Cited by 5,748Genomics and Phylogenetic StudiesBacterial Identification and Susceptibility TestingMicrobial Community Ecology and Physiology

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High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries

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Jain, Chirag, Rodriguez-R, Luis M., Phillippy, Adam M., Konstantinidis, Konstantinos T., Aluru, Srinivas·2018·Nature Communications

DOI 10.1038/s41467-018-07641-9PMC PMC6269478

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Abstract

A fundamental question in microbiology is whether there is continuum of genetic diversity among genomes, or clear species boundaries prevail instead. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) help address this question by facilitating high resolution taxonomic analysis of thousands of genomes from diverse phylogenetic lineages. To scale to available genomes and beyond, we present FastANI, a new method to estimate ANI using alignment-free approximate sequence mapping. FastANI is accurate for both finished and draft genomes, and is up to three orders of magnitude faster compared to alignment-based approaches. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal clear genetic discontinuity, with 99.8% of the total 8 billion genome pairs analyzed conforming to >95% intra-species and <83% inter-species ANI values. This discontinuity is manifested with or without the most frequently sequenced species, and is robust to historic additions in the genome databases.

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Fig. 1 Correlation of FastANI and Mash-based ANI output with ANIb values for datasets D1–D5. Because FastANI assumes a probabilistic identity cutoff that is set to 80% by default, it reports 76, 570, 4271, 464, and 130 genome matches for the individual queries in datasets D1–D5 respectively. To enable a direct quality comparison against FastANI, Mash is executed for only those pairs that are reported by FastANI. Notice that each dataset encompasses a different nucleotide identity range (x-axes). Gray line represents a straight line y = x plot for reference. Pearson correlation coefficients corresponding to these plots are listed separately in Table 2. Last plot shows error of these methods w.r.t. ANIb using all five datasetsCC BY · PubMed Central

Fig. 2 Scaling up FastANI’s performance using multi-core parallel execution. We executed parallel FastANI processes on 40 physical cores, where each process was assigned an equally sized part of the reference D1–D5 databases. Left and right plots evaluate FastANI’s compute and indexing phase, respectively. FastANI achieves reasonable speedups on all datasets except the compute phase in D1 and D5, as their runtime on a single core is too small to begin with (Table 3)CC BY · PubMed Central

Fig. 3 Genetic discontinuity observed using 90 K genomes. a Histogram plot showing the distribution of ANI values among the 90 K genomes. Only ANI values in the 76–100% range are shown. Out of total 8.01 billion pairwise genome comparisons, FastANI reported only 17M ANI values (0.21%) with ANI between 83 and 95% indicating a genetic discontinuum. Multiple colors are used to show how genomes from different genera are contributing to this distribution. Few peaks in the histogram arise from genera that have been extensively sequenced and dominate the database. b Density curves of ANI values in the ANI range 76–100%. Each curve shows the density curve corresponding to the database at a particular time period. Discontinuity in all four curves is observed consistently. c. Distribution of ANI values with each comparison labeled by the nomenclature of genomes being compared. All the comparisons between Escherichia coli and Shigella spp. have been labeled separately. The 95% ANI threshold on x-axis serves as a valid classifier for comparisons belonging to same and different speciesCC BY · PubMed Central

Fig. 4 FastANI algorithm explained using synthetic and real examples. a Illustration of FastANI’s work-flow for computing ANI between a query genome and a reference genome. Five mappings are obtained from three query fragments using Mashmap24. Mforward saves the maximum identity mapping for each query fragment. In this example, Mforward = {m2, m4, m5}. From this set, Mreciprocal picks m4 and m5 as the maximum identity mapping for each reference bin. Mapping identities of orthologous mappings, thus found in Mreciprocal, are finally averaged to compute ANI. b FastANI supports visualization of the orthologous mappings Mreciprocal that are used to estimate the ANI value using genoPlotR39. In this figure, ANI is computed between Bartonella quintana strain (NC_018533.1) as query and Bartonella henselae strain (NC_005956.1) as reference. Red line segments denote the orthologous mappings computed by FastANI for ANI estimationCC BY · PubMed Central

