Natural selection for nucleotide usage at synonymous and nonsynonymous sites in influenza A virus genes

Identification and characterization of codon usage pattern and influencing factors in HFRS-causing hantaviruses

Hemorrhagic fever with renal syndrome (HFRS) is an acute viral zoonosis carried and transmitted by infected rodents through urine, droppings, or saliva. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors which hinder the development of potential therapeutic solutions for HFRS. Hantaan virus (HTNV), Dobrava-Belgrade virus (DOBV), Seoul virus (SEOV), and Puumala virus (PUUV) are predominantly found in hantaviral species that cause HFRS in patients. Despite ongoing prevention and control efforts, HFRS remains a serious economic burden worldwide. Furthermore, recent studies reported that the hantavirus nucleocapsid protein is a multi-functional protein and plays a major role in the replication cycle of the hantavirus. However, the precise mechanism of the nucleoproteins in viral pathogenesis is not completely understood. In the framework of the current study, various in silico approaches were employed to identify the factors influencing the codon usage pattern of hantaviral nucleoproteins. Based on the relative synonymous codon usage (RSCU) values, a comparative analysis was performed between HFRS-causing hantavirus and their hosts, suggesting that HTNV, DOBV, SEOV, and PUUV, were inclined to evolve their codon usage patterns that were comparable to those of their hosts. The results indicated that most of the overrepresented codons had AU-endings, which revealed that mutational pressure is the major force shaping codon usage patterns. However, the influence of natural selection and geographical factors cannot be ignored on viral codon usage bias. Further analysis also demonstrated that HFRS causing hantaviruses adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts. To our knowledge, no study to date reported the factors influencing the codon usage pattern within hantaviral nucleoproteins. Thus, the proposed computational scheme can help in understanding the underlying mechanism of codon usage patterns in HFRS-causing hantaviruses which lend a helping hand in designing effective anti-HFRS treatments in future. This study, although comprehensive, relies on in silico methods and thus necessitates experimental validation for more solid outcomes. Beyond the identified factors influencing viral behavior, there could be other yet undiscovered influences. These potential factors should be targets for further research to improve HFRS therapeutic strategies.

PCR-Based Detection and Genetic Characterization of Parainfluenza Virus 5 Detected in Pigs in Korea from 2016 to 2018

This study applied a molecular-based method to detect parainfluenza virus 5 (PIV5) collected from 2016 to 2018 in nine provinces of Republic of Korea. We demonstrated that PIV5 was detectable in both serum and pooled organs at an average positive rate of 1.78% (99/5566). Among these, the complete genome sequence of 15,246 nucleotides was obtained for 12 field strains. Three out of the 12 strains had the lowest genetic identity (96.20-96.68%) among the 21 porcine PIV5 genomes collected in Germany, China, India, and Republic of Korea from 1998 to 2017. By analyzing a large collection of complete genome sequences of the structural protein-coding F and HN genes, this study proposed a classification of PIV5 into two lineages, 1 and 2, and identified that group 2.2.2 within sub-lineage 2.2 was substantially divergent. The evolution of two structural protein-coding genes was largely under purifying selection. A few codons (6/9 for the F gene, 7/8 for the HN gene) had elevated dN/dS values, which were loaded on internal branches and were predicted to be related to beneficial trait(s) of the virus.

Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron

The ongoing SARS-CoV-2 evolution process has generated several variants due to its continuous mutations, making pandemics more critical. The present study illustrates SARS-CoV-2 evolution and its emerging mutations in five directions. First, the significant mutations in the genome and S-glycoprotein were analyzed in different variants. Three linear models were developed with the regression line to depict the mutational load for S-glycoprotein, total genome excluding S-glycoprotein, and whole genome. Second, the continent-wide evolution of SARS-CoV-2 and its variants with their clades and divergence were evaluated. It showed the region-wise evolution of the SARS-CoV-2 variants and their clustering event. The major clades for each variant were identified. One example is clade 21K, a major clade of the Omicron variant. Third, lineage dynamics and comparison between SARS-CoV-2 lineages across different countries are also illustrated, demonstrating dominant variants in various countries over time. Fourth, gene-wise mutation patterns and genetic variability of SARS-CoV-2 variants across various countries are illustrated. High mutation patterns were found in the ORF10, ORF6, S, and low mutation pattern E genes. Finally, emerging AA point mutations (T478K, L452R, N501Y, S477N, E484A, Q498R, and Y505H), their frequencies, and country-wise occurrence were identified, and the highest event of two mutations (T478K and L452R) was observed.

Evaluation of the added value of viral genomic information for predicting severity of influenza infection

BACKGROUND

The severity of an influenza infection is influenced by both host and viral characteristics. This study aims to assess the relevance of viral genomic data for the prediction of severe influenza A(H3N2) infections among patients hospitalized for severe acute respiratory infection (SARI), in view of risk assessment and patient management.

METHODS

160 A(H3N2) influenza positive samples from the 2016-2017 season originating from the Belgian SARI surveillance were selected for whole genome sequencing. Predictor variables for severity were selected using a penalized elastic net logistic regression model from a combined host and genomic dataset, including patient information and nucleotide mutations identified in the viral genome. The goodness-of-fit of the model combining host and genomic data was compared using a likelihood-ratio test with the model including host data only. Internal validation of model discrimination was conducted by calculating the optimism-adjusted area under the Receiver Operating Characteristic curve (AUC) for both models.

RESULTS

The model including viral mutations in addition to the host characteristics had an improved fit ([Formula: see text]=12.03, df = 3, p = 0.007). The optimism-adjusted AUC increased from 0.671 to 0.732.

CONCLUSIONS

Adding genomic data (selected season-specific mutations in the viral genome) to the model containing host characteristics improved the prediction of severe influenza infection among hospitalized SARI patients, thereby offering the potential for translation into a prospective strategy to perform early season risk assessment or to guide individual patient management.

V. R, Jha RM, Kumari A, Gandotra S, Rao V, Faruq M, Kumar S, Reshma G. B, Varma G. N, Roy SS, Sengupta A, Chattopadhyay S, Singhal K, Pradhan S, Jha D, Naushin S, Wadhwa S, Tyagi N, Poojary M, Scaria V, Sivasubbu S. High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

Biased Mutation and Selection in RNA Viruses

RNA viruses are responsible for some of the worst pandemics known to mankind, including outbreaks of Influenza, Ebola, and COVID-19. One major challenge in tackling RNA viruses is the fact they are extremely genetically diverse. Nevertheless, they share common features that include their dependence on host cells for replication, and high mutation rates. We set out to search for shared evolutionary characteristics that may aid in gaining a broader understanding of RNA virus evolution, and constructed a phylogeny-based data set spanning thousands of sequences from diverse single-stranded RNA viruses of animals. Strikingly, we found that the vast majority of these viruses have a skewed nucleotide composition, manifested as adenine rich (A-rich) coding sequences. In order to test whether A-richness is driven by selection or by biased mutation processes, we harnessed the effects of incomplete purifying selection at the tips of virus phylogenies. Our results revealed consistent mutational biases toward U rather than A in genomes of all viruses. In +ssRNA viruses, we found that this bias is compensated by selection against U and selection for A, which leads to A-rich genomes. In -ssRNA viruses, the genomic mutational bias toward U on the negative strand manifests as A-rich coding sequences, on the positive strand. We investigated possible reasons for the advantage of A-rich sequences including weakened RNA secondary structures, codon usage bias, and selection for a particular amino acid composition, and conclude that host immune pressures may have led to similar biases in coding sequence composition across very divergent RNA viruses.

