Article’s

The integration of bioinformatics in plant genomics has accelerated the identification of genes responsible for agronomically important traits. Clitoria ternatea (butterfly pea) is an economically valuable leguminous plant known for medicinal, ornamental, and nutraceutical properties, while Glycine max (soybean) serves as a well-studied model crop with extensive genomic resources. Comparative genomics and bioinformatics tools enable the identification of homologous genes between these species, facilitating the discovery of genes associated with stress tolerance, yield, and secondary metabolite production. Tools such as sequence alignment programs, genome annotation platforms, and functional genomics databases play a crucial role in this process. This paper discusses key bioinformatics tools, databases, and computational approaches used for identifying agro-economically important genes in C. ternatea using G. max as a reference model. The rapid development of genomic technologies and computational biology has significantly advanced the identification of agriculturally important genes in plants. Bioinformatics plays a crucial role in analyzing large-scale genomic datasets and predicting gene functions through comparative analysis and sequence annotation. Clitoria ternatea, commonly known as butterfly pea, is an economically important leguminous plant with medicinal, ornamental, and nutritional value. However, genomic information for this species has historically been limited. Recently, the availability of transcriptome shotgun assembly (TSA) and whole genome shotgun (WGS) sequence datasets for Clitoria ternatea in public databases has created new opportunities for gene discovery and functional analysis. Comparative genomics using well-characterized model crops such as Glycine max (soybean) provides an effective strategy for identifying genes associated with important agronomic traits. Soybean possesses a well-annotated genome and extensive genetic databases, making it suitable for identifying orthologous genes in related legumes. Bioinformatics tools such as sequence alignment algorithms, gene prediction software, genome annotation platforms, and functional analysis databases are widely used to identify candidate genes responsible for traits such as stress tolerance, nitrogen fixation, growth regulation, and secondary metabolite biosynthesis. This study highlights the role of computational tools and publicly available genomic resources in identifying agro-economically important genes in Clitoria ternatea through comparative analysis with soybean. The integration of bioinformatics techniques with plant genomics can accelerate crop improvement programs, enhance understanding of plant metabolic pathways, and support sustainable agricultural development.