Mapping-based horizontal gene transfer detection from sequencing data – enhancing metagenomic approaches for pathogen identification
Year: 2016
Type: other
Abstract: Horizontal gene transfer (HGT) is a fundamental mechanism that enables organisms such as bacteria to directly transfer genetic material between distant species. This way, for instance, bacteria can acquire antibiotic resistance genes or pathogenic toxins with possible severe consequences for public health. Current bioinformatics approaches focus on the detection of past HGT events by exploring phylogenetic tree or genome composition inconsistencies. To the best of our knowledge, so far, no approach uses next-generation sequencing (NGS) data or methods. A mapping-based approach offers the chance of detecting HGT events in the sequenced HGT organism early in analyses, even when the HGT organism has not been sequenced before. We propose the tools Daisy and Donald, novel mapping-based pipelines for HGT detection from NGS data. Donald leverages metagenomic profiling tools to identify candidate references for the acceptor genome reference (the parent genome of the HGT organism acquiring the HGT sequence) and the donor genome reference (the parent donating the HGT sequence). Subsequently, Daisy determines specific HGT regions relying on established methods from structural variant detection approved for human NGS data. Preliminary results of simulated and real data show that Donald successfully identifies acceptor and donor candidates as such and is able to distinguish non-HGT samples as true negatives. Daisy detects HGT regions with base pair resolution, and outperforms alternative approaches using a genome assembly of the reads. We see our approach as a powerful complement for comprehensive analysis of bacterial genomes in the context of NGS data.
Institution: Robert Koch Institute
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W2624482434