Allele-specific nonstationarity in evolution of influenza A virus surface proteins

Influenza A virus (IAV) is a major public health problem and a pandemic threat. Its evolution is largely driven by diversifying positive selection so that relative fitness of different amino acid variants changes with time due to changes in herd immunity or genomic context, and novel amino acid variants attain fitness advantage. Here, we hypothesize that diversifying selection also has another manifestation: the fitness associated with a particular amino acid variant should decline with time since its origin, as the herd immunity adapts to it. By tracing the evolution of antigenic sites at IAV surface proteins, we show that an amino acid variant becomes progressively more likely to become replaced by another variant with time since its origin-a phenomenon we call "senescence." Senescence is particularly pronounced at experimentally validated antigenic sites, implying that it is largely driven by host immunity. By contrast, at internal sites, existing variants become more favorable with time, probably due to arising contingent mutations at other epistatically interacting sites. Our findings reveal a previously undescribed facet of adaptive evolution and suggest approaches for prediction of evolutionary dynamics of pathogens.

Stability of the Influenza Virus Hemagglutinin Protein Correlates with Evolutionary Dynamics

One of the constraints on fast-evolving viruses, such as influenza virus, is protein stability, or how strongly the folded protein holds together. Despite the importance of this protein property, there has been limited investigation of the impact of the stability of the influenza virus hemagglutinin protein—the primary antibody target of the immune system—on its evolution. Using a combination of computational estimates of stability and experiments, our analysis found that viruses with more-stable hemagglutinin proteins were associated with long-term persistence in the population. There are two potential reasons for the observed persistence. One is that more-stable proteins tolerate destabilizing mutations that less-stable proteins could not, thus increasing opportunities for immune escape. The second is that greater stability increases the fitness of the virus through increased production of infectious particles. Further research on the relative importance of these mechanisms could help inform the annual influenza vaccine composition decision process.

Protein thermodynamics are an integral determinant of viral fitness and one of the major drivers of protein evolution. Mutations in the influenza A virus (IAV) hemagglutinin (HA) protein can eliminate neutralizing antibody binding to mediate escape from preexisting antiviral immunity. Prior research on the IAV nucleoprotein suggests that protein stability may constrain seasonal IAV evolution; however, the role of stability in shaping the evolutionary dynamics of the HA protein has not been explored. We used the full coding sequence of 9,797 H1N1pdm09 HA sequences and 16,716 human seasonal H3N2 HA sequences to computationally estimate relative changes in the thermal stability of the HA protein between 2009 and 2016. Phylogenetic methods were used to characterize how stability differences impacted the evolutionary dynamics of the virus. We found that pandemic H1N1 IAV strains split into two lineages that had different relative HA protein stabilities and that later variants were descended from the higher-stability lineage. Analysis of the mutations associated with the selective sweep of the higher-stability lineage found that they were characterized by the early appearance of highly stabilizing mutations, the earliest of which was not located in a known antigenic site. Experimental evidence further suggested that H1N1 HA stability may be correlated with in vitro virus production and infection. A similar analysis of H3N2 strains found that surviving lineages were also largely descended from viruses predicted to encode more-stable HA proteins. Our results suggest that HA protein stability likely plays a significant role in the persistence of different IAV lineages.

IMPORTANCE One of the constraints on fast-evolving viruses, such as influenza virus, is protein stability, or how strongly the folded protein holds together. Despite the importance of this protein property, there has been limited investigation of the impact of the stability of the influenza virus hemagglutinin protein—the primary antibody target of the immune system—on its evolution. Using a combination of computational estimates of stability and experiments, our analysis found that viruses with more-stable hemagglutinin proteins were associated with long-term persistence in the population. There are two potential reasons for the observed persistence. One is that more-stable proteins tolerate destabilizing mutations that less-stable proteins could not, thus increasing opportunities for immune escape. The second is that greater stability increases the fitness of the virus through increased production of infectious particles. Further research on the relative importance of these mechanisms could help inform the annual influenza vaccine composition decision process.

