Bt Research 2024, Vol.15, No.3, 141-153 http://microbescipublisher.com/index.php/bt 145 are commonly used for sequence alignment, model testing, and tree construction, providing robust platforms for phylogenetic inference. 5.2 Interpretation of phylogenetic trees Interpreting phylogenetic trees involves understanding the evolutionary relationships and genetic distances between different Bt strains. A phylogenetic tree visually represents these relationships, with branches indicating divergence points from common ancestors. Nodes on the tree represent hypothetical common ancestors, while the length of branches corresponds to genetic distances or evolutionary time. For example, the phylogenetic analysis of Bt strains by Wang et al. (2018) using MLST revealed two major clusters containing 21 sub-groups, highlighting the genetic diversity and evolutionary lineage within the Bt species. Similarly, Lechuga et al. (2020) constructed a phylogenetic tree based on whole-genome sequences, which placed Bt HER1410 within a clade comprising members from the B. thuringiensis serovar thuringiensis and other serovars, illustrating the intermingled taxonomy within the B. cereus group. By comparing phylogenetic trees constructed using different markers, researchers can validate the consistency of evolutionary relationships and identify potential discrepancies. For instance, the use of both 16S rRNA and housekeeping genes helps ensure a more accurate depiction of phylogenetic relationships (Shikov et al., 2021). Phylogenetic trees also provide insights into horizontal gene transfer events, gene loss, and the evolutionary pressures shaping the genetic diversity of Bt strains. 5.3 Case studies of phylogenetic trees Case studies of phylogenetic tree construction in Bt research provide practical examples of how these methodologies are applied. One notable study by Rabha et al. (2018) utilized MLST to analyze Bt isolates from Assam soil, identifying 14 unique sequence types (STs) and demonstrating the phylogenetic diversity of these isolates. The phylogenetic tree constructed in this study revealed three major lineages, with most isolates belonging to Bt, and a few clustering with B. cereus, highlighting the genetic relationships and diversity within the Bt strains. Another case study by Shikov et al. (2021) used proteomic and genomic data to assess the phylogenetic relationships of Bt strains, finding that the distribution of several genomic virulence determinants did not align with traditional serotyping classification, suggesting the need for phylogenomics approaches for more accurate classification (Figure 1). Wang and Ash (2015) employed the FFP method to construct a whole-genome phylogeny of Bacillus species, confirming the placement of Bt within a single clade and demonstrating the effectiveness of genome-wide analyses in resolving phylogenetic relationships. These case studies illustrate the practical applications and importance of phylogenetic tree construction in understanding the genetic and evolutionary dynamics of Bt strains. 6 Genetic Relationships and Divergence 6.1 Identification of genetic relationships Identifying genetic relationships among Bacillus thuringiensis (Bt) strains is crucial for understanding their evolutionary dynamics and potential applications. The genetic relationships are typically determined using phylogenetic analysis based on various genetic markers, such as housekeeping genes, 16S rRNA, and toxin genes. For example, Multi-Locus Sequence Typing (MLST) has been widely used to assess the genetic diversity and relationships among Bt strains. In a study by Wang et al. (2018), MLST analysis of 233 Bt strains revealed significant genetic relationships, identifying two major clusters containing 21 sub-groups. This method allows for the classification of Bt strains based on their genetic sequences, providing a detailed picture of their evolutionary lineage.
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