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“31 (70) was used to estimate average nucleotide identity across plasmid and MGE structures with default settings.”
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“SGBs were de ﬁ ned on 95% average nucleotide identity, a measure generally regarded as appropriate 72 , but it is nevertheless prone to clade speci ﬁ c biases, potentially further in ﬂ u-enced by altered speciation dynamics in association with (evolutionary) changes in host lifestyle 73 , i.e .…”
Influential
Time-shifted expression of acetoclastic and methylotrophic methanogenesis by a single Methanosarcina genomospecies predominates the methanogen dynamics in Philippine rice field soil
Li, X., Bei, Q., Nematabad, M. R., Peng, J., & Liesack, W. (2024) · Microbiome · doi:10.1186/s40168-023-01739-z · Cited by 44
“FastANI was used to calculate genome average nucleotide identity (ANI) values [65].”
BackgroundMethod
metaProbiotics: a tool for mining probiotic from metagenomic binning data based on a language model
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“To identify the bins associated with the intervening strain, we used fastaANI [81] (v1.”
Method
Antagonism as a foraging strategy in microbial communities
Stubbusch, A. K., Peaudecerf, F. J., Lee, K. S., Paoli, L., Schwartzman, J. A., Stocker, R., Basler, M., Schubert, O. T., Ackermann, M., Magnabosco, C., et al. (2025) · Science · doi:10.1126/science.adr8286 · Cited by 47
FungAMR: a comprehensive database for investigating fungal mutations associated with antimicrobial resistance
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Dialogue on the nomenclature and classification of prokaryotes
Rossello-Mora, R. A., & Whitman, W. B. (2018) · Systematic and Applied Microbiology · doi:10.1016/j.syapm.2018.07.002 · Cited by 44
Ecogenomic characterization of widespread, closely-related SAR11 clades of the freshwater genus “Candidatus Fonsibacter” and proposal of Ca. Fonsibacter lacus sp. nov
Tsementzi, D., Rodriguez‐R, L. M., Ruiz-Pérez, C. A., Meziti, A., Hatt, J. K., & Konstantinidis, K. T. (2019) · Systematic and Applied Microbiology · doi:10.1016/j.syapm.2019.03.007 · Cited by 44
Self-citation
Chromulinavorax destructans, a pathogen of microzooplankton that provides a window into the enigmatic candidate phylum Dependentiae
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Switching on the light: using metagenomic shotgun sequencing to characterize the intestinal microbiome of Atlantic cod
Riiser, E. S., Haverkamp, T. H. A., Varadharajan, S., Borgan, Ø., Jakobsen, K. S., Jentoft, S., & Star, B. (2019) · Environmental Microbiology · doi:10.1111/1462-2920.14652 · Cited by 41
Phylogenomic Classification and Biosynthetic Potential of the Fossil Fuel-Biodesulfurizing Rhodococcus Strain IGTS8
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Extended-Spectrum Beta-Lactamase Producing-Escherichia coli Isolated From Irrigation Waters and Produce in Ecuador
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“The identification of genus and species of the isolates was carried out using fastANI (Jain et al., 2018) with a percentage >80% of identification.”
Method
Genomic insights of high-risk clones of ESBL-producing Escherichia coli isolated from community infections and commercial meat in southern Brazil
Soncini, J. G. M., Cerdeira, L., Sano, E., Koga, V. L., Tizura, A. T., Tano, Z. N., Nakazato, G., Kobayashi, R. K. T., Aires, C. A. M., Lincopán, N., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-13197-y · Cited by 43
Streptococcus suis outbreak caused by an emerging zoonotic strain with acquired multi-drug resistance in Thailand
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“32 against eight complete S. suis genomes and one complete Streptococcus parasuis genome to confirm the species classification of the isolates (Table S1) [34].”
Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation
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Defence systems and horizontal gene transfer in bacteria
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Two decades of bacterial ecology and evolution in a freshwater lake
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FastAAI: efficient estimation of genome average amino acid identity and phylum-level relationships using tetramers of universal proteins
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“…of FastAAI-based AAI values within phyla to determine whether or not reliable AAI thresholds can be identified that distinguish different ranks, similar to the 95% ANI that distinguishes (different) species [ 4 ] or the thresholds that distinguish domain and phylum ranks mentioned above.”
InfluentialSelf-citation
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Self-citation
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“, using FastANI [4], in the fact that traditional ANI represents the average nucleotide identity of all orthologous genes shared by any two genomes while the ANI of core genes represents the average nucleotide identity of the core genes shared by a pair of genomes.”
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Contrasting patterns of microbial dominance in the Arabidopsis thaliana phyllosphere
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Description of Erysipelothrix piscisicarius sp. nov., an emergent fish pathogen, and assessment of virulence using a tiger barb (Puntigrus tetrazona) infection model
