Bt Research 2025, Vol.16, No.4, 136-146 http://microbescipublisher.com/index.php/bt 136 Feature Review Open Access Bioinformatics Tools for Bt Genome Data Analysis Shusheng Liu 1, Chunyang Zhan2 1 Tropical Microbial Resources Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China 2 Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China Corresponding author: chunyang.zhan@hitar.org Bt Research, 2025, Vol.16, No.4 doi: 10.5376/bt.2025.16.0017 Received: 15 May, 2025 Accepted: 20 Jun., 2025 Published: 08 Jul., 2025 Copyright © 2025 Liu and Zhan, 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. Preferred citation for this article: Liu S.S., and Zhan C.Y., 2025, Engineering of Bt plasmids to enhance their insecticidal activity, Bt Research, 16(4): 136-146 (doi: 10.5376/bt.2025.16.0017) Abstract As an important microbial insecticide, Bacillus thuringiensis is of great significance to understanding the Bt insecticidal mechanism and improving the performance of strains. This study reviews the commonly used bioinformatics tools and methods in Bt genome data analysis in recent years, including genome assembly and annotation, transcriptome expression analysis, mining of virulence genes and their regulatory elements, comparative genome and evolutionary analysis, protein structure function prediction, and multiomics data integration and visualization platform. Through the application of these tools, researchers can more comprehensively analyze the genomic characteristics of Bt, reveal the expression and regulation mechanism of functional genes such as Cry toxin, compare the differences between Bt and other Bacillus, and explore its evolutionary laws, predict the structure and receptor interaction of toxin proteins, and then guide the design and application of new insecticidal strains. This study looks forward to the trend of bioinformatics integrating multiomics data and artificial intelligence analysis in Bt research, aiming to provide systematic tool guides and references for researchers engaged in Bt genome research and application. Keywords Bacillus thuringiensis; Genome; Bioinformatics tools; Toxin genes; Comparative genomics 1 Introduction Bacillus thuringiensis is a Gram-positive Bacillus widely used in agricultural and sanitary pest control, and is also a recognized safe and efficient microbial insecticide. During the spore formation process, Bt can produce consorubic crystal toxins with specific insecticidal activity, which has an efficient lethal effect on hundreds of insect larvae such as Lepidoptera, Diptera, Coleoptera, and at the same time is safe for humans and animals (Reyaz et al., 2019; Peralta et al., 2021). Genetically modified insect-resistant crops developed based on the Bt insecticidal gene have been widely planted and have played an important role in increasing crop yields and reducing the use of chemical pesticides. Bioinformatics plays an indispensable role in Bt genome research. Modern high-throughput sequencing technology allows us to obtain a large number of Bt strains' whole genome sequences and transcriptome, proteome and other omic data, but these data are huge and complex, and require processing and analysis with the help of bioinformatics tools. Through genome assembly and annotation, functional genes in the Bt genome, including insecticidal crystal protein genes and other secondary metabolite synthesis gene clusters (Yılmaz et al., 2024), can be comprehensively identified, thereby providing a basis for screening and modifying highly efficient strains. This study systematically sorts out the commonly used bioinformatics tools and their application progress in Bt genomic data analysis in the past five years, from the acquisition of original genomic data, efficient assembly and annotation, to the comparative assembly and difference analysis of transcriptomic data, to the mining of toxin gene families and regulatory elements, comparative genomics and evolutionary analysis methods, and toxin protein structure and function prediction, and finally discusses platform tools for integrating multiomics data and visualization of results. Through these contents, we strive to reflect the latest application progress and future trends of bioinformatics in Bt genome analysis, and provide a reference basis for further Bt functional gene discovery and strain molecular improvement.
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