| Summary: | 碩士 === 國立臺灣大學 === 醫事技術學研究所 === 87 === When Watson and Crick discovered the double-helix structure of DNA molecules in 1953, search for the secret of Life became intensified with time. Due to its complexity, we are far from understanding life processes, although tremendous progress has been made in the past.
In our laboratory, we are interested in genes expressed during embryogenesis; particularly at different stages of development. To investigate genes expressed at 07, 11, 15 and 17 days mouse embryos, we employed two different techniques, namely the complexity reduction (CR) analysis and bioinformatics. Using 64 pairs of CRN3 primers, 203 unique bands expressed at day 7 or day 11 mouse embryos I had isolated and analyzed. These sequences were searched against the TIGR's Human gene index (HGI) and Mouse gene index (MGI), and NCBI's dbEST and GenBank databases. Search results showed that approximately 50% of isolated fragments had high-match entries in MGI or dbEST. Others had moderate, low, or no matches in these databases. From the high-matched sequences, overlapping fragments were assembled into full length. One full-length cDNA with a function likely related to embryo development was cloned. Other fragments with low or no-matched DB information were potentially novel genes and needed to be characterized further. By the use of RT-PCR and Northern blotting, 22 CR fragments were selected to confirm their gene expression patterns at different embryos stages. One gene, M07GGAU011, was expressed in day 7 embryo, while the expression of another gene, M11CTTU131, was found predominantly in day 11 and day 15 embryos. The functions of these genes were unknown and should be further characterized. Finally, gene expression patterns at different stages (7 and 11 days) of mouse embryos were examined by cDNA microarray to validate the mouse gene fragments identified by CR screening. I have demonstrated that novel genes expressed during different stages of mouse embryo development could be easily identified by the CR approach.
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