ArticleEvolutionary bioinformatics online2018
Prediction of Horizontally and Widely Transferred Genes in Prokaryotes.
Article in Evolutionary bioinformatics online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Identification of virulence genes and clade-specific markers through pan-genomic analysis of Leptospira.BMC microbiology · 2025Article
- Metagenomic analyses of gut microbiome composition and function with age in a wild bird; little change, except increased transposase gene abundance.ISME communications · 2025Article
- Long-read sequencing reveals extensive gut phageome structural variations driven by genetic exchange with bacterial hosts.Science advances · 2024Article
- Article
- ARTS 2.0: feature updates and expansion of the Antibiotic Resistant Target Seeker for comparative genome mining.Nucleic acids research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Horizontal gene transfer (HGT) is the process whereby an organism acquires exogenous genes (horizontally transferred genes or HT genes) that are not inherited from the parent, but are derived from another organism. In prokaryotes, HGT has been considered as one of the important driving forces of evolution. Previously, genome-wide analyses have been conducted for estimating the proportion of HT genes in prokaryotic genomes, but the number of species examined at the time was limited, and gene annotation was relatively poor. Currently, tens of thousands of prokaryotic genomes have been published and gene annotation resources have improved. In the present study, HT gene prediction method was modified so that the estimate was robust to gene length, conducting a comprehensive search using 3017 representative prokaryotic genomes belonging to 1348 species. The result showed that an average of 13% (ranging from 0% to 30% across species) of protein-coding genes was predicted as being of horizontal origin. The proportion of the predicted HT genes per species was associated with the species' habitat, while a positive correlation between the proportion and genomic nucleotide frequency was also observed. Moreover, the functions of the predicted HT genes were inferred and compared according to two popular databases, the Clusters of Orthologous Groups and the Kyoto Encyclopedia of Genes and Genomes. As a result, both databases indicated that many of the widely transferred genes were involved in mobile genetic elements (transposons, phages, and plasmids) as expected. Notably, the present study predicted that six as-yet-uncharacterized genes were widely distributed HT genes, and therefore, will be interesting targets for evolutionary studies. Thus, this study demonstrates that a data-driven approach using massive sequence data may contribute to a broader understanding of HGT in prokaryotes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.