Next-Generation Sequencing (NGS) Technologies: Transformative Impact on Genomics and Personalized Medicine
Uday Kiran Bathini
Pharmacology and Toxicology, Wright State University, Dayton, United States.
Vaishnavi Burra
Drug Design and Biomedical Science, Edinburgh Napier University, Edinburgh, United Kingdom.
Lahari Vuddanti
Healthcare Informatics, Sacred Heart University, Connecticut, USA.
Seetharam Gude
*
Research and Development, Aurobindo Pharma Limited, Hyderabad, India.
*Author to whom correspondence should be addressed.
Abstract
Next-generation sequencing (NGS) has become a cornerstone technology in modern genomics, fundamentally changing how genetic information is generated, analyzed, and applied. This review explores the expanding role of NGS across both research and clinical settings, emphasizing its transformative impact on precision medicine while also addressing existing technical and analytical challenges. An extensive review of contemporary literature was undertaken to evaluate recent progress in sequencing platforms, library preparation strategies, data processing workflows, and downstream analytical methods. Particular attention is given to the application of NGS in the study of rare genetic diseases, cancer genomics, infectious disease surveillance, microbiome analysis, population genetics, and functional genomics. By enabling the parallel sequencing of millions of DNA and RNA fragments, NGS provides unparalleled resolution into genomic architecture, sequence variation, gene expression dynamics, and epigenetic regulation. These capabilities have significantly advanced diagnostic accuracy, facilitated the development of targeted and personalized therapeutic strategies, and improved disease risk assessment. Emerging innovations, including long-read sequencing technologies, single-cell sequencing approaches, and integrative epigenomic profiling, are further enhancing the analytical power and clinical relevance of NGS. Despite these advancements, several limitations continue to hinder the full potential of NGS, such as challenges related to sequencing accuracy, data interpretation, cost constraints, and the scalability of bioinformatics infrastructures required to manage large and complex datasets. Addressing these issues through improvements in sequencing chemistry, computational algorithms, and cost-efficiency will be critical for broader clinical adoption. Overall, NGS continues to bridge the gap between genomic research and clinical implementation, and ongoing technological and analytical innovations are expected to expand its accessibility and impact across global healthcare and biomedical research.
Keywords: Next-generation sequencing, genomics, personalized medicine, computational tools