Fitness Inference from Short-Read Data: Within-Host Evolution of a Reassortant H5N1 Influenza Virus

We present a method to infer the role of selection acting during the within-host evolution of the influenza virus from short-read genome sequence data. Linkage disequilibrium between loci is accounted for by treating short-read sequences as noisy multilocus emissions from an underlying model of haplotype evolution. A hierarchical model-selection procedure is used to infer the underlying fitness landscape of the virus insofar as that landscape is explored by the viral population. In a first application of our method, we analyze data from an evolutionary experiment describing the growth of a reassortant H5N1 virus in ferrets. Across two sets of replica experiments we infer multiple alleles to be under selection, including variants associated with receptor binding specificity, glycosylation, and with the increased transmissibility of the virus. We identify epistasis as an important component of the within-host fitness landscape, and show that adaptation can proceed through multiple genetic pathways.

Identifying selection in the within-host evolution of influenza using viral sequence data

The within-host evolution of influenza is a vital component of its epidemiology. A question of particular interest is the role that selection plays in shaping the viral population over the course of a single infection. We here describe a method to measure selection acting upon the influenza virus within an individual host, based upon time-resolved genome sequence data from an infection. Analysing sequence data from a transmission study conducted in pigs, describing part of the haemagglutinin gene (HA1) of an influenza virus, we find signatures of non-neutrality in six of a total of sixteen infections. We find evidence for both positive and negative selection acting upon specific alleles, while in three cases, the data suggest the presence of time-dependent selection. In one infection we observe what is potentially a specific immune response against the virus; a non-synonymous mutation in an epitope region of the virus is found to be under initially positive, then strongly negative selection. Crucially, given the lack of homologous recombination in influenza, our method accounts for linkage disequilibrium between nucleotides at different positions in the haemagglutinin gene, allowing for the analysis of populations in which multiple mutations are present at any given time. Our approach offers a new insight into the dynamics of influenza infection, providing a detailed characterisation of the forces that underlie viral evolution.

The evolution of the influenza virus is of great importance for human health. Through evolution, current influenza viruses develop the ability to infect people who have been vaccinated against earlier strains. New strains of influenza that infect birds and pigs could evolve to infect and spread between people, causing a global pandemic. The influenza virus lives within a human or animal host, so that viral evolution happens within, or in the spread between, individuals. As such, what happens to the virus during the course of an infection is a question of great interest. We here describe a statistical method that uses viral genome sequence data to measure how evolution affects the influenza virus within a single host. Studying data from infections transmitted between pigs, we find evidence for evolutionary adaptation in six of sixteen animals for which data were available. In one case, an immune response mounted by a pig against the virus is apparent. Our method provides a statistical framework for using sequence data to study viral evolution on very short timescales, enabling new research into within-host viral evolution.

Intrasubtype reassortments cause adaptive amino acid replacements in H3N2 influenza genes

Reassortments and point mutations are two major contributors to diversity of Influenza A virus; however, the link between these two processes is unclear. It has been suggested that reassortments provoke a temporary increase in the rate of amino acid changes as the viral proteins adapt to new genetic environment, but this phenomenon has not been studied systematically. Here, we use a phylogenetic approach to infer the reassortment events between the 8 segments of influenza A H3N2 virus since its emergence in humans in 1968. We then study the amino acid replacements that occurred in genes encoded in each segment subsequent to reassortments. In five out of eight genes (NA, M1, HA, PB1 and NS1), the reassortment events led to a transient increase in the rate of amino acid replacements on the descendant phylogenetic branches. In NA and HA, the replacements following reassortments were enriched with parallel and/or reversing replacements; in contrast, the replacements at sites responsible for differences between antigenic clusters (in HA) and at sites under positive selection (in NA) were underrepresented among them. Post-reassortment adaptive walks contribute to adaptive evolution in Influenza A: in NA, an average reassortment event causes at least 2.1 amino acid replacements in a reassorted gene, with, on average, 0.43 amino acid replacements per evolving post-reassortment lineage; and at least ~9% of all amino acid replacements are provoked by reassortments.

