Expression Profile Analysis of Neurodegenerative Disease: Advances in Specificity and Resolution

Microarray technology has become a common tool for developing expression profiles. Initially used in the analysis of cells lines and homogeneous tissues, this platform has been applied to more diverse tissues, such as the brain. Several neural disorders have already been profiled by microarrays using relatively large amounts of tissue. This data has unveiled many genes with differential expression between normal and diseased tissue that could potentially be used as gene markers for these afflictions. Because of the heterogeneity of the CNS, it is likely that small differences between gene expression in these studies would be enhanced by the sampling of a subset of cells based on these newly characterized gene markers. Subtraction of normal, unaffected cells from the sample may also result in a more accurate profile of a diseased cell. Expression profile studies from several neuropathological states are presented, with emphasis placed on those studies using small samples of cellular material and those using specialized methods of cell isolation and RNA amplification.     

转录后基因沉默的机制及其应用

确定导致转录后基因沉默的原因,探索在转基因植物研究中避免基因沉默的对策。方法是将转基因沉默分为转录水平的沉默和转录后水平的沉默,分别对RNA阈值模型、异位配对和异常RNA模型、双连RNA模型等几种导致转录后基因沉默模型的分析。结果确定了转基因沉默抑制现象和转录后基因沉默的形成机制,以及转录后基因沉默理论和实践意义。提出了利用RNAi等技术进行基因功能鉴定和利用基因沉默进行病毒防治的策略。