High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries

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.

Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy

“…This result is in contrast to reports of a genetic discontinuum between 83% to 95% ANI (Jain et al, 2018). These apparently contradictory results may reflect differences in how species were defined, but is primarily the result of changing the perspective from all pairwise comparisons in a large genomic dataset (Jain et al, 2018) to the inter-genus ANI values between closest species representatives (this study; Kim et al, 2014). This latter perspective suggests a fairly smooth continuum of inter-species generic diversity within genera which, despite the results presented here, may ultimately challenge efforts to unambiguously define species boundaries using ANI as additional species are discovered (Hanage, 2013).…”

“…4D). This result is in contrast to reports of a genetic discontinuum between 83% to 95% ANI (Jain et al, 2018). These apparently contradictory results may reflect differences in how species were defined, but is primarily the result of changing the perspective from all pairwise comparisons in a large genomic dataset (Jain et al, 2018) to the inter-genus ANI values between closest species representatives (this study; Kim et al, 2014).…”

“…Here we were interested in an operational species definition that facilitates the automated assignment of genomes to species and that scales to large datasets in order to allow all available and forthcoming genomes to be organized into species clusters. This can be achieved using whole-genome ANI which has emerged as a robust and widely accepted method for circumscribing species (Ciufo et al, 2018;Chun et al, 2018), with 95% ANI found to recapitulate the majority of existing species (Konstantinidis and Tiedje, 2005b;Jain et al, 2018;Olm et al, 2019). Further supporting the use of ANI is its strong correlation with DNA-DNA hybridization which was considered the gold standard for circumscribing bacterial and archaeal species for decades (Goris et al, 2007).…”

“…ANI is determined from the similarity of orthologous regions shared between two genomes (Konstantinidis and Tiedje, 2005a) and a number of methods have been proposed for calculating this statistic (Richter M and Rosselló-Móra, 2009;Varghese et al, 2015;Yoon et al, 2017). Here we made use of two recent advances in calculating ANI that allow tens of thousands of genomes to be organized into species clusters; a fast heuristic for approximating ANI (Mash: Ondov et al, 2016) and a computationally efficient approach highly correlated with the results of traditional methods (FastANI: Jain et al, 2018).…”

Microbial composition of Kombucha determined using amplicon sequencing and shotgun metagenomics

“…Contig sequences were aligned to raw data using BWA (Li & Durbin, 2009) and placed into taxonomic bins with MetaBat2 (Kang, Froula, Egan, & Wang, 2015) using a minimum contig length of 2,000 bp. The comparison and dereplication of recovered genomes bins were completed using dRep (Olm, Brown, Brooks, & Banfield, 2017) with minimum primary Average Nucleotide Identity (ANI) 60% (Varghese et al, 2015) and minimum secondary ANI 95% (Jain, Rodriguez-R, Phillippy, Konstantinidis, & Aluru, 2018). CheckM (Parks, Imelfort, Skennerton, Hugenholtz, & Tyson, 2015) was used to determine completeness and contamination of the best genomes selected by dRep analysis.…”