Computational Molecular Biology 2025, Vol.15, No.6, 299-306 http://bioscipublisher.com/index.php/cmb 304 a reasonable range, it is particularly important to understand how genes flow among microorganisms. Mastering these mechanisms can not only help formulate more stable soil management measures, but also enable people to utilize microorganisms more effectively to enhance the stress resistance of crops and improve soil fertility. It can be said that integrating the understanding of HGT into agricultural practice is a crucial step towards a more resilient agricultural ecosystem. 7 Challenges and Future Prospects 7.1 Limitations in computational sensitivity and specificity for HGT detection When conducting computational tests for HGT, the most common problem researchers encounter is often not how to set up the process, but that it is always difficult to balance sensitivity and specificity. Especially when it occurs among species that are closely related, the differences in sequence or phylogenetic aspects are so small that they are almost impossible to catch. The signals given by algorithms are often ambiguous, which may either miss true transfers or mistake common variations for exogenous genes. Although there are some improvement measures now, such as using heuristic judgments based on collinearity information or incorporating gene length and kinship into adaptive criteria, when it comes to an environment like soil where microorganisms are extremely complex and communities change rapidly, specificity is still not easy to guarantee. It is precisely for this reason that in order to more accurately identify various types of HGT events, in the future, we may still have to rely on stronger and more detailed computational models. 7.2 Integration of multi-omics data to improve accuracy and interpretation To make the detection of HGT more reliable, an increasing number of studies have begun to consider data from different omics together. When metagenomic, transcriptomic, proteomic and even metabolomic information is combined, transfer events that were originally difficult to explain by sequence alone can often find clearer ecological significance (De Sousa et al., 2023). Some new frameworks, such as models built on knowledge graphs, can also incorporate the complex relationships among genes, movable components and environmental variables into the analysis, making the prediction effect stronger. Such integration not only helps to identify the transmission path of resistance genes, but also can find other functional transfers related to soil health, and the explanatory level is much broader than that of the single-omics approach. 7.3 Need for standardization and curated benchmark datasets in HGT research In the entire field of HGT research, a long-standing difficulty is the lack of recognized and reliable benchmark datasets. Without clear reference standards, it is difficult for different analytical tools to be truly compared from the same starting point. Even when the same experiment is repeated, consistent conclusions may not be reached. Therefore, reference datasets that can cover multiple types of microbial communities and involve different types of gene transfer scenarios are particularly important. They can not only be used to verify methods but also contribute to the improvement of subsequent tools. Moreover, if there is an open, easy-to-operate toolbox that combines phylogenetic inference with high-throughput computing, the threshold for entering this field will also be much lower. Only by completing these fundamental tasks can we gain a deeper understanding of the role of HGT in soil microbial communities and its long-term significance in agricultural and environmental sustainability. 8 Conclusion When studying horizontal gene transfer in soil, computational analysis has almost become an unavoidable step. A process like MetaCHIP is to infer which genes might "come from elsewhere" by leveraging phylogenetic relationships and best-matching information without a reference genome. This method can not only capture recent gene exchanges but also reveal some earlier traces, thereby providing a clearer understanding of the role of HGT in resistance, metabolism and environmental adaptation. However, the reality is often not as smooth as the flowchart. Incomplete metagenomic assembly and overly similar strains often cause interference to the analysis, and this is basically inevitable in actual operation. The significance of HGT detection is not limited to "identifying transfer events" itself; it is more like a key to understanding how soil microbial communities maintain diversity and cope with stress. The spread of antibiotic resistance or metabolic capacity is often explained through these gene transfer pathways, and these functions are
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