The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes

Angly, Florent E., Willner, Dana, Prieto-Davó, Alejandra, Edwards, Robert A., Schmieder, Robert, Vega-Thurber, Rebecca, Antonopoulos, Dionysios A., Barott, Katie, Cottrell, Matthew T., Desnues, Christelle, Dinsdale, Elizabeth A., Furlan, Mike, Haynes, Matthew, Henn, Matthew R., Hu, Yongfei, Kirchman, David L., McDole, Tracey, McPherson, John D., Meyer, John D., Miller, R. Michael, Mundt, Egbert, Naviaux, Robert K., Rodriguez-Mueller, Beltran, Stevens, Rick, Wegley, Linda, Zhang, Lixin, Zhu, Baoli and Rohwer, Forest (2009) The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes. PLoS Computational Biology, 5 12: e1000593.1-e1000593.10. doi:10.1371/journal.pcbi.1000593

Author Angly, Florent E.
Willner, Dana
Prieto-Davó, Alejandra
Edwards, Robert A.
Schmieder, Robert
Vega-Thurber, Rebecca
Antonopoulos, Dionysios A.
Barott, Katie
Cottrell, Matthew T.
Desnues, Christelle
Dinsdale, Elizabeth A.
Furlan, Mike
Haynes, Matthew
Henn, Matthew R.
Hu, Yongfei
Kirchman, David L.
McDole, Tracey
McPherson, John D.
Meyer, John D.
Miller, R. Michael
Mundt, Egbert
Naviaux, Robert K.
Rodriguez-Mueller, Beltran
Stevens, Rick
Wegley, Linda
Zhang, Lixin
Zhu, Baoli
Rohwer, Forest
Title The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes
Journal name PLoS Computational Biology   Check publisher's open access policy
ISSN 1553-734X
Publication date 2009-12-01
Sub-type Article (original research)
DOI 10.1371/journal.pcbi.1000593
Open Access Status DOI
Volume 5
Issue 12
Start page e1000593.1
End page e1000593.10
Total pages 10
Place of publication San Francisco, CA, U.S.A.
Publisher Public Library of Science
Language eng
Formatted abstract
Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions.
Keyword Field gel-electrophoresis
Statistical significance
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Chemistry and Molecular Biosciences
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Citation counts: TR Web of Science Citation Count  Cited 130 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 22 Feb 2011, 00:30:10 EST