Exploration of the genetic landscape of bacterial dsDNA viruses reveals an ANI gap amid extensive mosaicism.

ABSTRACT: Average nucleotide identity (ANI) is a widely used metric to estimate genetic relatedness, especially in microbial species delineation. While ANI calculation has been well optimized for bacteria and closely related viral genomes, accurate estimation of ANI below 80%, particularly in large reference data sets, has been challenging due to a lack of accurate and scalable methods. To bridge this gap, we introduce MANIAC, an efficient computational pipeline optimized for estimating ANI and alignment fraction (AF) in viral genomes with divergence around ANI of 70%. Using a rigorous simulation framework, we demonstrate MANIAC's accuracy and scalability compared to existing approaches, even to data sets of hundreds of thousands of viral genomes. Applying MANIAC to a curated data set of complete ba

SUBMITTER: Ndovie W 

PROVIDER: S-EPMC11834439 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature