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

Autor: Lassalle F; UCL Genetics Institute, University College London, London, United Kingdom., Depledge DP; Division of Infection and Immunity, University College London, London, United Kingdom., Reeves MB; Division of Infection and Immunity, University College London, London, United Kingdom., Brown AC; Oxford Gene Technology, Begbroke, Oxfordshire, UK., Christiansen MT; Division of Infection and Immunity, University College London, London, United Kingdom., Tutill HJ; Division of Infection and Immunity, University College London, London, United Kingdom., Williams RJ; Division of Infection and Immunity, University College London, London, United Kingdom., Einer-Jensen K; QIAGEN-AAR, Aarhus, Denmark., Holdstock J; Oxford Gene Technology, Begbroke, Oxfordshire, UK., Atkinson C; Department of Virology, Royal Free Hospital, London, United Kingdom., Brown JR; Microbiology, Virology and Infection Prevention and Control, Camelia Botnar Laboratories, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom., van Loenen FB; Department of Viroscience, Erasmus, MC Rotterdam, the Netherlands., Clark DA; Department of Virology, Barts Health NHS Trust, London, United Kingdom., Griffiths PD; Division of Infection and Immunity, University College London, London, United Kingdom., Verjans GMGM; Department of Viroscience, Erasmus, MC Rotterdam, the Netherlands., Schutten M; Department of Viroscience, Erasmus, MC Rotterdam, the Netherlands., Milne RSB; Division of Infection and Immunity, University College London, London, United Kingdom., Balloux F; UCL Genetics Institute, University College London, London, United Kingdom., Breuer J; Division of Infection and Immunity, University College London, London, United Kingdom.
Jazyk: angličtina
Zdroj: Virus evolution [Virus Evol] 2016 Jun 15; Vol. 2 (1), pp. vew017. Date of Electronic Publication: 2016 Jun 15 (Print Publication: 2016).
DOI: 10.1093/ve/vew017
Abstrakt: 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.
Databáze: MEDLINE