The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Predicting microbial traits with phylogenies
Open accessAbstract
Phylogeny reflects genetic and phenotypic traits in Bacteria and Archaea. The phylogenetic conservatism of microbial traits has prompted the application of phylogeny-based algorithms to predict unknown trait values of extant taxa based on the traits of their evolutionary relatives to estimate, for instance, rRNA gene copy numbers, gene contents or tolerance to abiotic conditions. Unlike the ‘macrobial’ world, microbial ecologists face scenarios potentially compromising the accuracy of trait reconstruction methods, as, for example, extremely large phylogenies and limited information on the traits of interest. We review 990 bacterial and archaeal traits from the literature and support that phylogenetic trait conservatism is widespread through the tree of life, while revealing that it is generally weak for ecologically relevant phenotypic traits and high for genetically complex traits. We then perform a simulation exercise to assess the accuracy of phylogeny-based trait predictions in common scenarios faced by microbial ecologists. Our simulations show that ca. 60% of the variation in phylogeny-based trait predictions depends on the magnitude of the trait conservatism, the number of species in the tree, the proportion of species with unknown trait values and the mean distance in the tree to the nearest neighbour with a known trait value. Results are similar for both binary and continuous traits. We discuss these results under the light of the reviewed traits and provide recommendations for the use of phylogeny-based trait predictions for microbial ecologists.
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The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
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Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
Improving the coverage of the cyanobacterial phylum using diversity driven genome sequencing
Shih, P. M., Wu, D., Latifi, A., Axen, S. D., Fewer, D. P., Talla, E., Calteau, A., Cai, F., Tandeau de Marsac, N., Rippka, R., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217107110 · Cited by 800
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Cited by
Consistent and correctable bias in metagenomic sequencing experiments
McLaren, M. R., Willis, A. D., & Callahan, B. J. (2019) · eLife · doi:10.7554/elife.46923 · Cited by 429
Microbial functional diversity: From concepts to applications
Escalas, A., Hale, L., Voordeckers, J. W., Yang, Y., Firestone, M. K., Alvarez‐Cohen, L., & Zhou, J. (2019) · Ecology and Evolution · doi:10.1002/ece3.5670 · Cited by 265
A Guided Tour of Phylogenetic Comparative Methods for Studying Trait Evolution
Cornwallis, C. K., & Griffin, A. S. (2024) · Annual Review of Ecology, Evolution, and Systematics · doi:10.1146/annurev-ecolsys-102221-050754 · Cited by 37
Trait‐based approach to bacterial growth efficiency
Muscarella, M. E., Howey, X. M., & Lennon, J. T. (2020) · Environmental Microbiology · doi:10.1111/1462-2920.15120 · Cited by 30
Metadata
- Authors
- Goberna, M., & Verdú, M.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-09-15
- Volume
- 10
- Issue
- 4
- Pages
- 959-967
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W2203017743
- Cited by
- 197
- References
- 4
- FWCI
- 7.87
- Type
- journal article
- Language
- en
- Open access
- green
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