Computational Prediction Of Sigma-54 Promoters In Bacterial Genomes By Integrating Motif Finding And Machine Learning Strategies

The main function of RNA polymerase is to use DNA to make RNA.RNA polymerases use DNA as a template for the transcription process and use adenine deoxynucleotide?A?,thymidine deoxynucleotide?T?,cytosine deoxynucleotide?C?,uracil deoxynucleotide?U?to generate RNA for raw materials.In order to adapt to different environments,perform unique roles in organisms,and maintain the metabolic processes required for survival,cells need to control the formation of RNA through transcription to control the synthesis of proteins and control the expression of genes.And RNA polymerase is present in all organisms,cells,and viruses.Therefore,RNA polymerase is a very important enzyme.The RNA polymerase core enzyme contains 5 subunits??,?',?? and ?? and ??.For binding to DNA sequences,RNA core enzymes and factors combine to make RNA polymerase holoenzymes.sigma factor,as a unit of RNA polymerase holoenzyme,is a critical factor in the process of gene transcriptional regulation.It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes.Therefore,the type of promoter in prokaryotes is defined by the type of factor.At present,the known factors mainly fall into two categories:one is sigma-70,which regulates the transcription of most housekeeping genes under normal circumstances and the other is sigma-54 which is responsible for regulating the transcription of specific genes related to the environment.Because transcription is the first step in gene expression and factors play a key role in transcription initiation,the study of factors has become one of the keys to the study of gene expression regulation in recent years.It has also been studied by biologists in various countries.Many members of the sigma-54.family play an important role in many cell metabolisms such as nitrogen fixation and arginine decomposition.Therefore,it is important to understand the subsequent steps of gene expression and establish the gene transcription network to reveal the transcription mechanism of the sigma-54 promoterThis paper develops a new method to predict sigma-54 promoter in bacterial genomes.The new method organically integrates motif finding and machine learning strategies to capture the intrinsic features of sigma-54 promoters.We mainly validate our method on three kinds of datasets.Firstly,we use the benchmark data on the E.coli collection to train the model.The experiments on E.coli benchmark test set show that our method has good capability to distinguish sigma-54 promoters from peripheral non-functional DNA sequences or randomly selected DNA sequences.Secondly,we applied our trained model to three different genomes of computational prediction data for further testing,including:Bacillus subtilis?NC₀00964?,Clostridium acetobutylicum?NC₀03030?and Lactobacillus brevis?NC₀08497?_The applications of other three bacterial genomes indicate the potential robustness and applicative power of our method on a large number of bacterial genomes.At last,we also apply our method to the identification of other promoters and obtained good performance.Besides,we developed a Webserver for six kinds of sigma factors specific promoter prediction.