Natural Selection Determines Synonymous Codon Usage Patterns of Neuraminidase (NA) Gene of the Different Subtypes of Influenza A Virus in Canada

Synonymous codon usage patterns of neuraminidase (NA) gene of 64 subtypes (one is a mixed subtype) of influenza A virus found in Canada were analyzed. In total, 1422 NA sequences were analyzed. Among the subtypes, H1N1 is the prevailing one with 516 NCBI accession records, followed by H3N2, H3N8, and H4N6. The year of 2009 has the highest report records for the NA sequences in Canada, corresponding to the 2009 pandemic event. Correspondence analysis on the RSCU values of the four major subtypes showed that they had distinct clustering patterns in the two-dimensional scatter plot, indicating that different subtypes of IAV utilized different preferential codons. This subtype clustering pattern implied the important influence of natural selection, which could be further evidenced by an extremely flattened regression line in the neutrality plot (GC12 versus G3s plot) and a significant phylogenetic signal on the distribution of different subtypes in the clades of the phylogenetic tree (λ statistic). In conclusion, different subtypes of IAV showed an evolutionary differentiation on choosing different optimal codons. Natural selection played a deterministic role to structure IAV codon usage patterns in Canada.

Molecular signature of high yield (growth) influenza a virus reassortants prepared as candidate vaccine seeds

Background

Human influenza virus isolates generally grow poorly in embryonated chicken eggs. Hence, gene reassortment of influenza A wild type (wt) viruses is performed with a highly egg adapted donor virus, A/Puerto Rico/8/1934 (PR8), to provide the high yield reassortant (HYR) viral ‘seeds’ for vaccine production. HYR must contain the hemagglutinin (HA) and neuraminidase (NA) genes of wt virus and one to six ‘internal’ genes from PR8. Most studies of influenza wt and HYRs have focused on the HA gene. The main objective of this study is the identification of the molecular signature in all eight gene segments of influenza A HYR candidate vaccine seeds associated with high growth in ovo.

Methodology

The genomes of 14 wt parental viruses, 23 HYRs (5 H1N1; 2, 1976 H1N1-SOIV; 2, 2009 H1N1pdm; 2 H2N2 and 12 H3N2) and PR8 were sequenced using the high-throughput sequencing pipeline with big dye terminator chemistry.

Results

Silent and coding mutations were found in all internal genes derived from PR8 with the exception of the M gene. The M gene derived from PR8 was invariant in all 23 HYRs underlining the critical role of PR8 M in high yield phenotype. None of the wt virus derived internal genes had any silent change(s) except the PB1 gene in X-157. The highest number of recurrent silent and coding mutations was found in NS. With respect to the surface antigens, the majority of HYRs had coding mutations in HA; only 2 HYRs had coding mutations in NA.

Significance

In the era of application of reverse genetics to alter influenza A virus genomes, the mutations identified in the HYR gene segments associated with high growth in ovo may be of great practical benefit to modify PR8 and/or wt virus gene sequences for improved growth of vaccine ‘seed’ viruses.

Components of selection in the evolution of the influenza virus: linkage effects beat inherent selection

The influenza virus is an important human pathogen, with a rapid rate of evolution in the human population. The rate of homologous recombination within genes of influenza is essentially zero. As such, where two alleles within the same gene are in linkage disequilibrium, interference between alleles will occur, whereby selection acting upon one allele has an influence upon the frequency of the other. We here measured the relative importance of selection and interference effects upon the evolution of influenza. We considered time-resolved allele frequency data from the global evolutionary history of the haemagglutinin gene of human influenza A/H3N2, conducting an in-depth analysis of sequences collected since 1996. Using a model that accounts for selection-caused interference between alleles in linkage disequilibrium, we estimated the inherent selective benefit of individual polymorphisms in the viral population. These inherent selection coefficients were in turn used to calculate the total selective effect of interference acting upon each polymorphism, considering the effect of the initial background upon which a mutation arose, and the subsequent effect of interference from other alleles that were under selection. Viewing events in retrospect, we estimated the influence of each of these components in determining whether a mutant allele eventually fixed or died in the global viral population. Our inherent selection coefficients, when combined across different regions of the protein, were consistent with previous measurements of dN/dS for the same system. Alleles going on to fix in the global population tended to be under more positive selection, to arise on more beneficial backgrounds, and to avoid strong negative interference from other alleles under selection. However, on average, the fate of a polymorphism was determined more by the combined influence of interference effects than by its inherent selection coefficient.

