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Data from: Telling the whole story in a 10,000-genome world

Citation

Beiko, Robert G. (2012), Data from: Telling the whole story in a 10,000-genome world, Dryad, Dataset, https://doi.org/10.5061/dryad.gf39c8dc

Abstract

BACKGROUND: Genome sequencing has revolutionized our view of the relationships among genomes, particularly in revealing the confounding effects of lateral genetic transfer (LGT). Phylogenomic techniques have been used to construct purported trees of microbial life. Although such trees are easily interpreted and allow the use of a subset of genomes as "proxies" for the full set, LGT and other phenomena impact the positioning of different groups in genome trees, confounding and potentially invalidating attempts to construct a phylogeny-based taxonomy of microorganisms. Network and graph approaches can reveal complex sets of relationships, but applying these techniques to large data sets is a significant challenge. Notwithstanding the question of what exactly it might represent, generating and interpreting a Tree or Network of All Genomes will only be feasible if current algorithms can be improved upon. RESULTS: Complex relationships among even the most-similar genomes demonstrate that proxy-based approaches to simplifying large sets of genomes are not alone sufficient to solve the analysis problem. A phylogenomic analysis of 1173 sequenced bacterial and archaeal genomes generated phylogenetic trees for 159,905 distinct homologous gene sets. The relationships inferred from this set can be heavily dependent on the inclusion of other taxa: for example, phyla such as Spirochaetes, Proteobacteria and Firmicutes are recovered as cohesive groups or split depending on the presence of other specific lineages. Furthermore, named groups such as Acidithiobacillus, Coprothermobacter and Brachyspira show a multitude of affiliations that are more consistent with their ecology than with small subunit ribosomal DNA-based taxonomy. Network and graph representations can illustrate the multitude of conflicting affinities, but all methods impose constraints on the input data and create challenges of construction and interpretation. CONCLUSIONS: These complex relationships highlight the need for an inclusive approach to genomic data, and current methods with minor alterations will likely scale to allow the analysis of data sets with 10,000 or more genomes. The main challenges lie in the visualization and interpretation of genomic relationships, and the redefinition of microbial taxonomy when subsets of genomic data are so evidently in conflict with one another, and with the "canonical" molecular taxonomy.

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