The Prediction And Analysis Of Fuctional Genes Of Multiple Microbes

The function analysis of the microbial functional genomics is of great importance to the clarification of the gene functions and evolutionary characters for microbes as well as higher organisms. By taking into the prediction and analysis of the fucntional genes of multiple microbes, we offer new thoughts to the accurate gene prediction and evolutionary studies to the microbial functional genes. This research mainly contains the following four parts:1. The annotation of the well-studied organism, Saccharomyces cerevisiae, keeps improving in the past decade while there are unresolved debates over the amount of biologically significant open reading frames(ORFs) in yeast genome. By combining the Support Vector Machine(SVM) method with six widely used measurements of sequence statistical features, we revisited the total count of protein-coding genes in S. cerevisiae S288 c genome. The accuracy of our method is over 99.5% in 10-fold cross-validation, and a retrospective examination showed the fidelity of our method in recognizing ORFs that likely encode proteins. In addition, we have provided a web service that can be accessed at http://cobi.uestc.edu.cn/services/yeast/. The method can be appied to the prediction of other kinds of functional genes.2. The essential genes and high expression of gene are two important evolutionary conservative genes. Studies have found that the conservation of the genes is inseparable with their functions. We got 20 prokaryotes from the DEG Database with essential genes available and analysis the functional distribution of both the essential genes and the high expression genes in these species. The study reveals the relationships between gene function and conservation.3. The horizontal gene transfer drives the diversity evolution of species. We analysis the overlaps and correlative coefficient between the essentiality genes, the high expression genes and the HGTs of the 20 prokaryotic species with DEG data. This work reveals the comparison of evolutionary strength between the essentiality and expression level of genes from the aspect of HGT.4. Considering both the COGs and the HGTs reflect replication strand bias, we make an additional study about the evolutionary comparison between the high expression genes and the essential genes from this aspect. In addition, we discussed the limitation of simply using CAI as a substitute of gene expression and found different results drawing from different angles. Both the essential genes and the high expression genes show codon usage optimization, revealing the two have gone through a strong evolutionary translation selection and it’s unreliable to simply use CAI to represent the expression level.By using the SVM to predict the coding genes of the S. cerevisiae S288 c, we provide a reliable method to predict the protein-coding genes in Saccharomyces genomes, and by using the COG functional classification and the horizontal gene transfer data, we offer new evidences to the evolutionary study of the essential genes and the high expression genes. Furthermore, given the high accuracy and reliability of the first re-annotation work, we may consider using support vector machine(SVM) with appropriate biological features to predict other functional genes, such as high expression genes, essential genes, etc, which will guarantee the further functional analysis of these genes.