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Construction of whole genomic and proteomic trees based on DNA and Protein probes
Thesis

Construction of whole genomic and proteomic trees based on DNA and Protein probes

Chi-Ching Lee
Masters, 國立清華大學, 生物資訊與結構生物研究所
2006

Abstract

比較基因體 生物資訊 微生物基因體 全基因體比較 基因體樹 蛋白質體樹 Comparative genome Bioinformatics Microbial genome Whole genome comparison Genomic tree Proteomic tree
The classification of microorganisms is difficult because they have various morphological and environmental distributing properties. Since 1970, taxonomy systems have been developed based on some stable and standard molecular biomarkers; for instance, sequence similarity of SSU RNA (small subunit ribosomal RNA) is the first and still wildly used biomarker nowadays for prokaryotes. However, it has been reported insufficient to classify all kinds of organisms by using one or only a few biomarkers. After 2000, the development of genome sequencing techniques has been so rapid that it is now possible to analyze the evolutionary relationships of organisms on the scale of whole genomes. We have developed a probe-based genome/proteome clustering approach based on the frequency of biologically meaningful restriction enzyme recognition elements and protein signatures. Such elements and signatures are provided by REBASE, the Restriction Enzyme dataBASE, and Prosite database, a collection of annotated motif descriptors from protein families and domains, We compared bacteria, archaea and fungi to build the genomic and proteomic tree by an unsupervised clustering method. Our results showed that, the genomic tree grouped together microorganisms with similar GC contents, and the proteomic tree clustered bacteria, archaea and fungi into two branches, where the latter two share the same node. Furthermore, the tree built based on Prosite signatures agreed well with the traditional phylogeny at the basal branches while the distal classifications seemed to reflect phenotypic features, such as the parasitism, thermophilicity, capabilities of methanogenesis or photosynthesis, better than traditional SSU RNA-based classifications. A web service has been set up, which is available at: http://probac.life.nthu.edu.tw/.

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