Success in life is the product of many factors. Inherent ability often underlies great achievement. But other factors may play their part. The circumstances a child is born into may help or hinder his or her progress. Later events also have their effect; a life may be influenced by a lucky break, or an unforeseen disaster. In this work, we examine the factors underlying success for mutations in the HA gene of human influenza virus A/H3N2, defining success as the attainment of a high frequency in the global population. We examined the history of the gene from 1968 until 2010. For each observed mutation, a mathematical model was used to estimate the inherent benefit or disadvantage it conferred to the virus. We calculated the advantageousness or otherwise of the background upon which it arose, and the subsequent effect of interference from other mutations under selection. We found that successful mutations tended to have an advantageous background, and were subsequently fortunate in avoiding negative events throughout their lifetime. Beneficial mutations were more likely to be successful. But a mutation's chances of success were influenced more by circumstances of birth and subsequent events, than by its inherent effect on the virus.

Pandemic influenza A virus codon usage revisited: biases, adaptation and implications for vaccine strain development

Background

Influenza A virus (IAV) is a member of the family Orthomyxoviridae and contains eight segments of a single-stranded RNA genome with negative polarity. The first influenza pandemic of this century was declared in April of 2009, with the emergence of a novel H1N1 IAV strain (H1N1pdm) in Mexico and USA. Understanding the extent and causes of biases in codon usage is essential to the understanding of viral evolution. A comprehensive study to investigate the effect of selection pressure imposed by the human host on the codon usage of an emerging, pandemic IAV strain and the trends in viral codon usage involved over the pandemic time period is much needed.

Results

We performed a comprehensive codon usage analysis of 310 IAV strains from the pandemic of 2009. Highly biased codon usage for Ala, Arg, Pro, Thr and Ser were found. Codon usage is strongly influenced by underlying biases in base composition. When correspondence analysis (COA) on relative synonymous codon usage (RSCU) is applied, the distribution of IAV ORFs in the plane defined by the first two major dimensional factors showed that different strains are located at different places, suggesting that IAV codon usage also reflects an evolutionary process.

Conclusions

A general association between codon usage bias, base composition and poor adaptation of the virus to the respective host tRNA pool, suggests that mutational pressure is the main force shaping H1N1 pdm IAV codon usage. A dynamic process is observed in the variation of codon usage of the strains enrolled in these studies. These results suggest a balance of mutational bias and natural selection, which allow the virus to explore and re-adapt its codon usage to different environments. Recoding of IAV taking into account codon bias, base composition and adaptation to host tRNA may provide important clues to develop new and appropriate vaccines.

The mouse B cell-specific mb-1 gene encodes an immunoreceptor tyrosine-based activation motif (ITAM) protein that may be evolutionarily conserved in diverse species by purifying selection

