for biomedical researchers on elucidating the role of genes in human diseases. One powerful method to reveal insight into gene functions is the systematic analysis of gene expression. Two popular high-throughput gene expression technologies, microarray and Serial Analysis of Gene Expression (SAGE) are capable of producing large amounts of gene expression data with the potential of providing novel insights into fundamental disease processes, especially complex syndromes such as cardiovascular disease, whose etiologies are due to multiple genetic factors and their interplay with the environment. Microarray and SAGE have already been used to examine gene expression patterns of cell-culture, animal and human tissues models of cardiovascular diseases. In this review, we will first give a brief introduction of microarray and SAGE     

基因表达系列分析(SAGE)的研究进展

基因表达系列分析方法（SAGE）是一种新的基因表达分析方法,它可同时分析数千种转录子的表达情况.SAGE不仅可以定量分析已知基因,还可分析未知的基因表达情况.SAGE为从分子水平阐明疾病的发病机制找到有效的治疗靶位和诊断标志创造了条件.     

Extract‐SAGE: An integrated platform for cross­analysis and GA­based selection of SAGE data

Serial analysis of gene expression (SAGE) is a powerful quantification technique for gene expression data. The huge amount of tag data in SAGE libraries of samples is difficult to analyze with current SAGE analysis tools. Data is often not provided in a biologically significant way for cross‐analysis and ‐comparison, thus limiting its application. Hence, an integrated software platform that can perform such a complex task is required. Here, we implement set theory for cross‐analyzing gene expression data among different SAGE libraries of tissue sources; up‐ or down‐regulated tissue‐specific tags can be identified computationally. Extract‐SAGE employs a genetic algorithm (GA) to reduce the number of genes among the SAGE libraries. Its representative tag mining will facilitate the discovery of the candidate genes with discriminating gene expression.     

Gene expression profiling of human diseases by serial analysis of gene expression

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.     

基因表达系列性分析技术及其应用

基因表达系列性分析（SAGE）是一种高通量的基因表达模式的研究技术,能够对特定细胞或组织中的大量转录本同时进行定量分析。本综述了SAGE技术的基本原理和实验流程以及近年来SAGE方法上的改进,同时介绍了该技术的一些应用研究实例和Internet上可资利用的SAGE数据库资源。     

Location cloning strategy for characterizing genetic defects in Huntington's disease and Alzheimer's disease

The recognition that DNA polymorphisms are widespread in the human genome and can be used as high quality genetic markers has introduced a new strategy for approaching inherited disorders for which no protein defect has been identified. Genetic linkage analysis can establish the chromosomal position of the genetic defect, providing a potential opportunity for isolating the disease gene and characterizing its product in the absence of any knowledge of its biochemical function. The first step in this location cloning approach has been successful in mapping the Huntington's disease gene to chromosome 4, and has implicated chromosome 21 as the site of a defect in familial Alzheimer's disease. An intensive effort is under way to narrow the region containing the disease gene and identify the defect in each of these disorders. This review will present the success that has been achieved and the problems that remain and will assess the current status of the location cloning strategy with regard to Huntington's disease and familial Alzheimer's disease.