Detecting horizontal gene transfer: a probabilistic approach

Abstract Background Horizontal gene transfer (HGT) is the event of a DNA sequence being transferred between species not by inheritance. HGT is a crucial factor in prokaryotic evolution and is a significant source for genomic novelty resulting in antibiotic resistance or the outbreak of virulent stra...

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Bibliographic Details
Main Authors: Gur Sevillya, Orit Adato, Sagi Snir
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Genomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12864-019-6395-5
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Summary:Abstract Background Horizontal gene transfer (HGT) is the event of a DNA sequence being transferred between species not by inheritance. HGT is a crucial factor in prokaryotic evolution and is a significant source for genomic novelty resulting in antibiotic resistance or the outbreak of virulent strains. Detection of HGT and the mechanisms responsible and enabling it, is hence of prime importance.Existing algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from its recipient genome. Closely related species pose an even greater challenge as most genes are very similar and therefore, the phylogenetic signal is weak anyhow. Notwithstanding, the importance of detecting HGT between such organisms is extremely high for the role of HGT in the emergence of new highly virulent strains. Results In a recent work we devised a novel technique that relies on loss of synteny around a gene as a witness for HGT. We used a novel heuristic for synteny measurement, SI (Syntent Index), and the technique was tested on both simulated and real data and was found to provide a greater sensitivity than other HGT techniques. This synteny–based approach suffers low specificity, in particular more closely related species. Here we devise an adaptive approach to cope with this by varying the criteria according to species distance. The new approach is doubly adaptive as it also considers the lengths of the genes being transferred. In particular, we use Chernoff bound to decree HGT both in simulations and real bacterial genomes taken from EggNog database. Conclusions Here we show empirically that this approach is more conservative than the previous χ 2 based approach and provides a lower false positive rate, especially for closely related species and under wide range of genome parameters.
ISSN:1471-2164