Computational Molecular Biology 2025, Vol.15, No.6, 299-306 http://bioscipublisher.com/index.php/cmb 300 detailed understanding of the role of HGT in soil microbial ecology and its evolutionary significance, and provide some operational references for how to deal with gene flow in environmental management. 2 Ecological Context of HGT in Soil Microbiomes 2.1 Diversity and complexity of microbial life in soil ecosystems Before discussing how genes flow in the soil, one point is easily overlooked: the soil itself is an extremely crowded and complex "microbial city". All kinds of bacteria are mixed together, sometimes competing and sometimes cooperating, and the community structure is thus constantly changing. This high degree of diversity cannot be maintained simply by evolutionary accumulation. Many microorganisms actually rely on horizontal gene transfer (HGT) to maintain the vitality and adaptability of the community (Coyte et al., 2022a; Zhu et al., 2024). Especially in the rhizosphere and mycelial sphere, microbial interactions are particularly frequent, and there are more opportunities for gene exchange, which often makes this area be regarded as a place where the complexity of the community is "magnified". Of course, not all regions are so active, but overall, the diversity of soil microorganisms is indeed inseparable from this kind of gene flow. 2.2 Environmental conditions influencing gene exchange (e.g., pH, moisture, nutrients) The occurrence of HGT is not exactly the same in different soil environments. pH, humidity, the amount of nutrients, and even the presence of pollutants can all influence the frequency and mode of gene exchange. For instance, after the application of manure, foreign microorganisms and mobile genetic elements (MGEs) will rush in within a short period of time, thereby making the HGT slightly more active. However, in soils containing antibiotics or heavy metals, the situation is different. These stresses will select microorganisms carrying resistance genes, making the genes on MGEs more likely to spread (Sobecky & Coombs, 2009). These environmental factors do not act independently but jointly influence the flow rate of genes and the interaction patterns among different taxonomic groups, and ultimately will also be reflected in the stability of the community. 2.3 Role of HGT in microbial adaptation and functional gene dissemination In the soil, whether microorganisms can gain a firm foothold in a new environment often depends not only on their own capabilities but also on whether they have the opportunity to "pick up" suitable genes from other microorganisms. HGT precisely provides such a shortcut to push genes related to antibiotic tolerance, metabolic patterns and resilience around the community (Maheshwari et al., 2017). These genes sometimes do not offer much help to certain microbiota, but for others, they may be key to entering new niches or recovering from stress. Changes at the community level are not always unidirectional. In some cases, HGT can make the entire community more stable, but this effect is often influenced by environmental conditions or the characteristics of the genes themselves (Coyte et al., 2022b). Understanding how these genes flow can not only help explain the adaptability of soil systems, but is also closely related to practical applications such as improving soil health, promoting sustainable agriculture and environmental remediation. 3 Computational Methods for HGT Detection 3.1 Sequence-based approaches: comparative genomics and phylogenetic incongruence When analyzing HGT, many studies start with the sequence, but the approach is not complicated. It simply juxtaposes the evolutionary history of a certain gene with the phylogenetic relationship of the species it belongs to for comparison. If the two don't match, it's highly likely that this gene is not a "local product". The ideas of comparative genomics and phylogenetic inconsistencies basically revolve around this point. Tools like HGTphyloDetect swallow a large number of sequences in the process of reconstructing the gene tree, and then sort out possible donor-recipient relationships bit by bit, and even capture subtle transfers between closely related species (Yuan et al., 2023). However, such methods are not omnipotent. On the one hand, they require a large amount of computing power. As long as the reference database is slightly missing or biased, the judgment is prone to deviation, which is quite common in actual operation. 3.2 Composition-based techniques: k-mer profiles, GC skew, codon usage bias Another type of detection approach does not rely on phylogenetic information but focuses on the "textual style" of the gene sequence itself. Characteristics such as k-mer composition, GC content skew, and codon usage
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