Dataset Information

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity.

ABSTRACT:

Background

Large sequence datasets are difficult to visualize and handle. Additionally, they often do not represent a random subset of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases.

Results

Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity.

Conclusions

Treemmer can reduce the size of datasets with different phylogenetic structures and levels of redundancy while maintaining a sub-sample that is representative of the original diversity. Additionally, it is possible to fine-tune the behavior of Treemmer including any kind of meta-information, making Treemmer particularly useful for empirical studies.

SUBMITTER: Menardo F

PROVIDER: S-EPMC5930393 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Publications

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity.

Menardo Fabrizio F Loiseau Chloé C Brites Daniela D Coscolla Mireia M Gygli Sebastian M SM Rutaihwa Liliana K LK Trauner Andrej A Beisel Christian C Borrell Sonia S Gagneux Sebastien S

BMC bioinformatics 20180502 1

<h4>Background</h4>Large sequence datasets are difficult to visualize and handle. Additionally, they often do not represent a random subset of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases.<h4>Results</h4>Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity.<h4>Con ...[more]

PMID: 29716518

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Project description:Denitrification by sulfur-oxidizing bacteria is an effective nitrate removal strategy in engineered aquatic systems. However, the community taxonomic and metabolic diversity of sulfur-driven denitrification (SDN) systems, as well as the relationship between nitrate removal and SDN community structure, remains underexplored. This is particularly true for SDN reactors applied to marine aquaria, despite the increasing use of this technology to supplement filtration. We applied 16S rRNA gene, metagenomic, and metatranscriptomic analyses to explore the microbial basis of SDN reactors operating on Georgia Aquarium's Ocean Voyager, the largest indoor closed-system seawater exhibit in the United States. The exhibit's two SDN systems vary in water retention time and nitrate removal efficiency. The systems also support significantly different microbial communities. These communities contain canonical SDN bacteria, including a strain related to Thiobacillus thioparus that dominates the system with the higher water retention time and nitrate removal but is effectively absent from the other system. Both systems contain a wide diversity of other microbes whose metagenome-assembled genomes contain genes of SDN metabolism. These include hundreds of strains of the epsilonproteobacterium Sulfurimonas, as well as gammaproteobacterial sulfur oxidizers of the Thiotrichales and Chromatiales, and a relative of Sedimenticolathiotaurini with complete denitrification potential. The SDN genes are transcribed and the taxonomic richness of the transcript pool varies markedly among the enzymatic steps, with some steps dominated by transcripts from noncanonical SDN taxa. These results indicate complex and variable SDN communities that may involve chemical dependencies among taxa as well as the potential for altering community structure to optimize nitrate removal.IMPORTANCE Engineered aquatic systems such as aquaria and aquaculture facilities have large societal value. Ensuring the health of animals in these systems requires understanding how microorganisms contribute to chemical cycling and waste removal. Focusing on the largest seawater aquarium in the United States, we explore the microbial communities in specialized reactors designed to remove excess nitrogen through the metabolic activity of sulfur-consuming microbes. We show that the diversity of microbes in these reactors is both high and highly variable, with distinct community types associated with significant differences in nitrogen removal rate. We also show that the genes encoding the metabolic steps of nitrogen removal are distributed broadly throughout community members, suggesting that the chemical transformations in this system are likely a result of microbes relying on other microbes. These results provide a framework for future studies exploring the contributions of different community members, both in waste removal and in structuring microbial biodiversity.

Dataset Information

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity.

Background

Results

Conclusions

Publications

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity.

Similar Datasets

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