9,130 research outputs found

    Patterns and rates of viral evolution in HIV-1 subtype B infected females and males.

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    Biological sex differences affect the course of HIV infection, with untreated women having lower viral loads compared to their male counterparts but, for a given viral load, women have a higher rate of progression to AIDS. However, the vast majority of data on viral evolution, a process that is clearly impacted by host immunity and could be impacted by sex differences, has been derived from men. We conducted an intensive analysis of HIV-1 gag and env-gp120 evolution taken over the first 6-11 years of infection from 8 Women's Interagency HIV Study (WIHS) participants who had not received combination antiretroviral therapy (ART). This was compared to similar data previously collected from men, with both groups infected with HIV-1 subtype B. Early virus populations in men and women were generally homogenous with no differences in diversity between sexes. No differences in ensuing nucleotide substitution rates were found between the female and male cohorts studied herein. As previously reported for men, time to peak diversity in env-gp120 in women was positively associated with time to CD4+ cell count below 200 (P = 0.017), and the number of predicted N-linked glycosylation sites generally increased over time, followed by a plateau or decline, with the majority of changes localized to the V1-V2 region. These findings strongly suggest that the sex differences in HIV-1 disease progression attributed to immune system composition and sensitivities are not revealed by, nor do they impact, global patterns of viral evolution, the latter of which proceeds similarly in women and men

    Canalization of the evolutionary trajectory of the human influenza virus

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    Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure

    Evolutionary History and Attenuation of Myxoma Virus on Two Continents

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    The attenuation of myxoma virus (MYXV) following its introduction as a biological control into the European rabbit populations of Australia and Europe is the canonical study of the evolution of virulence. However, the evolutionary genetics of this profound change in host-pathogen relationship is unknown. We describe the genome-scale evolution of MYXV covering a range of virulence grades sampled over 49 years from the parallel Australian and European epidemics, including the high-virulence progenitor strains released in the early 1950s. MYXV evolved rapidly over the sampling period, exhibiting one of the highest nucleotide substitution rates ever reported for a double-stranded DNA virus, and indicative of a relatively high mutation rate and/or a continually changing selective environment. Our comparative sequence data reveal that changes in virulence involved multiple genes, likely losses of gene function due to insertion-deletion events, and no mutations common to specific virulence grades. Hence, despite the similarity in selection pressures there are multiple genetic routes to attain either highly virulent or attenuated phenotypes in MYXV, resulting in convergence for phenotype but not genotype. © 2012 Kerr et al

    Islands of linkage in an ocean of pervasive recombination reveals two-speed evolution of human cytomegalovirus genomes

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    Human cytomegalovirus (HCMV) infects most of the population worldwide, persisting throughout the host's life in a latent state with periodic episodes of reactivation. While typically asymptomatic, HCMV can cause fatal disease among congenitally infected infants and immunocompromised patients. These clinical issues are compounded by the emergence of antiviral resistance and the absence of an effective vaccine, the development of which is likely complicated by the numerous immune evasins encoded by HCMV to counter the host's adaptive immune responses, a feature that facilitates frequent super-infections. Understanding the evolutionary dynamics of HCMV is essential for the development of effective new drugs and vaccines. By comparing viral genomes from uncultivated or low-passaged clinical samples of diverse origins, we observe evidence of frequent homologous recombination events, both recent and ancient, and no structure of HCMV genetic diversity at the whole-genome scale. Analysis of individual gene-scale loci reveals a striking dichotomy: while most of the genome is highly conserved, recombines essentially freely and has evolved under purifying selection, 21 genes display extreme diversity, structured into distinct genotypes that do not recombine with each other. Most of these hyper-variable genes encode glycoproteins involved in cell entry or escape of host immunity. Evidence that half of them have diverged through episodes of intense positive selection suggests that rapid evolution of hyper-variable loci is likely driven by interactions with host immunity. It appears that this process is enabled by recombination unlinking hyper-variable loci from strongly constrained neighboring sites. It is conceivable that viral mechanisms facilitating super-infection have evolved to promote recombination between diverged genotypes, allowing the virus to continuously diversify at key loci to escape immune detection, while maintaining a genome optimally adapted to its asymptomatic infectious lifecycle

    Genetic structure and evolution of the Leishmania genus in Africa and Eurasia: what does MLSA tell us

