ReviewApplied and environmental microbiology2025
Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes.
Review in Applied and environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed.
- A bacterial pangenome association study identifies a role for polyamine metabolism and alkaline tolerance in middle ear infections.PLoS pathogens · 2026Article
- Genome shuffling enables quantitative trait locus mapping in Bacillus subtilis.Nature communications · 2026Article
- Skin Infection Pathogenicity Associated with a Canine Microbiome Resident: Polygenic Architecture of Virulence Factors inAntibiotics (Basel, Switzerland) · 2026Article
- A genome-wide association study to identify the genetic loci underlying carbapenem resistance in Acinetobacter baumannii.BMC genomics · 2026Article
- Convergent evolution of ST2 and ST164 mediates dissemination of the blaAnnals of clinical microbiology and antimicrobials · 2026Article
- Host genomic regulation of ileal Bradyrhizobium abundance modulates eating speed and fat metabolism in birds: a causal mechanism study.Journal of animal science and biotechnology · 2026Article
- Utilizing whole genome sequencing data for machine learning driven prediction of antibiotic resistance inFrontiers in microbiology · 2026Article
- Genomic and Phenotypic Bases of Salt Tolerance in Sinorhizobium meliloti: Candidate Traits for Bioinoculant Development Addressing Saline Soils.Microbial biotechnology · 2026Article
- Strainify: Strain-Level Microbiome Profiling for Low-Coverage Short-Read Metagenomic Datasets.bioRxiv : the preprint server for biology · 2025Article
- Bacterial Systematic Genetics and Integrated Multi-Omics: Beyond Static Genomics Toward Predictive Models.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
With the continuous advancements in high-throughput genome sequencing technologies and the development of innovative bioinformatics tools, bacterial genome-wide association studies (BGWAS) have emerged as a transformative approach for investigating the genetic variations underlying diverse bacterial phenotypes at the population genome level. This review provides a comprehensive overview of the application of BGWAS in elucidating genetic determinants of bacterial drug resistance, pathogenicity, host specificity, biofilm formation, and probiotic fermentation characteristics. We systematically summarize the BGWAS workflow, including study design, data analysis pipelines, and the bioinformatics software employed at various stages. Furthermore, we highlight specialized tools tailored for BGWAS and discuss their unique features and applications. We also discuss confounding factors that can influence the accuracy and reliability of BGWAS results, including population structure, linkage disequilibrium, and multiple testing. By incorporating recent advancements, this review serves as a comprehensive reference for researchers utilizing BGWAS to uncover the genetic basis of bacterial phenotypes.
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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.