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      Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes.

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          Abstract

          Among available genome relatedness indices, average nucleotide identity (ANI) is one of the most robust measurements of genomic relatedness between strains, and has great potential in the taxonomy of bacteria and archaea as a substitute for the labour-intensive DNA-DNA hybridization (DDH) technique. An ANI threshold range (95-96%) for species demarcation had previously been suggested based on comparative investigation between DDH and ANI values, albeit with rather limited datasets. Furthermore, its generality was not tested on all lineages of prokaryotes. Here, we investigated the overall distribution of ANI values generated by pairwise comparison of 6787 genomes of prokaryotes belonging to 22 phyla to see whether the suggested range can be applied to all species. There was an apparent distinction in the overall ANI distribution between intra- and interspecies relationships at around 95-96% ANI. We went on to determine which level of 16S rRNA gene sequence similarity corresponds to the currently accepted ANI threshold for species demarcation using over one million comparisons. A twofold cross-validation statistical test revealed that 98.65% 16S rRNA gene sequence similarity can be used as the threshold for differentiating two species, which is consistent with previous suggestions (98.2-99.0%) derived from comparative studies between DDH and 16S rRNA gene sequence similarity. Our findings should be useful in accelerating the use of genomic sequence data in the taxonomy of bacteria and archaea.

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          Author and article information

          Journal
          Int J Syst Evol Microbiol
          International journal of systematic and evolutionary microbiology
          Microbiology Society
          1466-5034
          1466-5026
          Feb 2014
          : 64
          : Pt 2
          Affiliations
          [1 ] School of Biological Sciences, Seoul National University, Seoul 151-742, Republic of Korea.
          [2 ] Interdisciplinary Program in Bioinformatics and Bioinformatics Institute, Seoul National University, Seoul 151-742, Republic of Korea.
          Article
          10.1099/ijs.0.059774-0
          24505072
          cb4346b7-95ec-4d53-906d-25fcffdf5053
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