Application And Improvement Of High Throughput Gene Screening Technology

Background and ObjectivesGene expression and regulation is a complicated process. The realization of biological function of cells in special phase and period is based on the regulation of many genes expressed in cells at the special status. Clarify the gene expression profile in cells in special functional state will help to understand the mechanism of disease. As one of the best high throughput gene screening technology, Serial Analysis of Gene Expression (SAGE) allows both qualitative and quantitative analysis of previously unknown transcripts and is largely be used in disease gene expression profile research. Hence, understand the advantages and the drawbacks of SAGE will play a significant role on disease genome research. Allograft rejection is a leading cause for the failure of allotransplantation. CD4+T cells play critical roles in this process. Identifying the genes alternatively expressed in CD4+T cells during allograft rejection will provide significant information for understanding the mechanism of allograft rejection. Hence, we choose to construct the allotransplantation CD4+T cells SAGE library in this study. Through the application and the analysis of this library, we plan to clarify the advantages and the drawbacks of SAGE when using it as the method to research disease related genes.Based on the advantages of high throughput, high sensitivity, high reproducibility, quantitative analysis of transcriptome and its ability to find unknown gene, SAGE has been widely applied to analyze gene expression profile of the specific cells in specific biological status and more than thousands of SAGE-related studies have been published since the mid-1990s. However, the low specificity for matching SAGE tags to their original transcripts which coming from the nature of SAGE makes gene identification for differentially expressed tags becomes to the big challenge of SAGE. In view of this factor, the transcript or gene assigned should be verified by another approach. Of the limited methods available, GLGI (generation of long cDNA from SAGE tags for gene identification) can convert tag into a 3'-EST by extending the tag to the 3'end of the corresponding cDNA template. The increased length provides higher specificity to determine the gene origin of the tag, but the coverage of the tags which can be convert into 3'-EST are not big. Therefore, developing new genomics techniques is needed to provide more powerful tool for disease related gene research.The newly emerged next-generation DNA sequencing technology provides new tools to analyze chromosomal structural aberrations, such as Ditags Genome Scanning (DGS), which allows screening genome at kb resolution level. However, the DNA preparing process of the original DGS is very complicated which limited the use of DGS largely. In "Part two" of this dissertation, we continuously revised the original DGS and successfully created revised in vivo DGS, simplified in vitro DGS.Although revised DGS can be used to study disease genome at large scale, the short tag length cannot supply good region for PCR primer design. In part three, we constructed the technique named large-scale sequencing restriction DNA fragments for higher resolution genome studies and aimed to solve this problem.MethodsPart One Construction and analysis of allotransplantation CD4+T cell SAGE libraryIn this study, we constructed allotransplantation and isotransplantation CD4+T cells mRNA tag library by using SAGE. Statistical analysis identified differential expressed SAGE tags. By matching to NCBI SAGEmap reliable database we identified CD4+T cell allotransplantation related low copy single matched genes, and by using GLGI we identified the genes of multiple matched tags and novel tags. By using real-time RT-PCR, we compared the sensitivity of SAGE and real-time RT-PCR, and by comparing with the results of cDNA microarray, we analyzed the differences and complementarity of SAGE and cDNA microarray.Part two Application and improvement of DGSWe constructed revised in vivo DGS by replacing two steps of plasmid library construction in original DGS with in vitro M13 PCR and solexa sequencing ditags fragments directly. We tested the simplified in vitro DGS protocol using the genomic DNA from the leukemic Kasumi-1 cell line. The major steps of the simplified in vitro DGS protocol include PstI restriction digestion of genomic DNA, PstI-MmeI-Solexa adaptor ligation, remove free adaptor, tags releasing by Mmel digestion, recovery of tag-adaptor-tag fragments, ditags formation and PCR amplification. Following the protocol stated above, we constructed eight breast cancer ditags libraries and performed solexa sequencing.Part three Large-scale sequencing restriction DNA fragments for genome studiesWe used FatI and Tsp509I to prepare CATG-AATT restriction fragments. All digested fragments have the'CATG'or'AATT'5'-overhangs and were filled by T4 DNA polymerase. After add an'A'to the 3'end of the blunt DNA fragments, we ligated them to adaptors who have a single'T' overhang at their 3'end. Purify the products can remove all unligated adaptors and self-ligated adaptors. Solexa PCR was used to selectively enrich DNA fragments and Solexa sequencing was performed afterwards.ResultsPart One Construction and analysis of allotransplantation CD4+T cell SAGE libraryWe collected a total of 51,808 SAGE tags from allograft activated CD4+T cells and 51,644 SAGE tags from isograft group CD4+T cells. Statistical analysis identified 402 SAGE tags that were significantly different (p...