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Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus

Like many viruses, Hepatitis C Virus (HCV) has a high mutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly usef...

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Autores principales: Tisthammer, Kaho H., Solis, Caroline, Orcales, Faye, Nzerem, Madu, Winstead, Ryan, Dong, Weiyan, Joy, Jeffrey B., Pennings, Pleuni S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113599/
https://www.ncbi.nlm.nih.gov/pubmed/35500034
http://dx.doi.org/10.1371/journal.pgen.1010179
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author Tisthammer, Kaho H.
Solis, Caroline
Orcales, Faye
Nzerem, Madu
Winstead, Ryan
Dong, Weiyan
Joy, Jeffrey B.
Pennings, Pleuni S.
author_facet Tisthammer, Kaho H.
Solis, Caroline
Orcales, Faye
Nzerem, Madu
Winstead, Ryan
Dong, Weiyan
Joy, Jeffrey B.
Pennings, Pleuni S.
author_sort Tisthammer, Kaho H.
collection PubMed
description Like many viruses, Hepatitis C Virus (HCV) has a high mutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimate in vivo fitness costs, but this approach works best with deep sequencing data from many hosts are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show that in vivo fitness costs of mutations can be site and virus specific, reinforcing the utility of constructing in vivo fitness cost maps of viral genomes.
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spelling pubmed-91135992022-05-18 Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus Tisthammer, Kaho H. Solis, Caroline Orcales, Faye Nzerem, Madu Winstead, Ryan Dong, Weiyan Joy, Jeffrey B. Pennings, Pleuni S. PLoS Genet Research Article Like many viruses, Hepatitis C Virus (HCV) has a high mutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimate in vivo fitness costs, but this approach works best with deep sequencing data from many hosts are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show that in vivo fitness costs of mutations can be site and virus specific, reinforcing the utility of constructing in vivo fitness cost maps of viral genomes. Public Library of Science 2022-05-02 /pmc/articles/PMC9113599/ /pubmed/35500034 http://dx.doi.org/10.1371/journal.pgen.1010179 Text en © 2022 Tisthammer et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tisthammer, Kaho H.
Solis, Caroline
Orcales, Faye
Nzerem, Madu
Winstead, Ryan
Dong, Weiyan
Joy, Jeffrey B.
Pennings, Pleuni S.
Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title_full Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title_fullStr Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title_full_unstemmed Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title_short Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
title_sort assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of hepatitis c virus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113599/
https://www.ncbi.nlm.nih.gov/pubmed/35500034
http://dx.doi.org/10.1371/journal.pgen.1010179
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