Expression and Chromosomal Mapping of Mouse Gpx2 Gene Encoding the Gastrointestinal Form of Glutathione Peroxidase, GPX-GI

GPX-GI is a cytosolic tetrameric Se-dependent glutathione peroxidase, similar in properties to GPX-1. Unlike the almost ubiquitous GPX-1, GPX-GI is mainly expressed in the epithelium of gastrointestinal tract. GPX-GI contributes to at least fifty percent of GPX activity in rodent small intestmal epithelium. The total GPX activity consists of at least 70% of selenium-dependent GPX activity in this compartment.By analyzing a panel of mouse mterspecies DNA from the Jackson Laboratory's backcross resource,we mapped Gpx2 gene to mouse chromosome 12 between D12Mit4 and D12Mit5, near the Ccs1 locus which contains a colon cancer susceptibility gene. A pseudogene, Gpx2-ps is mapped to mouse chromosome 7.Comparison of Gpx2 gene expression in three pairs of C57BL/6Ha and ICR/Ha mice which are respectively resistant and sensitive to dimethylhydrazine-induced colon cancer, we found a higher Gpx2 mRNA level in C57BL/6Ha colon than ICR/Ha colon. Interestingly, a lower level of GPX activity is found in the resistant strain of mice. Because GPX-1 has three times higher specific activity than GPX GI, our data suggest that the decreased GPX activity may result from a higher level of Gpx2 gene expression in those cells co-express GPx1 gene

北方岩溶矿床水文地质图编制理论和方法

以岩溶水系统理论为基础，将矿区富水性条件，矿井突水条件和矿井水实际资料，有机地结合起来，进行量化、分区，以新颖，直观的方法表现在图上，使图件具有很强的实用性。

Constructing protein-protein interaction network of hypertension with blood stasis syndrome via digital gene expression sequencing and database mining

OBJECTIVE： To construct a protein-protein interaction（PPI） network in hypertension patients with blood-stasis syndrome（BSS） by using digital gene expression（DGE） sequencing and database mining techniques.METHODS： DGE analysis based on the Solexa Genome Analyzer platform was performed on vascular endothelial cells incubated with serum of hypertension patients with BSS. The differentially expressed genes were f iltered by comparing the expression levels between the different experimental groups. Then functional categories and e nriched pathways of the unique genes for BSS were analyzed using Database for Annotation, Visualization and Integrated Discovery（DAVID） to select those in the enrichment pathways. I nterologous Interaction Database（I2D） was used to construct PPI networks with the selected genes for hypertension patients with BSS. The potential candidate genes related to BSS were identif ied by comparing the number of relationships among genes. Confi rmed by quantitative reverse transcription-polymerase chain reaction（q RTPCR）, gene ontology（GO） analysis was used to infer the functional annotations of the potential candidate genes for BSS.RESULTS： With gene enrichment analysis using DAVID, a list of 58 genes was chosen from the unique genes. The selected 58 genes were analyzed using I2 D, and a PPI network was constructed. Based on the network analysis results, candidate genes for BSS were identifi ed：DDIT3, JUN, HSPA8, NFIL3, HSPA5, HIST2H2 BE, H3F3 B, CEBPB, SAT1 and GADD45 A. Verif ied through qRT-PCR and analyzed by GO, the functional annotations of the potential candidate genes were explored.CONCLUSION： Compared with previous methodologies reported in the literature, the present DGE analysis and data mining method have shown a great improvement in analyzing BSS.

Transcriptome-wide association studies: a view from Mendelian randomization

Background:Genome-wide association studies(GWASs)have identified thousands of genetic variants that are associated with many complex traits.However,their biological mechanisms remain largely unknown.Transcriptome-wide association studies(TWAS)have been recently proposed as an invaluable tool for investigating the potential gene regulatory mechanisms underlying variant-trait associations.Specifically,TWAS integrate GWAS with expression mapping studies based on a common set of variants and aim to identify genes whose GReX is associated with the phenotype.Various methods have been developed for performing TWAS and/or similar integrative analysis.Each such method has a different modeling assumption and many were initially developed to answer different biological questions.Consequently,it is not straightforward to understand their modeling property from a theoretical perspective.Results:We present a technical review on thirteen TWAS methods.Importantly,we show that these methods can all be viewed as two-sample Mendelian randomization(MR)analysis,which has been widely applied in GWASs for examining the causal effects of exposure on outcome.Viewing different TWAS methods from an MR perspective provides us a unique angle for understanding their benefits and pitfalls.We systematically introduce the MR analysis framework,explain how features of the GWAS and expression data influence the adaptation of MR for TWAS,and re-interpret the modeling assumptions made in different TWAS methods from an MR angle.We finally describe future directions for TWAS methodology development.Conclusions:We hope that this review would serve as a useful reference for both methodologists who develop TWAS methods and practitioners who perform TWAS analysis.