Average Nucleotide Identity, commonly abbreviated as ANI, is one of the most widely used genomic metrics for comparing microbial genomes. It measures the average nucleotide similarity between shared genomic regions of two genomes.
In microbial genomics, ANI is frequently used to evaluate whether two bacterial or archaeal genomes belong to the same species, to compare closely related organisms and to support taxonomic interpretation in genome-based studies.
ANI measures the mean nucleotide identity between orthologous genomic regions shared by two genomes. In practice, one genome is fragmented and compared against another genome to identify matching regions and calculate their average sequence identity.
The resulting percentage provides a quantitative estimate of whole-genome similarity. A high ANI value indicates that two genomes are very similar, while a lower ANI value suggests greater genomic divergence.
ANI has become a standard approach for genome-based microbial species delineation. Historically, bacterial species were often defined using DNA-DNA hybridisation, phenotypic traits and marker genes such as 16S rRNA. Genome sequencing has made it possible to evaluate species boundaries more precisely using whole-genome comparisons.
A commonly used threshold around 95-96% ANI is often considered consistent with species-level relatedness for many bacteria and archaea. However, this threshold should be interpreted carefully and in relation to taxonomy, biology and the quality of the genomes analysed.
ANI can help clarify taxonomic relationships between isolates, reference genomes and public genomic databases. It is particularly useful when species identification based on marker genes is ambiguous or when closely related taxa are difficult to distinguish.
In microbial R&D, ANI can help determine whether a newly sequenced strain is close to a known species, belongs to a recognised taxonomic group or may require deeper taxonomic investigation.
ANI is useful for comparing genomes at the species level, but it is not always sufficient for high-resolution strain discrimination. Two strains may show very high ANI values while still differing in SNPs, plasmids, accessory genes, structural variations or industrial phenotypes.
For this reason, ANI is often used as an initial genomic similarity metric, followed by more detailed analyses such as SNP analysis, pangenome analysis, core genome comparison or synteny analysis.
ANI depends on genome quality, assembly completeness, contamination level and the proportion of shared genomic regions. Poor-quality assemblies or incomplete genomes may affect the reliability of ANI values.
ANI also does not directly explain functional differences between strains. It provides a global similarity measure, but additional comparative genomics analyses are needed to identify genes, mutations or structural events that may explain biological or industrial properties.
For industrial microbiology, ANI can be useful during strain identification, database comparison, taxonomic validation and initial genomic characterisation. It helps position a strain within a broader microbial group before performing more targeted analyses.
In fermentation, probiotics, food biotechnology, environmental microbiology or animal health, ANI can support the first step of a genomic workflow by confirming the relationship between candidate strains, reference genomes and public isolates.
ANI is often part of a broader comparative genomics strategy. It provides a global similarity estimate, while other approaches provide deeper insight into genomic differences.
For related concepts, read our articles on comparative genomics for industrial strain selection, SNP analysis, pangenome analysis and genome assembly.
Biomanda provides bioinformatics services for microbial genomics, taxonomic interpretation and comparative genomics. Depending on the project, Biomanda can support genome assembly quality assessment, ANI calculation, reference genome comparison, database screening, SNP analysis, pangenome analysis and biological interpretation.
The objective is to help companies and research teams transform genome sequences into reliable information for strain identification, taxonomy, R&D decisions and industrial microbiology projects.
Average Nucleotide Identity is a key metric in microbial genomics. It provides a genome-wide estimate of similarity and helps support species-level interpretation, taxonomic validation and initial strain characterisation.
However, ANI should not be used alone when the objective is to understand functional differences between closely related strains. It is most powerful when integrated into a broader comparative genomics workflow.