Mutations Mining And Systems Based On Evolution Of HBV Viral Sequences

Hepatitis B Virus(HBV) infection as one of the severe diseases which affecting human health problems. This kind of virus infection is the main reason to lead to the chronic liver disease, cirrhosis and liver cancer. Due to the particularity of its own replication, HBV with high variation characteristics. According to research shows that HBV gene variation is the root cause of HBV persistent infection. Meanwhile, in the process of natural selection or the random of evolution, research on HBV evolution, it’s also important to find out the origin of the virus. Therefore, research of HBV gene variation and evolution can provide a certain reference for understanding the pathogenesis of hepatitis B virus and guiding clinical treatment.In order to understand the genetic variation of HBV, detecting the SNP loci of HBV sequences has been widely used in the lot of studies, the detected SNP loci has great clinical significance. But the SNP loci detection methods are either too difficult in technical are too largely cost, so that to be limited in forensic practice. Therefore, to explore a computer-based detection methods of SNP loci become a trend. In this topic, according to the characteristics of the SNP loci of HBV sequences, we proposed a method based on optimal risk and prevention to detect the SNP loci which in HBV sequences. The proposed method is first applied to detect the SNP loci, experimental results show that:the method not only can detect the SNP loci of the HBV X gene fragment and the pre-C gene fragment which have been reported, and also can find the new SNP loci. With hardware testing SNP loci, the proposed computer method has the advantages of simple operation and low cost, and general laboratory and medical institutions can withstand.In the evolutionary process, HBV sequence just only have a small amount of SNP loci, mostly loci retained and passed on to future generations or disappear in the evolutionary process. Established phylogenetic tree can directly reflect the evolutionary relationship of HBV sequences, it can help to understand the HBV evolutionary history and evolutionary mechanisms. Based on this, we propose a new phylogenetic tree construction method. This method firstly used MEME (Multiple EM for Motif Elicitation) algorithm to mining HBV motif, and then take the new sequence metrics CI (Conservation Index) to construct phylogenetic tree of HBV sequences, finally used the evolutionary distance to assess the phylogenetic tree reliability. The experimental results show that:the new sequences metrics CI can build HBV sequence phylogenetic tree and analysis the evolutionary relationship between HBV sequence effectively.