Evidence map›Paper›PMID 25159222›Full record

ArticleBMC genomics2014

HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers.

Qiyun Zhu, Michael Kosoy, Katharina Dittmar

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Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers.

0numbers the graph read from it
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117citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

117 citing papers in PubMed.

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57 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Qiyun ZhuDepartment of Biological Sciences, University at Buffalo, State University of New York, 109 Cooke Hall, Buffalo, NY 14260, USA. qiyunzhu@buffalo.edu.
Michael Kosoy
Katharina Dittmar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFirst pass methods based on BLAST match are commonly used as an initial step to separate the different phylogenetic histories of genes in microbial genomes, and target putative horizontal gene transfer (HGT) events. This will continue to be necessary given the rapid growth of genomic data and the technical difficulties in conducting large-scale explicit phylogenetic analyses. However, these methods often produce misleading results due to their inability to resolve indirect phylogenetic links and their vulnerability to stochastic events.

resultsA new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has a low requirement for computational resources.

conclusionsHGTector is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

Indexed as

Genes, BacterialGene Transfer, HorizontalSoftwareComputer SimulationEvolution, MolecularGenomicsModels, GeneticRickettsiaSearch Engine

Identifiers

PMID25159222
PMCPMC4155097

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.