The B-lymphocyte accessory molecule Ig-alpha (Ig-α) is encoded by the mouse B cell-specific gene (mb-1), and along with the Ig-beta (Ig-β) molecule and a membrane bound immunoglobulin (mIg) makes up the B-cell receptor (BCR). Ig-α and Ig-β form a heterodimer structure that upon antigen binding and receptor clustering primarily initiates and controls BCR intracellular signaling via a phosphorylation cascade, ultimately triggering an effector response. The signaling capacity of Ig-α is contained within its immunoreceptor tyrosine-based activation motif (ITAM), which is also a key component for intracellular signaling initiation in other immune cell-specific receptors. Although numerous studies have been devoted to the mb-1 gene product, Ig-α, and its signaling mechanism, an evolutionary analysis of the mb-1 gene has been lacking until now. In this study, mb-1 coding sequences from 19 species were compared using Bayesian inference. Analysis revealed a gene phylogeny consistent with an expected species divergence pattern, clustering species from the primate order separate from lower mammals and other species. In addition, an overall comparison of non-synonymous and synonymous nucleotide mutational changes suggests that the mb-1 gene has undergone purifying selection throughout its evolution.

Young proteins experience more variable selection pressures than old proteins

It is well known that young proteins tend to experience weaker purifying selection and evolve more quickly than old proteins. Here, we show that, in addition, young proteins tend to experience more variable selection pressures over time than old proteins. We demonstrate this pattern in three independent taxonomic groups: yeast, Drosophila, and mammals. The increased variability of selection pressures on young proteins is highly significant even after controlling for the fact that young proteins are typically shorter and experience weaker purifying selection than old proteins. The majority of our results are consistent with the hypothesis that the function of a young gene tends to change over time more readily than that of an old gene. At the same time, our results may be caused in part by young genes that serve constant functions over time, but nevertheless appear to evolve under changing selection pressures due to depletion of adaptive mutations. In either case, our results imply that the evolution of a protein-coding sequence is partly determined by its age and origin, and not only by the phenotypic properties of the encoded protein. We discuss, via specific examples, the consequences of these findings for understanding of the sources of evolutionary novelty.

Codon usage bias and the evolution of influenza A viruses. Codon Usage Biases of Influenza Virus

BACKGROUND

The influenza A virus is an important infectious cause of morbidity and mortality in humans and was responsible for 3 pandemics in the 20th century. As the replication of the influenza virus is based on its host's machinery, codon usage of its viral genes might be subject to host selection pressures, especially after interspecies transmission. A better understanding of viral evolution and host adaptive responses might help control this disease.

RESULTS

Relative Synonymous Codon Usage (RSCU) values of the genes from segment 1 to segment 6 of avian and human influenza viruses, including pandemic H1N1, were studied via Correspondence Analysis (CA). The codon usage patterns of seasonal human influenza viruses were distinct among their subtypes and different from those of avian viruses. Newly isolated viruses could be added to the CA results, creating a tool to investigate the host origin and evolution of viral genes. It was found that the 1918 pandemic H1N1 virus contained genes with mammalian-like viral codon usage patterns, indicating that the introduction of this virus to humans was not through in toto transfer of an avian influenza virus.Many human viral genes had directional changes in codon usage over time of viral isolation, indicating the effect of host selection pressures. These changes reduced the overall GC content and the usage of G at the third codon position in the viral genome. Limited evidence of translational selection pressure was found in a few viral genes.

CONCLUSIONS

Codon usage patterns from CA allowed identification of host origin and evolutionary trends in influenza viruses, providing an alternative method and a tool to understand the evolution of influenza viruses. Human influenza viruses are subject to selection pressure on codon usage which might assist in understanding the characteristics of newly emerging viruses.

Human alpha and beta papillomaviruses use different synonymous codon profiles

Human papillomaviruses use rare codons relative to their hosts. It has been theorized that this is a mechanism to allow the virus to escape immune surveillance. In the present study, we examined the codings of four major genes of 21 human alpha (mucosatropic) viruses and 16 human beta (cutaneous-tropic) viruses. We compared the codon usage of different genes from a given papillomavirus and also the same genes from different papillomaviruses. Our data showed that codon usage was not always uniform between two genes of a given papillomavirus or between the same genes of papillomaviruses from different genera. We speculate as to why this might be and conclude that codon usage in the papillomaviruses may not only play a role in facilitating escape from immune surveillance but may also underlie some of the unanswered questions in the papillomavirus field.