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The Arabidopsis root transcriptome by serial analysis of gene expression. Gene identification using the genome sequence 总被引:5,自引:0,他引:5
Fizames C Muños S Cazettes C Nacry P Boucherez J Gaymard F Piquemal D Delorme V Commes T Doumas P Cooke R Marti J Sentenac H Gojon A 《Plant physiology》2004,134(1):67-80
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In an attempt to understand the molecular bases of gastric cancer progression, we have analyzed the differentially expressed genes in gastric cancer by SAGE. Four SAGE cDNA tag libraries were constructed from two sets of gastric cancer and normal tissues and 241,127 tags were obtained. By comparing the tags from cancer and normal tissues, 414 differentially expressed tags, representing 383 genes, were identified in cancer tissues (p = 0.01). Of the 414 tags, 50 tags were previously unidentified and potentially novel genes. Although each gastric cancer tissue revealed more than 200 differentially expressed genes compared to the respective normal tissue, the number of genes with consistent regulation patterns in both cancer tissues was 51: 12 up-regulated and 39 down-regulated genes. The genes that showed consistent regulation patterns included well-known genes such as Trefoil factor 3, RegIV, gastric intrinsic factor, and lactotransferrin as well as a few novel candidates. Interestingly, the expression of several genes, such as osteoglycin, prostate stem cell antigen, and histone deacetylase 3, was variable in the two normal tissues but similar in the cancer tissues. The expression profiles of these genes in normal tissues, possibly due to genetic background, could greatly affect individual sensitivity to cancer development and/or progression. The genes identified in this study will provide useful target genes for diagnosis and molecular treatment of gastric cancer. 相似文献
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Correct identification of genes from serial analysis of gene expression tag sequences 总被引:3,自引:0,他引:3
SAGE (serial analysis of gene expression) is a remarkable technique for genome-wide analysis of gene expression. It is crucial to understand the extent to which SAGE can accurately indicate a gene or expressed sequence tag (EST) with a single tag. We analyzed the effect of the size of SAGE tag on gene identification. Our observation indicates that SAGE tags are in general not long enough to achieve the degree of uniqueness of identification originally envisaged. Our observations also indicate that the limitation of using SAGE tag to identify a gene can be overcome by converting SAGE tags into longer 3' EST sequences with the generation of longer cDNA fragments from SAGE tages for gene identification (GLGI) method. 相似文献
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The impact of SNPs on the interpretation of SAGE and MPSS experimental data 总被引:2,自引:0,他引:2
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Silva AP De Souza JE Galante PA Riggins GJ De Souza SJ Camargo AA 《Nucleic acids research》2004,32(20):6104-6110
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Transcriptomes for serial analysis of gene expression 总被引:1,自引:0,他引:1
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Huang J Miao X Jin W Couble P Mita K Zhang Y Liu W Zhuang L Shen Y Keime C Gandrillon O Brouilly P Briolay J Zhao G Huang Y 《Genomics》2005,86(2):233-241
The silkworm Bombyx mori is one of the most economically important insects and serves as a model for Lepidoptera insects. We used serial analysis of gene expression (SAGE) to derive profiles of expressed genes during the developmental life cycle of the silkworm and to create a reference for understanding silkworm metamorphosis. We generated four SAGE libraries, one from each of the four developmental stages of the silkworm. In total we obtained 257,964 SAGE tags, of which 39,485 were unique tags. Sorted by copy number, 14.1% of the unique tags were detected at a median to high level (five or more copies), 24.2% at lower levels (two to four copies), and 61.7% as single copies. Using a basic local alignment search tool on the EST database, 35% of the tags matched known silkworm expressed sequence tags. SAGE demonstrated that a number of the genes were up- or down-regulated during the four developmental phases of the egg, larva, pupa, and adult. Furthermore, we found that the generation of longer cDNA fragments from SAGE tags constituted the most efficient method of gene identification, which facilitated the analysis of a large number of unknown genes. 相似文献
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