GWarrange: a pre- and post- genome-wide association studies pipeline for detecting phenotype-associated genome rearrangement events

TL;DR

GWarrange is a pipeline that uses k-mers to detect genome rearrangements linked to phenotypes in bacterial genome-wide association studies.

Contribution

GWarrange introduces a novel method to interpret k-mers in the context of genome rearrangements using placeholder sequences for repeats.

Findings

GWarrange successfully identifies genome rearrangements associated with phenotypes in bacterial species.

The pipeline replaces repeat sequences with placeholders to improve k-mer analysis of rearrangement boundaries.

Case studies on Bordetella pertussis and Enterococcus faecium demonstrate the pipeline's effectiveness.

Abstract

The use of k-mers to capture genetic variation in bacterial genome-wide association studies (bGWAS) has demonstrated its effectiveness in overcoming the plasticity of bacterial genomes by providing a comprehensive array of genetic variants in a genome set that is not confined to a single reference genome. However, little attempt has been made to interpret k-mers in the context of genome rearrangements, partly due to challenges in the exhaustive and high-throughput identification of genome structure and individual rearrangement events. Here, we present GWarrange, a pre- and post-bGWAS processing methodology that leverages the unique properties of k-mers to facilitate bGWAS for genome rearrangements. Repeat sequences are common instigators of genome rearrangements through intragenomic homologous recombination, and they are commonly found at rearrangement boundaries. Using whole-genome sequences, repeat sequences are replaced by short placeholder sequences, allowing the regions flanking repeats to be incorporated into relatively short k-mers. Then, locations of flanking regions in significant k-mers are mapped back to complete genome sequences to visualise genome rearrangements. Four case studies based on two bacterial species (Bordetella pertussis and Enterococcus faecium) and a simulated genome set are presented to demonstrate the ability to identify phenotype-associated rearrangements. GWarrange is available at https://github.com/DorothyTamYiLing/GWarrangehttps://github.com/DorothyTamYiLing/genome_rearrangement.git.

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