Pomaranski, E. K., Griffin, M. J., Camus, A. C., Armwood, A. R., Shelley, J., Waldbieser, G. C., LaFrentz, B. R., García, J. C., Yanong, R. P. E., & Soto, E. (2019) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.003838 · Cited by 42
Escherichia ruysiae sp. nov., a novel Gram-stain-negative bacterium, isolated from a faecal sample of an international traveller
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“Sequence similarities between SARS-CoV-2 genome pairs were computed using the software FastANI, which uses a high throughput method for average nucleotide identity analysis [21].”
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Strain Identification and Quantitative Analysis in Microbial Communities
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“Average nucleotide identity (ANI) values for genomes of interest were calculated using FastANI [47].”
BackgroundMethod
High-risk Escherichia coli clones that cause neonatal meningitis and association with recrudescent infection
Nhu, N. T. K., Phan, M., Hancock, S. J., Peters, K. M., Álvarez-Fraga, L., Forde, B. M., Andersen, S. B., Miliya, T., Harris, P. N. A., Beatson, S. A., et al. (2023) · eLife · doi:10.7554/elife.91853 · Cited by 41
“Assembled contigs 432 were subject to taxonomic profiling using kraken2 [55] and fastANI [58].”
Method
Christensenella strain resources, genomic/metabolomic profiling, and association with host at species level
Sun, X., Huang, H., Wang, X., Wei, R.-Q., Niu, H.-Y., Chen, H. Y., Luo, M., Abdugheni, R., Wang, Y., Liu, F.-L., et al. (2024) · Gut Microbes · doi:10.1080/19490976.2024.2347725 · Cited by 42
“ Sifarchaeota ,” a Novel Asgard Phylum from Costa Rican Sediment Capable of Polysaccharide Degradation and Anaerobic Methylotrophy
Farag, I., Zhao, R., & Biddle, J. F. (2021) · Applied and Environmental Microbiology · doi:10.1128/aem.02584-20 · Cited by 37
“In addition to phylogenomic analysis, we calculated the average nucleotide identity (ANI) using FastANI (34) and average amino acid identity (AAI) using CompareM (https://github.”
Method
Microbial iron and carbon metabolism as revealed by taxonomy-specific functional diversity in the Southern Ocean
Sun, Y., Debeljak, P., & Obernosterer, I. (2021) · The ISME Journal · doi:10.1038/s41396-021-00973-3 · Cited by 41
Genome-resolved metagenome and metatranscriptome analyses of thermophilic composting reveal key bacterial players and their metabolic interactions
Braga, L. P. P., Pereira, R. V., Martins, L. F., Moura, L. M. S., Sanchez, F. B., Patané, J. S. L., da Silva, A. M., & Setúbal, J. C. (2021) · BMC Genomics · doi:10.1186/s12864-021-07957-9 · Cited by 42
Antimicrobial Resistance in Campylobacter coli and Campylobacter jejuni from Human Campylobacteriosis in Taiwan, 2016 to 2019
Liao, Y.-S., Chen, B.-H., Teng, R.-H., Wang, Y.-W., Chang, J.-H., Liang, S.-Y., Tsao, C.-S., Hong, Y.-P., Sung, H.-Y., & Chiou, C. (2021) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01736-21 · Cited by 41
“com/ParBLiSS/FastANI) (62), antimicrobial resistance genes using AMRFinderPlus (https://www.”
Method
Population differentiation of Rhodobacteraceae along with coral compartments
Luo, D., Wang, X., Feng, X., Tian, M., Wang, S., Tang, S., Ang, P. O., Yan, A., & Luo, H. (2021) · The ISME Journal · doi:10.1038/s41396-021-01009-6 · Cited by 41
Comparative Genome Analysis of ‘Candidatus Phytoplasma luffae’ Reveals the Influential Roles of Potential Mobile Units in Phytoplasma Evolution
Huang, C.-T., Cho, S., Lin, Y.-C., Tan, C., Chiu, Y.-C., Yang, J., & Kuo, C. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.773608 · Cited by 40
“1 (Jain et al., 2018) was used to calculate the proportion of genomic segments mapped and the average nucleotide identity (ANI).”
Method
Genomic Evidence for the Recycling of Complex Organic Carbon by Novel Thermoplasmatota Clades in Deep-Sea Sediments
Zheng, P., Wei, Z., Zhou, Y., Li, Q., Qi, Z., Diao, X., & Wang, Y. (2022) · mSystems · doi:10.1128/msystems.00077-22 · Cited by 40
“The MAG Bin162 for clade A from SY40 was much different from those for clade B (Bin292, Bin295, and Bin296) in SY153 with ANI values of 69 to 70%, which is much lower than the values for a moderate affinity (ANI 80 to 90%) (33) and supports the divergency between the two marine clades.”
Result
Comparing genomes recovered from time-series metagenomes using long- and short-read sequencing technologies
Orellana, L. H., Krüger, K., Sidhu, C., & Amann, R. (2023) · Microbiome · doi:10.1186/s40168-023-01557-3 · Cited by 40
Intraspecific microdiversity and ecological drivers of lactic acid bacteria in naturally fermented milk ecosystem
You, L., Jin, H., Kwok, L., Lv, R., Zhao, Z., Bilige, M., Sun, Z., Liu, W., & Zhang, H. (2023) · 中国科学通报：英文版 · doi:10.1016/j.scib.2023.09.001 · Cited by 43
Global emergence of Escherichia coli with PBP3 insertions
Long, H., Zhao, F., Feng, Y., & Zong, Z. (2024) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/dkae393 · Cited by 40
A designed synthetic microbiota provides insight to community function in Clostridioides difficile resistance
Tian, S., Kim, M. S., Zhao, J., Heber, K., Hao, F., Koslicki, D., Tian, S., Singh, V., Patterson, A. D., & Bisanz, J. E. (2025) · Cell Host & Microbe · doi:10.1016/j.chom.2025.02.007 · Cited by 44

