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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HumGut: a comprehensive human gut prokaryotic genomes collection filtered by metagenome data
Hiseni, P., Rudi, K., Wilson, R. C., Hegge, F. T., & Snipen, L. G. (2021) · Microbiome · doi:10.1186/s40168-021-01114-w · Cited by 116
bin3C: exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes
DeMaere, M. Z., & Darling, A. E. (2019) · Genome biology · doi:10.1186/s13059-019-1643-1 · Cited by 109
“0) [34] was used to calculate pairwise average nucleotide identity (ANI) between the 223 candidate genome sequences.”
Method
Metagenome-assembled genome extraction and analysis from microbiomes using KBase
Chivian, D. C., Jungbluth, S. P., Dehal, P., Wood‐Charlson, E. M., Canon, R. S., Allen, B. H., Clark, M. M., Gu, T., Land, M., Price, G. A., et al. (2022) · Nature Protocols · doi:10.1038/s41596-022-00747-x · Cited by 108
The genus Serratia revisited by genomics
Williams, D. J., Grimont, P. A. D., Cazares, A., Grimont, F., Ageron, E., Pettigrew, K. A., Cazares, D., Njamkepo, E., Weill, F., Heinz, E., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32929-2 · Cited by 110
The gut microbiota — brain axis of insects
Liberti, J., & Engel, P. (2020) · Current Opinion in Insect Science · doi:10.1016/j.cois.2020.01.004 · Cited by 113
High quality genome sequences of thirteen Hypoxylaceae (Ascomycota) strengthen the phylogenetic family backbone and enable the discovery of new taxa
Wibberg, D., Stadler, M., Lambert, C. R., Bunk, B., Spröer, C., Rückert, C., Kalinowski, J., Cox, R. J., & Kuhnert, E. (2020) · Fungal Diversity · doi:10.1007/s13225-020-00447-5 · Cited by 106
Niche and local geography shape the pangenome of wastewater- and livestock-associated Enterobacteriaceae
Shaw, L. P., Chau, K., Kavanagh, J., AbuOun, M., Stubberfield, E. J., Gweon, H. S., Barker, L., Rodger, G., Bowes, M. J., Hubbard, A. T. M., et al. (2021) · Science Advances · doi:10.1126/sciadv.abe3868 · Cited by 99
Single cell genomics reveals plastid-lacking Picozoa are close relatives of red algae
Schön, M., Zlatogursky, V. V., Singh, R., Poirier, C., Wilken, S., Mathur, V., Strassert, J. F. H., Pinhassi, J., Worden, A., Keeling, P., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26918-0 · Cited by 82
“0 100 200 300 EGTs Rattus norvegicus (0) Neurospora crassa (0) Dictyostelium discoideum (1) Tetrahymena thermophila (1) Thecamonas trahens (1) Cryptosporidium muris (3) Phytophthora capsici (6) Hematodinium sp SG-2012 (10) Paraphysomonas bandaiensis (12) Rhodelphids (14) Telonema subtile (15) Picozoa (16) Toxoplasma g…”
Background
GTDB release 10: a complete and systematic taxonomy for 715 230 bacterial and 17 245 archaeal genomes
Parks, D. H., Chaumeil, P.-A., Mussig, A. J., Rinke, C., Chuvochina, M. S., & Hugenholtz, P. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1040 · Cited by 163
“In terms of computational efficiency, we replaced FastANI [ 24 ] with skani [ 25 ] for calculating ANI and AF values in R09-RS220.”
Fueled by methane: deep-sea sponges from asphalt seeps gain their nutrition from methane-oxidizing symbionts
Rubin‐Blum, M., Antony, C. P., Sayavedra, L., Martínez‐Pérez, C., Birgel, D., Peckmann, J., Wu, Y.-C., Cárdenas, P., MacDonald, I. R., Marcon, Y., et al. (2019) · The ISME Journal · doi:10.1038/s41396-019-0346-7 · Cited by 104
Streptomyces Endophytes Promote Host Health and Enhance Growth across Plant Species
Worsley, S. F., Newitt, J., Rassbach, J., Batey, S. F. D., Holmes, N. A., Murrell, J. C., Wilkinson, B. M., & Hutchings, M. I. (2020) · Applied and Environmental Microbiology · doi:10.1128/aem.01053-20 · Cited by 105
“1%, respectively; these were below the 95% threshold that is generally used to assign strains to a known species (29, 30), and so they could be new Streptomyces species.”
