PaSiT: a novel approach based on short-oligonucleotide frequencies for efficient bacterial identification and typing

Gleb Goussarov, Ilse Cleenwerck, Mohamed Mysara, Natalie Leys, Pieter Monsieurs, Guillaume Tahon, Aurélien Carlier, Peter Vandamme, Rob Van Houdt

Research output: Contribution to journalA1: Web of Science-article

Abstract

MOTIVATION: One of the most widespread methods used in taxonomy studies to distinguish between strains or taxa is the calculation of average nucleotide identity. It requires a computationally expensive alignment step and is therefore not suitable for large-scale comparisons. Short oligonucleotide-based methods do offer a faster alternative but at the expense of accuracy. Here, we aim to address this shortcoming by providing a software that implements a novel method based on short-oligonucleotide frequencies to compute inter-genomic distances.

RESULTS: Our tetranucleotide and hexanucleotide implementations, which were optimized based on a taxonomically well-defined set of over 200 newly sequenced bacterial genomes, are as accurate as the short oligonucleotide-based method TETRA and average nucleotide identity, for identifying bacterial species and strains, respectively. Moreover, the lightweight nature of this method makes it applicable for large-scale analyses.

AVAILABILITY AND IMPLEMENTATION: The method introduced here was implemented, together with other existing methods, in a dependency-free software written in C, GenDisCal, available as source code from https://github.com/LM-UGent/GenDisCal. The software supports multithreading and has been tested on Windows and Linux (CentOS). In addition, a Java-based graphical user interface that acts as a wrapper for the software is also available.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish
JournalBioinformatics
Volume36
Issue number8
Pages (from-to)2337-2344
Number of pages8
ISSN1367-4803
DOIs
Publication statusPublished - 2020
Externally publishedYes

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