Average Nucleotide Identity (ANI): A Measure of Genomic Similarity

Average Nucleotide Identity (ANI) is a computational metric used to quantify the genomic similarity between two microbial genomes. It measures the mean sequence identity across all orthologous regions—regions of the genome that are shared and aligned between the two organisms. ANI is widely used in microbial genomics and metagenomics to:

• Compare the similarity of bacterial or archaeal genomes.
• Define species boundaries (e.g., a threshold of 95–96% ANI is commonly used to delineate bacterial species).
• Identify redundant genomes in datasets, such as Metagenome-Assembled Genomes (MAGs), for de-replication.

How ANI Is Calculated

1. Genome Alignment: The genomes of two organisms are compared using whole-genome alignment tools (e.g., BLAST, MUMmer, or FastANI). These tools identify regions of the genomes that are homologous (shared due to common ancestry).
2. Identity Calculation: For each aligned region, the percentage of identical nucleotides is calculated. ANI is then computed as the mean identity across all aligned regions that meet a specified length threshold (e.g., regions \( \geq \) 1,000 base pairs).
3. Normalization: ANI accounts for unaligned regions (e.g., due to genomic rearrangements or horizontal gene transfer) by focusing only on the aligned portions of the genomes. This ensures the metric reflects conserved genomic similarity rather than absolute sequence coverage.

Interpreting ANI Values ANI values range from 0% to 100%, where:

• ANI \( \approx \) 100%: The genomes are nearly identical, likely representing strains of the same species or clones.
• ANI \( \geq \) 95–96%: The genomes likely belong to the same species (a widely accepted threshold for bacterial species delineation).
• ANI \( \approx \) 80–95%: The genomes belong to closely related species within the same genus.
• ANI \( < \) 80%: The genomes are distantly related and likely belong to different genera or higher taxonomic ranks.

Applications of ANI

1. Species Delineation: ANI is a gold standard for defining microbial species, replacing or complementing traditional methods like DNA-DNA hybridization (DDH). For example, an ANI \(\geq \) 95% is often used to confirm that two genomes belong to the same species.
2. De-Replication of MAGs: In metagenomics, ANI is used to identify and remove redundant MAGs from datasets. MAGs with ANI values above a threshold (e.g., 99%) are considered redundant, and only the highest-quality representative is retained for downstream analysis.
3. Strain-Level Comparisons: ANI can distinguish between closely related strains of the same species, helping researchers study microbial diversity at fine taxonomic resolutions.
4. Taxonomic Classification: ANI is used to assign unknown genomes to known taxonomic groups by comparing them to reference genomes in databases.

Tools for Calculating ANI

Several bioinformatics tools are available to compute ANI, including:

• FastANI ( Galaxy version 1.3) (Jain et al. 2018): A fast, alignment-free tool for estimating ANI between genomes.
• PyANI: A Python-based tool that supports multiple ANI calculation methods (e.g., BLAST, MUMmer).

Limitations of ANI

While ANI is a powerful metric, it has some limitations:

• Dependence on Alignment: ANI requires sufficiently aligned regions to be accurate. Highly divergent or rearranged genomes may yield unreliable ANI values.
• Threshold Variability: The ANI threshold for species delineation (e.g., 95%) may vary depending on the microbial group or study context.
• Computational Requirements: Calculating ANI for large datasets (e.g., thousands of MAGs) can be computationally intensive.

Average Nucleotide Identity (ANI) is a fundamental metric in microbial genomics, providing a robust way to compare genomes, define species, and refine metagenomic datasets. By leveraging ANI, researchers can ensure the accuracy and reliability of their genomic analyses, from species classification to de-replication of MAGs.

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