HGTphyloDetect: facilitating the identification and phylogenetic analysis of horizontal gene transfer
Journal article, 2023

Horizontal gene transfer (HGT) is an important driver in genome evolution, gain-of-function, and metabolic adaptation to environmental niches. Genome-wide identification of putative HGT events has become increasingly practical, given the rapid growth of genomic data. However, existing HGT analysis toolboxes are not widely used, limited by their inability to perform phylogenetic reconstruction to explore potential donors, and the detection of HGT from both evolutionarily distant and closely related species.In this study, we have developed HGTphyloDetect, which is a versatile computational toolbox that combines high-throughput analysis with phylogenetic inference, to facilitate comprehensive investigation of HGT events. Two case studies with Saccharomyces cerevisiae and Candida versatilis demonstrate the ability of HGTphyloDetect to identify horizontally acquired genes with high accuracy. In addition, HGTphyloDetect enables phylogenetic analysis to illustrate a likely path of gene transmission among the evolutionarily distant or closely related species.The HGTphyloDetect computational toolbox is designed for ease of use and can accurately find HGT events with a very low false discovery rate in a high-throughput manner. The HGTphyloDetect toolbox and its related user tutorial are freely available at https:// github.com/SysBioChalmers/HGTphyloDetect.

gene transmission

evolution analysis

horizontal gene transfer

phylogenetic analysis

Author

Le Yuan

Chalmers, Life Sciences, Systems and Synthetic Biology

Hongzhong Lu

Shanghai Jiao Tong University

Feiran Li

National Academy of Sciences (NAS)

Jens B Nielsen

Chalmers, Life Sciences, Systems and Synthetic Biology

Eduard Kerkhoven

Chalmers, Life Sciences, Systems and Synthetic Biology

Briefings in Bioinformatics

1467-5463 (ISSN) 1477-4054 (eISSN)

Vol. 24 2 bbad035

Model-Based Construction And Optimisation Of Versatile Chassis Yeast Strains For Production Of Valuable Lipid And Aromatic Compounds (CHASSY)

European Commission (EC) (EC/H2020/720824), 2016-12-01 -- 2020-11-30.

Subject Categories

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

Genetics

DOI

10.1093/bib/bbad035

PubMed

36752380

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Latest update

3/7/2024 9