The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
The phylogenomics of evolving virus virulence
Open accessAbstract
How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study. The virulence of viruses is a major determinant of the health burden of viral infections in humans and other species. In this article, Geoghegan and Holmes discuss how largely disparate research fields — theoretical modelling of virulence evolution and experimental dissection of genetic virulence determinants in laboratory model systems — can be bridged by considering real genomic data of viral evolution in a phylogenetic context. They describe the underlying principles of virulence evolution and how they apply to real-world viral infections and outbreaks of global importance.
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Cites
Nextstrain: real-time tracking of pathogen evolution
Hadfield, J., Megill, C., Bell, S. M., Huddleston, J., Potter, B., Callender, C., Sagulenko, P., Bedford, T., & Neher, R. A. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty407 · Cited by 3,154
The Population Genetics of dN/dS
Kryazhimskiy, S., & Plotkin, J. B. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000304 · Cited by 962
Towards a genomics-informed, real-time, global pathogen surveillance system
Gardy, J. L., & Loman, N. J. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2017.88 · Cited by 771
Evolution of Infectious Disease
Ewald, P. W. (1994) · doi:10.1093/oso/9780195060584.001.0001 · Cited by 714
Establishment and cryptic transmission of Zika virus in Brazil and the Americas
Faria, N. R., Quick, J., Claro, I. M., Thézé, J., de Jesus, J. G., Giovanetti, M., Kraemer, M. U. G., Hill, S. C., Black, A., da Costa, A. C., et al. (2017) · Nature · doi:10.1038/nature22401 · Cited by 616
Self-citationGenomic analysis of increased host immune and cell death responses induced by 1918 influenza virus
Kash, J. C., Tumpey, T. M., Proll, S. C., Carter, V., Perwitasari, O., Thomas, M. J., Basler, C. F., Palese, P., Taubenberger, J. K., García-Sastre, A., et al. (2006) · Nature · doi:10.1038/nature05181 · Cited by 551
Ancient adaptive evolution of the primate antiviral DNA-editing enzyme APOBEC3G
Sawyer, S. L., Emerman, M., & Malik, H. S. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020275 · Cited by 485
The evolution of Ebola virus: Insights from the 2013-2016 epidemic
Holmes, E. C., Dudas, G., Rambaut, A., & Andersen, K. G. (2016) · Nature · doi:10.1038/nature19790 · Cited by 314
Self-citationPredicting virus emergence amid evolutionary noise
Geoghegan, J. L., & Holmes, E. C. (2017) · Open Biology · doi:10.1098/rsob.170189 · Cited by 209
Self-citationThe Evolutionary Pathway to Virulence of an RNA Virus
Stern, A., Yeh, M. T., Zinger, T., Smith, M., Wright, C., Ling, G., Nielsen, R., Macadam, A., & Andino, R. (2017) · Cell · doi:10.1016/j.cell.2017.03.013 · Cited by 127
Cited by
After the pandemic: perspectives on the future trajectory of COVID-19
Telenti, A., Arvin, A., Corey, L., Corti, D., Diamond, M. S., García-Sastre, A., Garry, R. F., Holmes, E. C., Pang, P. S., & Virgin, H. W. (2021) · Nature · doi:10.1038/s41586-021-03792-w · Cited by 426
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Metadata
- Authors
- Geoghegan, J. L., & Holmes, E. C.
- Venue
- Nature Reviews Genetics
- Published
- 2018-10-10
- Volume
- 19
- Issue
- 12
- Pages
- 756-769
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2897661836
- Cited by
- 232
- References
- 10
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- bronze
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