Developing ZCURVE 1.02 Computer Program For Prokaryotic Gene Identification And Analyzing Microbial Essential Genes

It is up to now that more than 200 bacterial and archaeal genomes have been completed due to the quick development of bacterial genome-sequencing projects. Indentification of protein-coding genes in microbial genomes is one of the most important tasks in bioinformatics (computional biology). This paper describes a little improvement in recognizing protein-coding genes in bacterial genomes using the Z curve method and also tries to use the BLAST to identify the essential genes in microbes. The first part of the paper introduces the human genome project (HGP) and model organasim genome project. Several well-known gene recognition programs for prokaryotes and the unsolved problems in gene recognition are also referred. The second part of the paper introduces the Z curve methodology which is the basic tool in analyzing prokaryotic genomes and gives a brief introduction to the application of Z curve method in various areas such as gene finding in prokaryotic genomes, isochore structure in eukaryotic genomes and identification of replication origins in the genome of archaeon and bacteria. The third part of the paper proposes the application of Z curve method in the recognition of protein-coding genes in prokaryotic genomes. The author implements the C++ language to rewrite the ZCURVE 1.0 program and makes a little adjustment in training the Fisher coefficients. The rewritten program with a little improvement is named as ZCURVE 1.02. Compared with ZCURVE 1.0, ZCURVE 1.02 shows similar accuracy and lower additional prediction rate. Furthermore, the speed of ZCURVE 1.02 has been enhanced. ZCURVE 1.02 can be run under different operating systems such as Linux and IRIX and can be intergrated into other programs more conveniently. In the fourth part of the paper, the author tries to analyze the microbial essential genes using the method of BLAST. The database of essential genes (DEG) contains 2248 essential genes in 8 species after it is updated by the auther. The author analyzes the nucleotide distribution of essential genes and nonessential genes in Bacillus subtilis using the Z curve method and tries to predict the essential genes using the method of BLAST. Besides, the author categorizes the essential genes in E. coli K12 according to different functions and tries to discuss feasibility of predicting essential genes using the BLAST method.