Identification of differentially expressed genes like cofilin2 in growing collateral arteries

Arteriogenesis, the growth of pre-existing collateral arteries, can be induced in rabbits by occlusion of the femoral artery. In order to analyze the differential gene expression in arteriogenesis, cDNA of collateral arteries 24h after femoral occlusion or sham operation was subjected to suppression subtractive hybridization (SSH). We demonstrated an upregulation of the U6 snRNA binding protein Lsm5, cytochrome b, an expressed sequence tag, and the actin-depolymerizing factor cofilin2 mRNA in collateral arteries 24h after femoral ligation. For cofilin2, we also detected an increase in the protein level and a localization predominantly in smooth muscle cells of collaterals. Simultaneously with the upregulation of cofilin2 we found a downregulation of the alpha-smooth muscle actin mRNA in growing collateral arteries. In summary, our data showed an augmented expression level of genes contributing to different fundamental processes of arteriogenesis.     

Identification of differentially expressed genes in omental adipose tissues of obese patients by suppression subtractive hybridization

To identify differentially expressed genes between obese individuals and normal control, we have undertaken suppression subtractive hybridization (SSH). Omental adipose tissues were obtained via abdominal surgery for appendicitis in both 13 obese subjects [BMI (body mass index) >30 kg/m2] and 13 normal subjects (BMI >18 and <25 kg/m2). Following SSH, about one thousand clones were sequenced and found to derive from 426 different genes. These predominately expressed genes included genes involved in lipid metabolism, cytokines, signal transduction, GLUT4 translocation, cell cycle and growth, cytoskeleton, and others. Although more detailed analyses are necessary, it is anticipated that further study of genes identified will provide insights into their specific roles in the etiology of obesity.     

差异表达基因的分离策略

生命活动的各个进程伴随着不同基因的选择性开启和关闭。如何有效地分离克隆各种差异表达的基因,成为分子生物学研究的一个努力方向,大量差异基因分离策略因之问世。本文扼要介绍了近年来发展的几种主要分离策略,并详细介绍一种新的差异基因分离方法--抑制差减杂交。     

Ranking analysis of microarray data: a powerful method for identifying differentially expressed genes

Microarray technology provides a powerful tool for the expression profile of thousands of genes simultaneously, which makes it possible to explore the molecular and metabolic etiology of the development of a complex disease under study. However, classical statistical methods and technologies fail to be applicable to microarray data. Therefore, it is necessary and motivating to develop powerful methods for large-scale statistical analyses. In this paper, we described a novel method, called Ranking Analysis of Microarray Data (RAM). RAM, which is a large-scale two-sample t-test method, is based on comparisons between a set of ranked T statistics and a set of ranked Z values (a set of ranked estimated null scores) yielded by a "randomly splitting" approach instead of a "permutation" approach and a two-simulation strategy for estimating the proportion of genes identified by chance, i.e., the false discovery rate (FDR). The results obtained from the simulated and observed microarray data show that RAM is more efficient in identification of genes differentially expressed and estimation of FDR under undesirable conditions such as a large fudge factor, small sample size, or mixture distribution of noises than Significance Analysis of Microarrays.