Authors: Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T., & Aluru, S.
Affiliations: National Institutes of Health (US)
Georgia Institute of Technology (US)
Corresponding author: Konstantinidis, Konstantinos T.
Aluru, Srinivas
ORCID: Jain, Chirag
Rodriguez-R, Luis M.
Phillippy, Adam M.
Konstantinidis, Konstantinos T.
Aluru, Srinivas
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2018-11-30
Volume: 9
Issue: 1
Pages: 5114-5114
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-018-07641-9
PMC: PMC6269478
OpenAlex: W2951254987
Cited by: 5,748
References: 40
Citations by year: 2026: 1107 · 2025: 1110 · 2024: 977 · 2023: 789 · 2022: 695 · 2021: 617 · 2020: 305 · 2019: 128 · 2018: 16
FWCI: 96.11
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Nature Communications (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, other-oa)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders: National Science Foundation (1416259, 1816027, 1356288)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Health Sciences › Medicine › Microbiology (medical) › Bacterial Identification and Susceptibility Testing
Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
Keywords: average nucleotide identity, prokaryotic genomes, species boundaries, taxonomic classification, draft genome sequence
MeSH terms: Phylogeny, Prokaryotic Cells, Genetic Variation, Databases, Factual, Genome, Bacterial, Sequence Analysis, DNA

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High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries

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