Title |
Introducing EzAAI: a pipeline for high throughput calculations of prokaryotic average amino acid identity |
Author |
Dongwook Kim, Sein Park, and Jongsik Chun |
Address |
Interdisciplinary Program in Bioinformatics, Institute of Molecular Biology & Genetics, School of Biological Sciences, Seoul National University, Seoul 08826, Republic of Korea |
Bibliography |
Journal of Microbiology, 59(5),476–480, 2021,
|
DOI |
10.1007/s12275-021-1154-0
|
Key Words |
average amino acid identity, comparative genomics,
phylogeny, software suite |
Abstract |
The average amino acid identity (AAI) is an index of pairwise
genomic relatedness, and multiple studies have proposed its
application in prokaryotic taxonomy and related disciplines.
AAI demonstrates better resolution in elucidating taxonomic
structure beyond the species rank when compared with average
nucleotide identity (ANI), which is a standard criterion
in species delineation. However, an efficient and easy-to-use
computational tool for AAI calculation in large-scale taxonomic
studies is not yet available. Here, we introduce a bioinformatic
pipeline, named EzAAI, which allows for rapid
and accurate AAI calculation in prokaryote sequences. The
EzAAI tool is based on the MMSeqs2 program and computes
AAI values almost identical to those generated by the standard
BLAST algorithm with significant improvements in the
speed of these evaluations. Our pipeline also provides a function
for hierarchical clustering to create dendrograms, which
is an essential part of any taxonomic study. EzAAI is available
for download as a standalone JAVA program at http://
leb.snu.ac.kr/ezaai. |