A Genomic Perspective Across Earth’s Microbiomes Reveals That Genome Size in Archaea and Bacteria Is Linked to Ecosystem Type and Trophic Strategy
Rodríguez-Gijón, A., Nuy, J. K., Mehrshad, M., Buck, M., Schulz, F., Woyke, T., & Garcia, S. L. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.761869 · Cited by 105
Stable high-density and maternally inherited Wolbachia infections in Anopheles moucheti and Anopheles demeilloni mosquitoes
Walker, T., Quek, S., Jeffries, C. L., Bandibabone, J., Dhokiya, V., Bamou, R., Kristan, M., Messenger, L. A., Gidley, A., Hornett, E. A., et al. (2021) · Current Biology · doi:10.1016/j.cub.2021.03.056 · Cited by 101
Gemmatimonas groenlandica sp. nov. Is an Aerobic Anoxygenic Phototroph in the Phylum Gemmatimonadetes
Zeng, Y., Nupur, N., Wu, N., Madsen, A. M., Chen, X., Gardiner, A. T., & Koblížek, M. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2020.606612 · Cited by 103
“1.32; Jain et al., 2018) and CompareM (ver.”
BackgroundInfluential
The auxin-producing Bacillus thuringiensis RZ2MS9 promotes the growth and modifies the root architecture of tomato (Solanum lycopersicum cv. Micro-Tom)
Batista, B. D., Dourado, M. N., Figueredo, E. F., Hortencio, R. O., Marques, J. P. R., Piotto, F. Â., Bonatelli, M. L., Settles, M. L., de Azevedo, J. L., & Quecine, M. C. (2021) · Archives of Microbiology · doi:10.1007/s00203-021-02361-z · Cited by 108
An early origin of iron–sulfur cluster biosynthesis machineries before Earth oxygenation
Garcia, P. S., D’Angelo, F., de Choudens, S. O., Dussouchaud, M., Bouveret, E., Gribaldo, S., & Barras, F. (2022) · Nature Ecology & Evolution · doi:10.1038/s41559-022-01857-1 · Cited by 103
Rapid ecosystem-scale consequences of acute deoxygenation on a Caribbean coral reef
Johnson, M. D., Scott, J. J., Leray, M., Lucey, N., Bravo, L. M. R., Wied, W. L., & Altieri, A. H. (2021) · Nature Communications · doi:10.1038/s41467-021-24777-3 · Cited by 99
Identification and Characterization of 33 Bacillus cereus sensu lato Isolates from Agricultural Fields from Eleven Widely Distributed Countries by Whole Genome Sequencing
Zervas, A., Aggerbeck, M. R., Allaga, H., Güzel, M., Hendriks, M., Jonuškienė, I., Kedves, O., Kupeli, A., Lamovšek, J., Mülner, P., et al. (2020) · Microorganisms · doi:10.3390/microorganisms8122028 · Cited by 100
Bacterial endosymbionts protect beneficial soil fungus from nematode attack
Büttner, H., Niehs, S. P., Vandelannoote, K., Cseresnyés, Z., Dose, B., Richter, I., Gerst, R., Figge, M. T., Stinear, T. P., Pidot, S. J., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2110669118 · Cited by 100
Genome-based classification of Burkholderia cepacia complex provides new insight into its taxonomic status
Yuan, J., Zhou, J., Zhou, J., Hu, M., Zhang, Q., Kong, N., Ren, H., Liang, L., & Yue, J. (2020) · Biology Direct · doi:10.1186/s13062-020-0258-5 · Cited by 102
All ANIs are not created equal: implications for prokaryotic species boundaries and integration of ANIs into polyphasic taxonomy
Palmer, M., Steenkamp, E. T., Blom, J., Hedlund, B. P., & Venter, S. N. (2020) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.004124 · Cited by 102
Comprehensive mouse microbiota genome catalog reveals major difference to its human counterpart
Kieser, S., Zdobnov, E. M., & Trajkovski, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009947 · Cited by 99
“95% ANI was used as a threshold to delineate genomes from the same species [18,19].”
Method
StrainGE: a toolkit to track and characterize low-abundance strains in complex microbial communities
van Dijk, L. R., Walker, B. J., Straub, T. J., Worby, C. J., Grote, A., Schreiber, H. L., Anyansi, C., Pickering, A. J., Hultgren, S. J., Manson, A. L., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02630-0 · Cited by 93
“The reads from a metagenomic sample are then aligned to the concatenated reference using BWA mem (25), removing read pairs with 1) improper pairing; 2) clipped alignment; or 3) implied insert size smaller than the read length.”
MethodInfluential
Carbon fixation rates in groundwater similar to those in oligotrophic marine systems
Overholt, W. A., Trumbore, S. E., Xu, X., Bornemann, T. L. V., Probst, A. J., Krüger, M., Herrmann, M., Thamdrup, B., Bristow, L. A., Taubert, M., et al. (2022) · Nature Geoscience · doi:10.1038/s41561-022-00968-5 · Cited by 103
Taxonomic and carbon metabolic diversification of Bathyarchaeia during its coevolution history with early Earth surface environment
Hou, J., Wang, Y., Zhu, P., Yang, N., Liang, L., Yu, T., Niu, M., Konhauser, K. O., Woodcroft, B. J., & Wang, F. (2023) · Science Advances · doi:10.1126/sciadv.adf5069 · Cited by 108
“After removing the MAGs assigned to other microbial lineages, the average nuclear acid identities (ANIs) between pairwise sets of MAGs were calculated by using FastANI ( 82 ).”
Sequencing-based analysis of microbiomes
Pinto, Y., & Bhatt, A. S. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00746-6 · Cited by 109
“Whereas species boundaries are generally well defined, there is debate over the exact definition of ‘strains’ within microbiology 71–73 .”
Mobile antimicrobial resistance genes in probiotics
Tóth, A. G., Csabai, I., Judge, M. F., Maróti, G., Becsei, Á., Spisák, S., & Solymosi, N. (2021) · doi:10.1101/2021.05.04.442546 · Cited by 97
Metabolic diversity within the globally abundant Marine Group II Euryarchaea offers insight into ecological patterns
Tully, B. (2019) · Nature Communications · doi:10.1038/s41467-018-07840-4 · Cited by 92
Adlercreutzia equolifaciens Is an Anti-Inflammatory Commensal Bacterium with Decreased Abundance in Gut Microbiota of Patients with Metabolic Liver Disease
Oñate, F. P., Chamignon, C., Burz, S. D., Lapaque, N., Monnoye, M., Philippe, C., Bredel, M., Chêne, L., Farin, W., Paillarse, J.-M., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241512232 · Cited by 97
Ecosystem-wide metagenomic binning enables prediction of ecological niches from genomes
Alneberg, J., Bennke, C. M., Beier, S., Bunse, C., Quince, C., Ininbergs, K., Riemann, L., Ekman, M., Jürgens, K., Labrenz, M., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-0856-x · Cited by 93
Major genetic discontinuity and novel toxigenic species in Clostridioides difficile taxonomy
Knight, D. R., Imwattana, K., Kullin, B., Guerrero-Araya, E., Paredes‐Sabja, D., Didelot, X., Dingle, K. E., Eyre, D. W., Rodríguez, C., & Riley, T. V. (2021) · eLife · doi:10.7554/elife.64325 · Cited by 98
“…Center for Biotechnology Information (NCBI) (Ciufo et al., 2018), ANI provides a pre- cise, objective, and scalable method for delineation of species, defined as monophyletic groups of strains with genomes that exhibit at least 96% ANI (Jain et al., 2018; Richter and Rosselló-Móra, 2009).”
BackgroundMethodInfluential
Comprehensive dataset of shotgun metagenomes from oxygen stratified freshwater lakes and ponds
Buck, M., Garcia, S. L., Fernández, L., Martin, G., Martínez-Rodríguez, G. A., Saarenheimo, J., Zopfi, J., Bertilsson, S., & Peura, S. (2021) · Scientific Data · doi:10.1038/s41597-021-00910-1 · Cited by 96
proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes
Mende, D. R., Letunić, I., Maistrenko, O. M., Schmidt, T., Milanese, A., Paoli, L., Hernández-Plaza, A., Orakov, A. N., Forslund, S. K., Sunagawa, S., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1002 · Cited by 90
Defining the Rhizobium leguminosarum Species Complex
Young, J. P. W., Moeskjær, S., Afonin, A. М., Rahi, P., Maluk, M., James, E. K., Cavassim, M. I. A., Rashid, M. H.-O., Aserse, A. A., Perry, B. J., et al. (2021) · Genes · doi:10.3390/genes12010111 · Cited by 95
“31 [71] with the default settings (kmer = 16, fragment length = 3000, minimum shared fraction = 0.”
