Molecular Evolution Study Of Measles Virus And Typing And Identification Of Enteroviruses Based On Bioinformatics

Humans have now identified more than5000kinds of types of viruses. Some virus candirectly cause human diseases, such as influenza, chicken pox, and smallpox, AIDS, SARSand avian flu and other serious diseases, in addition, some of the virus as predisposingfactors for certain diseases, such as herpes simplex virus type6can cause nerve disease,certain viruses may cause chronic fatigue syndrome. In recent years, with the developmentof next-generation sequencing technology, more of the viral genome has been sequenced. ByMarch2013, there are3251kinds viral genome published on the NCBI. How to takeadvantage of the bioinformatics techniques to the analysis of published mass virus genomeresources is an urgent need to solve the problem. In this study, we sequenced Measles virusN gene and used Bayesian-Markoff chain molecular evolution analysis for the MV N gene.We also applicated genomic barcode technology to the identificate and classify HumanEnterovirus. Our studies give new research perspective for traditional microbiology researchtechniques are difficult to solve such as virus evolution and identification of typing, andcontribute to a better understanding of the occurrence and development of viral diseases.Part I. Bayesian-Markoff chain molecular evolutionary for measles virusMeasles viruses (measles virus, MV) belongs to the paramyxovirus family measlesvirus is highly contagious, can cause measles and severe complications, includingcytomegalovirus pneumonia, inclusion body encephalitis after infected with the human body.Recent years, with the large-scale use of the measles vaccine, measles morbidity andmortality significantly reduced, but the local outbreak of measles in various still occur fromtime to time. The study of molecular evolution not only has meaning for the identification ofthe measles virus’s genetic subtype but also to provide a scientific basis to explain the localepidemic of measles virus at the molecular level.In the present study, we sequenced the N gene of16measles virus separated fromChina Jilin region, together with collate all published measles virus N gene sequencesdownloaded from the NCBI sequence database, build the largest measles virus coronavirusN gene sequence data sets. Between various strains of measles virus N gene sequences we detected the occurrence of recombination event with RDP3(Recombination DetectionProgram) software, and the results show that there is no recombination event occurredbetween the measles virus N gene. Then we use the Bayesian-Markov chain analysismethod molecular evolutionary analysis of the measles virus N gene data set. The resultsshowed466measles virus N gene sequence is divided into two clusters, one containing theA, B, G, H, and C genotype (the Jilin area16measles viruses show H1genotype), and thesecond containing genotype D cluster, which means that D genotype has unique evolutionarycharacteristics. We also estimate the measles virus N gene replacement rate as an average ofeach locus1.127E-3alternative events occur each year, the Time to Most Recent CommonAncestor (TMRCA) of different genotypes time ranging from20years to45years. Dynamicanalysis by the Bayesian-Markoff chain Bayesian skyline plot method to study theevolution of the measles virus N gene characteristics show that over the past50years, themeasles virus N gene evolutionary mutation rate continued to increase, and in2009reachedthe highest level, followed by a significant decline. The mutation rate of measles virus Ngene is at a low level in recent years, with the reported measles virus epidemic statisticaldata that matches.Part II. genome-based bar code identification of enterovirus typingHuman enterovirus (Human enterovirus, HEV) are small RNA virus family, enterovirus.HEV can cause a variety of clinical diseases, such as aseptic meningitis,meningoencephalitis, hand, foot and mouth disease and myocarditis, etc. HEV have beenreporting since the discovery with great harm to human health and society. Initially it to beclassified according to the pathogenicity and antigenicity, but these methods aretime-consuming and laborious, and Inadequate for a variety of HEV accurate genotyping,has gradually been replaced by genotyping. Due to Different evolutionary rates of the HEVdifferent genes, genotyping with phylogenetic tree with HEV biological traits often conflict.As the development of sequencing technology, nearly400enterovirus genomes have beensequenced. Mining richer information from a genomic perspective, it is imperative todevelop new HEV identified sub-type method.In this study, from the level of the genome, we used a new bioinformatics technology-Genome barcode technology to identificate and classify enterovirus. We first downloadedcommon viruses: human immunodeficiency virus (HIV), hepatitis C virus (HCV), influenzavirus (Influenza virus), enteroviruses (EV) from the NCBI several, and then calculate the the barcode feature vectors of different viral genome using Euclidean distance, whereby thedistance between enterovirus enterovirus identification and establishment of thephylogenetic tree. The results showed that: different viruses have different genomic barcodeimage, wherein the abnormal region may be for the horizontal transfer of gene fragments.Genome barcode distance can classify all kinds of viruses, and has a very good typing effecton enterovirus subtypes. The phylogenetic trees using genome barcode technology and usingVP1use traditional sequence alignment methods have94%similarity, genomic bar codetechnology more according with pathogenicity in the Coxsackie A group, meaning thegenomic barcode technology can reflect more information than single-gene sequencealignment information and can be a new, reliable typing HEV identification technology.