ArticleBMC bioinformatics2019
Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Article
- Biofilm-forming traits enrich the plasmid diversity and functional potential in particle-attached bacteria in coastal ecosystems.Microbiology spectrum · 2026Article
- Foliar metal micronutrients reshape rhizosphere soil multifunctionality by filtering microbial life-history strategies.NPJ biofilms and microbiomes · 2026Article
- Large-scale estimation of bacterial and archaeal DNA prevalence in metagenomes reveals biome-specific patterns.mSystems · 2026Article
- Carbon regime structures functional trait trajectories during primary succession in microorganisms.The ISME journal · 2026Article
- Bridging ecological processes to elevated antibiotic resistance risk in tomato microbiome under fungicide stress.The ISME journal · 2026Article
- Conservation agriculture buffers persistent carbon loss under warming by microbial adaptation.The ISME journal · 2026Article
- Soil Nutrient Enrichment Induces Trade-Offs in Bacterial Life-History Strategies Promoting Plant Productivity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Eutrophication Reshapes Microbial Communities and Life-History Strategies in the Riverine Ecosystems.Environmental microbiology reports · 2025Article
- Differences in the genomic potential of soil bacterial and viral communities between urban greenspaces and natural arid soils.Applied and environmental microbiology · 2025Article
- Microbial life-history strategies and genomic traits between pristine and cropland soils.mSystems · 2025Article
- Characterizing Wheat Rhizosphere Bacterial Microbiome Dynamics Under Salinity Stress: Insights from 16S rRNA Metagenomics for Enhancing Stress Tolerance.Plants (Basel, Switzerland) · 2025Article
- Increasing pesticide diversity impairs soil microbial functions.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Eutrophication shifts microbial communities and life-history strategies in the Yangtze River Estuary.Frontiers in microbiology · 2025Article
- The adaptability of grassland soil microbiomes to resource and stress shifts is mainly accomplished by niche conservatism under nitrogen deposition.ISME communications · 2025Article
- Bacterial genome size and gene functional diversity negatively correlate with taxonomic diversity along a pH gradient.Nature communications · 2023Article
- Life history strategies of soil bacterial communities across global terrestrial biomes.Nature microbiology · 2023Article
- Robbsia betulipollinis sp. nov., Isolated from Pollen of Birch (Betula pendula).Current microbiology · 2023Article
- Linking prokaryotic genome size variation to metabolic potential and environment.ISME communications · 2023Article
- Abiotic selection of microbial genome size in the global ocean.Nature communications · 2023Article
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3 authors.
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Abstract
backgroundMetagenomics caused a quantum leap in microbial ecology. However, the inherent size and complexity of metagenomic data limit its interpretation. The quantification of metagenomic traits in metagenomic analysis workflows has the potential to improve the exploitation of metagenomic data. Metagenomic traits are organisms' characteristics linked to their performance. They are measured at the genomic level taking a random sample of individuals in a community. As such, these traits provide valuable information to uncover microorganisms' ecological patterns. The Average Genome Size (AGS) and the 16S rRNA gene Average Copy Number (ACN) are two highly informative metagenomic traits that reflect microorganisms' ecological strategies as well as the environmental conditions they inhabit.
resultsHere, we present the ags.sh and acn.sh tools, which analytically derive the AGS and ACN metagenomic traits. These tools represent an advance on previous approaches to compute the AGS and ACN traits. Benchmarking shows that ags.sh is up to 11 times faster than state-of-the-art tools dedicated to the estimation AGS. Both ags.sh and acn.sh show comparable or higher accuracy than existing tools used to estimate these traits. To exemplify the applicability of both tools, we analyzed the 139 prokaryotic metagenomes of TARA Oceans and revealed the ecological strategies associated with different water layers.
conclusionWe took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools to combine easy tool usage with fast and accurate performance. Our tools compute the AGS and ACN metagenomic traits on unassembled metagenomes and allow researchers to improve their metagenomic data analysis to gain deeper insights into microorganisms' ecology. The ags.sh and acn.sh tools are publicly available using Docker container technology at https://github.com/pereiramemo/AGS-and-ACN-tools .
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