A new method for gene discovery in large-scale microarray data

Microarrays are an effective tool for monitoring genome-wide gene expression levels. In current microarray analyses, the majority of genes on arrays are frequently eliminated for further analysis because the changes in their expression levels (ratios) are considered to be not significant. This strategy risks failure to discover whole sets of genes related to a quantitative trait of interest, which is generally controlled by several loci that make various contributions. Here, we describe a high-throughput gene discovery method based on correspondence analysis with a new index for expression ratios [arctan (1/ratio)] and three artificial marker genes. This method allows us to quickly analyze the whole microarray dataset and discover up-/down-regulated genes related to a trait of interest. We employed an example dataset to show the theoretical advantage of this method. We then used the method to identify 88 cancer-related genes from a published microarray data from patients with breast cancer. This method also allows us to predict the phenotype of a given sample from the gene expression profile. This method can be easily performed and the result is also visible in 3D viewing software that we have developed.     

Insights into the relation between mrna and protein expression patterns: II. Experimental observations in Escherichia coli

There is a need for improved appreciation of the importance of genome-wide mRNA and protein expression measurements and their role in understanding translation and in relation to genome-wide mathematical frameworks for gene expression regulation. We investigated the use of a high-density microarray technique for mRNA expression analysis and a two-dimensional protein electrophoresis-tandem mass spectrometry method for protein analysis to monitor changes in gene expression. We applied these analytical tools in the context of an environmental perturbation of Escherichia coli cells-the addition of varying amounts of IPTG. We also tested the application of these tools to the study of a genetic perturbation of Escherichia coli cells-the ability of certain strains to hypersecrete the hemolysin protein. We observed a lack of correspondence between mRNA and protein expression profiles. Although our data do not include measurements on all expressed genes (because the ability to measure protein expression profiles is limiting), we observed that the qualitative and quantitative behavior of the measurements of a subset of expressed genes is similar to the behavior of the entire system. The change in observed average mRNA and protein amplification factors for 77 and 52 genes coincided with the observed change in mRNA amplification factor for the entire system. Furthermore, we found that the use of relative changes in expression could be used to elucidate mechanisms of gene expression regulation for the system studied, even when measurements were made on a small subset of the system.     

6天龄与10天龄大鼠的睾丸组织的基因差异表达

通过基因芯片技术,利用Roche-NimbleGen公司制作的大鼠12×135K全基因组表达谱芯片,对日龄为6d和10d的大鼠睾丸组织进行全基因组表达差异分析。结果显示:具有2倍以上的差异表达基因有4298个,其中表达上调的基因共1878个,表达下调的基因共2420个。这些差异表达的基因中有3154个基因具有基因本体注释,参与了154个生物学通路。进一步分析表明具有8倍以上差异表达的基因有13个,这些基因参与了生物学过程、细胞组分和分子功能等基因本体分类,进一步选择3个差异表达的基因,LOC686076、Cxcl6和Trib3,做了实时定量RT-PCR检测。其结果趋势与芯片数据一致。因此,我们初步认为精原干细胞的发生与增殖在大鼠早期的发育过程中已经有大量的基因参与,是一个多基因协调表达的过程。