Jun  Wang , Qikun  Huang

Microbial Resources Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Computational Molecular Biology, 2025, Vol. 15, No. 6   
Received: 20 Nov., 2025    Accepted: 12 Dec., 2025    Published: 25 Dec., 2025

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Horizontal gene transfer (HGT) plays a crucial role in microbial evolution and the diversification of soil ecosystem functions. This study employed computational methods to detect and analyze HGT events in agricultural soil microbiomes, aiming to reveal how gene transfer shapes microbial community dynamics and ecological functions. Metagenomic data were generated from soil samples collected from conventional and organic farming systems, then assembled, binned, and annotated to identify potential donor and recipient species. Combining sequence-based comparative genomics, composition-based analysis, and machine learning models, common mobile genetic elements and gene families associated with environmental adaptation and antibiotic resistance were detected. The results indicate that HGT significantly promotes microbial resilience and nutrient cycling in soil ecosystems and is influenced by environmental parameters such as pH and nutrient availability. This study provides a methodological framework for computational HGT detection and offers new insights into microbial evolution, soil health, and sustainable agricultural management. Future research integrating multi-omics data and standardized benchmarks will improve the accuracy and ecological interpretability of HGT studies.

Horizontal gene transfer; Soil microbiome; Metagenomics; Computational biology; Microbial ecology