Background
Diet leaves a genetic signature in a keystone member of the gut microbiota
Dapa, T., Ramiro, R. S., Pedro, M. F., Gordo, I., & Xavier, K. B. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.01.002 · Cited by 91
Beyond DNA barcoding: The unrealized potential of genome skim data in sample identification
Bohmann, K., Mirarab, S., Bafna, V., & Gilbert, M. T. P. (2020) · Molecular Ecology · doi:10.1111/mec.15507 · Cited by 90
“(2018). A Sequel to Sanger: Amplicon sequencing that scales. BMC Genomics, 19(1), 219. https://doi.org/10.1186/s1286 4-018-4611-3 Hebert, P. D. N., Cywinska, A., Ball, S. L., & deWaard, J. R. (2003). Biological identifications through DNA barcodes. Proceedings. Biological Sciences/The Royal Society, 270(1512), 313–321…”
BackgroundInfluential
Genomic insights into the phylogeny and biomass-degrading enzymes of rumen ciliates
Li, Z., Wang, X., Zhang, Y., Yu, Z., Zhang, T., Dai, X., Pan, X., Jing, R., Yan, Y., Liu, Y., et al. (2022) · The ISME Journal · doi:10.1038/s41396-022-01306-8 · Cited by 100
Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile
Dove, N. C., Torn, M. S., Hart, S. C., & Taş, N. (2021) · Nature Communications · doi:10.1038/s41467-021-22408-5 · Cited by 96
Gut microbiota modulates weight gain in mice after discontinued smoke exposure
Fluhr, L., Mor, U., Kolodziejczyk, A. A., Dori-Bachash, M., Leshem, A., Itav, S., Cohen, Y., Suez, J., Zmora, N., Moresi, C., et al. (2021) · Nature · doi:10.1038/s41586-021-04194-8 · Cited by 95
Comparative Genome Analysis Reveals Phylogenetic Identity of Bacillus velezensis HNA3 and Genomic Insights into Its Plant Growth Promotion and Biocontrol Effects
Zaid, D. S., Cai, S., Hu, C., Li, Z., & Li, Y. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.02169-21 · Cited by 92
“The genomes of sequenced Bacillus strains were compared with the B. velezensis HNA3 genome using the average nucleotide identity analysis tool FastANI (92).”
Method
Functional Insights into the Kelp Microbiome from Metagenome-Assembled Genomes
Weigel, B. L., Miranda, K. K., Fogarty, E. C., Watson, A. R., & Pfister, C. A. (2022) · mSystems · doi:10.1128/msystems.01422-21 · Cited by 93
“The demarcation for a bacterial species using whole-genome average nucleotide identity (ANI) is typically$95% (35), while ANI values across genera average 73% (36).”
BackgroundMethodInfluential
Plant microbiomes harbor potential to promote nutrient turnover in impoverished substrates of a Brazilian biodiversity hotspot
Camargo, A. P., de Souza, R. S. C., José, J., Gerhardt, I. R., Dante, R. A., Mukherjee, S., Huntemann, M., Kyrpides, N. C., Carazzolle, M. F., & Arruda, P. (2022) · The ISME Journal · doi:10.1038/s41396-022-01345-1 · Cited by 92
Genome-based studies indicate that the Enterococcus faecium Clade B strains belong to Enterococcus lactis species and lack of the hospital infection associated markers
Daza, M. V. B., Cortimiglia, C., Bassi, D., & Cocconcelli, P. S. (2021) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.004948 · Cited by 96
A key genetic factor governing arabinan utilization in the gut microbiome alleviates constipation
Zhang, C., Yu, L., Ma, C., Jiang, S., Zhang, Y., Wang, S., Tian, F., Xue, Y., Zhao, J., Zhang, H., et al. (2023) · Cell Host & Microbe · doi:10.1016/j.chom.2023.10.011 · Cited by 98
Integrative omics analysis of the termite gut system adaptation to Miscanthus diet identifies lignocellulose degradation enzymes
Całusińska, M., Marynowska, M., Bertucci, M., Untereiner, B., Klimek, D., Goux, X., Sillam‐Dussès, D., Gawron, P., Halder, R., Wilmes, P., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-1004-3 · Cited by 87
Endophytic Bacteria From the Roots of the Medicinal Plant Alkanna tinctoria Tausch (Boraginaceae): Exploration of Plant Growth Promoting Properties and Potential Role in the Production of Plant Secondary Metabolites
Rat, A., Naranjo, H. D., Krigas, N., Grigoriadou, K., Maloupa, E., Alonso, A. V., Schneider, C., Papageorgiou, V. P., Assimopoulou, A. N., Tsafantakis, N., et al. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.633488 · Cited by 89
Extending and improving metagenomic taxonomic profiling with uncharacterized species with MetaPhlAn 4Preprint
Blanco‐Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.22.504593 · Cited by 89
Estimating Pangenomes with Roary
Sitto, F., & Battistuzzi, F. U. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz284 · Cited by 89
gcType: a high-quality type strain genome database for microbial phylogenetic and functional research
Shi, W., Sun, Q., Fan, G., Hideaki, S., Ohkuma, M., Itoh, T., Zhou, Y., Cai, M., Kim, S.-G., Lee, J., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa957 · Cited by 87
“Various genome similarity metrics, including ANIb (60), FastANI (61), orthoANIb and orthoANIu (62), are provided for the calculation of similarity between a submitted genome sequence and the selected sequences.”
Background
PanACoTA: A modular tool for massive microbial comparative genomicsPreprint
Perrin, A., & Rocha, E. P. C. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1093/nargab/lqaa106 · Cited by 103
“For example, using 15 cores, FastANI [27] requires around 1h15 to compare all pairs of 200 genomes (40,000 pairwise comparisons), where Mash with a sketch size of 106 does the task in less than 3 minutes.”
Method

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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