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Updated: May 15, 2025

Novel Sequence Discovery by Subtractive Genomics
Published on: January 25, 2019
Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens
Bhavya Mudgal1, Devvret Verma1, Divya Venogopal2
1Department of Biotechnology, Graphic Era Deemed to be University, Dehradun, Uttarakhand 248002, India.
None:
Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential therapeutic targets by differentiating essential genes in pathogens and non-pathogenic genes. Since, identification of therapeutic targets and understanding of their structure, function, and role in pathogenesis is important in development of drug design. Therefore, this review will provide a comprehensive look at the subtractive genomics technique which was applied to various pathogens, often highlighting the effectiveness of the methodology in drug target discovery and novel therapeutics development. Tools and software such as BLAST, Roary, and AutoDock Vina are widely utilized in this methodology for various aspects such as, genome comparison, essential gene identification, clustering, subcellular localization, pathway analysis, molecular docking etc. Diseases such as tuberculosis, botulism, staphylococcal infections, ventilator-associated pneumonia, secondary meningitis, gonorrhoea, septicaemia, etc., are among the infectious diseases targeted using subtractive genomics. Comparison of basic principles, tools, and advancements use these subtractive genomics studies, will provide insight into the adaptable nature of this technique and the diversity of pathogens, which have benefited with this methodology into providing successful results. The main focus is on the genome sequencing advancements, annotation and validation through in-silico techniques, to find effective drug targets while, decreasing the possibility of toxicity in the host. We have also discussed the possibility of taking a multi-omics approach and incorporating AI and machine learning to expand on the current data and finding effective therapeutics for helping globally on health challenges.
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