The DOI matches its Crossref record; 94 of the 94 references it cites were found in a registry or an index.
Phylosymbiosis: Relationships and Functional Effects of Microbial Communities across Host Evolutionary History
Open accessAbstract
Phylosymbiosis was recently proposed to describe the eco-evolutionary pattern, whereby the ecological relatedness of host-associated microbial communities parallels the phylogeny of related host species. Here, we test the prevalence of phylosymbiosis and its functional significance under highly controlled conditions by characterizing the microbiota of 24 animal species from four different groups (Peromyscus deer mice, Drosophila flies, mosquitoes, and Nasonia wasps), and we reevaluate the phylosymbiotic relationships of seven species of wild hominids. We demonstrate three key findings. First, intraspecific microbiota variation is consistently less than interspecific microbiota variation, and microbiota-based models predict host species origin with high accuracy across the dataset. Interestingly, the age of host clade divergence positively associates with the degree of microbial community distinguishability between species within the host clades, spanning recent host speciation events (~1 million y ago) to more distantly related host genera (~108 million y ago). Second, topological congruence analyses of each group's complete phylogeny and microbiota dendrogram reveal significant degrees of phylosymbiosis, irrespective of host clade age or taxonomy. Third, consistent with selection on host-microbiota interactions driving phylosymbiosis, there are survival and performance reductions when interspecific microbiota transplants are conducted between closely related and divergent host species pairs. Overall, these findings indicate that the composition and functional effects of an animal's microbial community can be closely allied with host evolution, even across wide-ranging timescales and diverse animal systems reared under controlled conditions.
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A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
MUSCLE: multiple sequence alignment with high accuracy and high throughput
Edgar, R. C. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh340 · Cited by 44,662
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies
Stamatakis, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu033 · Cited by 32,291
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,322
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 20,826
Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376
jModelTest 2: more models, new heuristics and parallel computing
Darriba, D., Taboada, G. L., Doallo, R., & Posada, D. (2012) · Nature Methods · doi:10.1038/nmeth.2109 · Cited by 16,785
UCHIME improves sensitivity and speed of chimera detection
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., & Knight, R. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr381 · Cited by 15,114
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Price, M. N., Dehal, P. S., & Arkin, A. P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009490 · Cited by 14,894
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Petrov, V. A., Saltykova, I. V., Zhukova, I. A., Alifirova, V. M., Zhukova, N. G., Dorofeeva, Y. B., Tyakht, A. V., Kovarsky, B. A., Alekseev, D. G., Kostryukova, E. S., et al. (2017) · Bulletin of Experimental Biology and Medicine · doi:10.1007/s10517-017-3700-7 · Cited by 487
The human microbiome in evolution
Davenport, E. R., Sanders, J. G., Song, S. J., Amato, K. R., Clark, A. G., & Knight, R. (2017) · BMC Biology · doi:10.1186/s12915-017-0454-7 · Cited by 393
Microbiomes as sources of emergent host phenotypes
Lynch, J. B., & Hsiao, E. Y. (2019) · Science · doi:10.1126/science.aay0240 · Cited by 339
Applying the core microbiome to understand host–microbe systems
Risely, A. (2020) · Journal of Animal Ecology · doi:10.1111/1365-2656.13229 · Cited by 363
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Amend, A., Burgaud, G., Cunliffe, M., Edgcomb, V. P., Ettinger, C. L., Gutiérrez, M. H., Heitman, J., Hom, E. F. Y., Ianiri, G., Jones, A. C., et al. (2019) · mBio · doi:10.1128/mbio.01189-18 · Cited by 339
Voolstra, C. R., & Ziegler, M. (2020) · BioEssays · doi:10.1002/bies.202000004 · Cited by 303
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Gaulke, C. A., Arnold, H. K., Humphreys, I. R., Kembel, S. W., O’Dwyer, J. P., & Sharpton, T. J. (2018) · mBio · doi:10.1128/mbio.01348-18 · Cited by 117
Metadata
- Authors
- Brooks, A. W., Kohl, K. D., Brucker, R. M., van Opstal, E. J., & Bordenstein, S. R.
- Venue
- PLOS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-11-18
- Volume
- 14
- Issue
- 11
- Pages
- e2000225
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- OpenAlex
- W2553365624
- Cited by
- 632
- References
- 94
- FWCI
- 55.85
- Type
- journal article
- Language
- en
- Open access
- gold
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