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    Leishmaniasis is a complex parasitic disease from a taxonomic, clinical and epidemiological point of view. The role of genetic exchanges has been questioned for over twenty years and their recent experimental demonstration along with the identification of interspecific hybrids in natura has revived this debate. After arguing that genetic exchanges were exceptional and did not contribute to Leishmania evolution, it is currently proposed that interspecific exchanges could be a major driving force for rapid adaptation to new reservoirs and vectors, expansion into new parasitic cycles and adaptation to new life conditions. To assess the existence of gene flows between species during evolution we used MLSA-based (MultiLocus Sequence Analysis) approach to analyze 222 Leishmania strains from Africa and Eurasia to accurately represent the genetic diversity of this genus. We observed a remarkable congruence of the phylogenetic signal and identified seven genetic clusters that include mainly independent lineages which are accumulating divergences without any sign of recent interspecific recombination. From a taxonomic point of view, the strong genetic structuration of the different species does not question the current classification, except for species that cause visceral forms of leishmaniasis (L. donovani, L. infantum and L. archibaldi). Although these taxa cause specific clinical forms of the disease and are maintained through different parasitic cycles, they are not clearly distinct and form a continuum, in line with the concept of species complex already suggested for this group thirty years ago. These results should have practical consequences concerning the molecular identification of parasites and the subsequent therapeutic management of the disease

    Population genomics of domestic and wild yeasts

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    The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker's yeast, _Saccharomyces cerevisiae_, and its closest relative, the wild _S. paradoxus_, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. _S. paradoxus_ populations are well delineated along geographic boundaries while the variation among worldwide _S. cerevisiae_ isolates show less differentiation and is comparable to a single _S. paradoxus_ population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of _S. cerevisiae_ shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation

    Does virulence assessment of Vibrio anguillarum using sea bass (Dicentrarchus labrax) larvae correspond with genotypic and phenotypic characterization?

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    Background: Vibriosis is one of the most ubiquitous fish diseases caused by bacteria belonging to the genus Vibrio such as Vibrio (Listonella) anguillarum. Despite a lot of research efforts, the virulence factors and mechanism of V. anguillarum are still insufficiently known, in part because of the lack of standardized virulence assays. Methodology/Principal Findings: We investigated and compared the virulence of 15 V. anguillarum strains obtained from different hosts or non-host niches using a standardized gnotobiotic bioassay with European sea bass (Dicentrarchus labrax L.) larvae as model hosts. In addition, to assess potential relationships between virulence and genotypic and phenotypic characteristics, the strains were characterized by random amplified polymorphic DNA (RAPD) and repetitive extragenic palindromic PCR (rep-PCR) analyses, as well as by phenotypic analyses using Biolog's Phenotype MicroArray (TM) technology and some virulence factor assays. Conclusions/Significance: Virulence testing revealed ten virulent and five avirulent strains. While some relation could be established between serotype, genotype and phenotype, no relation was found between virulence and genotypic or phenotypic characteristics, illustrating the complexity of V. anguillarum virulence. Moreover, the standardized gnotobiotic system used in this study has proven its strength as a model to assess and compare the virulence of different V. anguillarum strains in vivo. In this way, the bioassay contributes to the study of mechanisms underlying virulence in V. anguillarum

    Comparative Analysis Association and Prediction of Various Phenotypic Traits of Oryza Sativa

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    Understanding the genotype-phenotype relationship and accurately predicting breeding values are crucial aspects of crop improvement programs. This paper investigates the genetic basis ,association of phenotypic trait height and yield and predicts the phenotypic traits of Oryza Sativa (rice) through a comprehensive approach encompassing genome-wide association studies (GWAS), phylogenetic analysis, machine learning algorithms, and the development of a graphical user interface (GUI) application. Genotypic and phenotypic data were collected from the RiceVarMap database. The genotypic information consisted of gene variation IDs, while the phenotype data included plant height. Data preprocessing involved the creation of a sequence. fasta file and multiple sequence alignment using the ClustalW tool. A phylogenetic tree was then constructed to analyse the subpopulations of Oryza Sativa. Clustering techniques were applied to further explore the genetic relationships among the samples. A GWAS file was generated to identify associations between genotype and phenotype. Subsequently, machine learning algorithms were employed for the classification and prediction of genomic estimated breeding values (GEBV) for height and yield traits. Random Forest emerged as the most accurate algorithm with 85% accuracy. To facilitate user interaction and data exploration, a GUI application was developed using Flask, allowing users to access the phylogenetic tree, height, and yield information, GWAS results, and make predictions.  We explored there is a strong positive association between phenotypic trait height and yield
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