The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
Viruses are a dominant driver of protein adaptation in mammals
Open accessAbstract
Viruses interact with hundreds to thousands of proteins in mammals, yet adaptation against viruses has only been studied in a few proteins specialized in antiviral defense. Whether adaptation to viruses typically involves only specialized antiviral proteins or affects a broad array of virus-interacting proteins is unknown. Here, we analyze adaptation in ~1300 virus-interacting proteins manually curated from a set of 9900 proteins conserved in all sequenced mammalian genomes. We show that viruses (i) use the more evolutionarily constrained proteins within the cellular functions they interact with and that (ii) despite this high constraint, virus-interacting proteins account for a high proportion of all protein adaptation in humans and other mammals. Adaptation is elevated in virus-interacting proteins across all functional categories, including both immune and non-immune functions. We conservatively estimate that viruses have driven close to 30% of all adaptive amino acid changes in the part of the human proteome conserved within mammals. Our results suggest that viruses are one of the most dominant drivers of evolutionary change across mammalian and human proteomes.
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UCSF Chimera—A visualization system for exploratory research and analysis
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20084 · Cited by 45,828
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
PAML 4: Phylogenetic Analysis by Maximum Likelihood
Yang, Z. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm088 · Cited by 13,879
<tt>BLAT</tt> —The <tt>BLAST</tt> -Like Alignment Tool
Kent, W. J. (2002) · Genome Research · doi:10.1101/gr.229202 · Cited by 8,480
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Gene Ontology Consortium: going forward
The Gene Ontology Consortium (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1179 · Cited by 3,492
Adaptive protein evolution at the Adh locus in Drosophila
McDonald, J. H., & Kreitman, M. (1991) · Nature · doi:10.1038/351652a0 · Cited by 3,283
HyPhy: hypothesis testing using phylogenies
Pond, S. L. K., Frost, S. D. W., & Muse, S. V. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti079 · Cited by 2,866
A draft map of the human proteome
Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., Madugundu, A. K., Kelkar, D. S., Isserlin, R., Jain, S., et al. (2014) · Nature · doi:10.1038/nature13302 · Cited by 2,198
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Creanza, N., Kolodny, O., & Feldman, M. W. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620732114 · Cited by 482
Gene expression variability across cells and species shapes innate immunity
Hagai, T., Chen, X., Miragaia, R. J., Rostom, R., Gomes, T., Kunowska, N., Henriksson, J., Park, J.-E., Proserpio, V., Donati, G., et al. (2018) · Nature · doi:10.1038/s41586-018-0657-2 · Cited by 220
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Enard, D., & Petrov, D. A. (2018) · Cell · doi:10.1016/j.cell.2018.08.034 · Cited by 208
Self-citationA structure-informed atlas of human-virus interactions
Lasso, G., Mayer, S. V., Winkelmann, E. R., Chu, T., Elliot, O., Patino-Galindo, J. A., Park, K., Rabadan, R., Honig, B., & Shapira, S. D. (2019) · Cell · doi:10.1016/j.cell.2019.08.005 · Cited by 133
Hawash, M. B. F., Sanz-Remón, J., Grenier, J.-C., Kohn, J., Yotova, V., Johnson, Z., Lanford, R. E., Brinkworth, J. F., & Barreiro, L. B. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2015855118 · Cited by 56
Metadata
- Authors
- Enard, D., Cai, L., Gwennap, C., & Petrov, D. A.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2016-05-17
- Volume
- 5
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W2304458632
- Cited by
- 361
- References
- 76
- FWCI
- 24.71
- Type
- journal article
- Language
- en
- Open access
- gold
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