Methods And Programs For Analyzing Microarray Data And Detecting Horizontal Gene Transfer: Phylogenetic Approaches

Phylogenetic analysis is one of the main methologies in both evolutionary biology and bioinformatics. In this dissertation, phylogenetic analysis is applied to analyze DNA microarray data and detect horizontal gene transfer. This gives out a new strategy to solve these two bioinformatics problems.With the development of genomics, many genome-scale experiments for gene expression profile were conducted by DNA microarray techniques. For a long time, clustering algorithms are main approaches for clustering gene expression data. Their main aims are to reduce data dimentions and mine new biologic knowledges. However, these approaches have no stable classification indexes or biologic background, and may mislead the results explaination.. In the first part of this dissertation, seprin gene expression profile is analysis by phylogenetic approach. Physiological functions and characteristic structures of the serpin gene superfamily have been studied extensively, yet the evolution of the serpin genes remains unclear. Gene duplication in this superfamily may shed light on this issue. Two models are used to predict the preservation of duplicated genes: the classical model and the duplication-degeneration-complementation (DDC) model. In this part, we analyzed the phylogenetic relationships of 33 human serpin genes and the expression data of some members of the serpin superfamily from a DNA microarray of human leukemia U937 cells with stably inducible expression of the leukemia-related AML1-ETO gene. We then determined the utility of the DDC model by mapping serpin superfamily expression data to the phylogenetic tree. The correlation between sequence and expression divergences as measured by the Pearson correlation coefficient indicated that human serpin genes evolved under the DDC model. Our study provides a new strategy for comparative analysis of gene sequences and microarray data. In order to extend this analysis to genomic level, a software package named PhyloExp was designed.In the second part of this dissertation, phylogenetic analysis is applied to detect horizontally transferred genes in microbial genome. Since 1950s researchers found that antibiotic-resistant plasmids could move among different bacterial species and spread drug-resistant genes, it has been widely accepted and recognised that HGT can also influence the evolution of plant and animal kingdoms. Firstly, we review two freeware programs: T-REX for MS Windows and RHOM for Linux. T-REX is agraphical user interface program that offers functions to reconstruct the HGT network among the donor and receptor hosts from the gene and species distance matrices. RHOM is a set of command-line driven programs used to detect HGT in genomes. While T-REX impresses with a user-friendly interface and drawing of the reticulation network, the strength of RHOM is an extensive statistical framework of genome and the graphical display of the estimated sequence position probabilities for the candidate horizontally transferred genes. These two softwares represent surrogate methods and phylogenomic approach, respectively. However, these two methods has themselves own limiting. On the one side, surrogate methods can not give out the donor genome or species; on the other side, phylogenomic methods can not solve "orphan genes" problem. In our study, software named HAPLY was designed to solve these problems. Firstly, a surrogate method implemented in HAPLY is used to detect the possible horizontal transferred genes in a microbiologic genome; then a phylogenomic analysis for a single or several genes by an online database search. Currently, HAPLY was implemented partly and further extensive work is needed.