Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Department of Statistics, University of Oxford, Oxford, United Kingdom.
Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Department of Zoology, University of Oxford, Oxford, United Kingdom.
Despite the recent breakthroughs in the treatment of HCV infection, we have a limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and for evaluating the risk of drug-resistance mutations emerging and disseminating in a population.
We have undertaken a high-resolution analysis of HCV within-host evolution from four individuals co-infected with HIV. We used long-read, deep-sequenced data of the full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.
We found statistical support for population structure maintaining the within-host HCV genetic diversity in three out of four individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28x10 -7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.
Together, these observations indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.