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Introduction: Since the introduction of Next-Generation Sequencing (NGS) in the early 2000s, this technology has emerged as a transformative advancement in the life sciences, significantly propelling genomic, transcriptomic, epigenomic, and other related research fields. The core principles of NGS technology encompass library preparation, sequencing, and the analysis of the resulting data. By enabling the parallel sequencing of millions of DNA fragments with high accuracy, low cost, and rapid turnaround, NGS has effectively replaced older methods like Sanger sequencing. It has revolutionized our understanding of genetic complexities, genome structures, and genetic diversity through the swift and precise sequencing of entire genomes and target regions. Key applications of NGS in the life sciences include the identification and study of genes related to quantitative and qualitative traits, genetic diversity studies, population genetics, the diagnosis of genetic diseases, epidemiology, microbiome analysis, forensic science, phylogenetics, systems biology, genetic engineering, genome editing, and plant and animal breeding. However, the effective use of NGS data necessitates the development of robust computational infrastructure and advanced algorithms, as well as the expansion of researchers' knowledge regarding the bioinformatic applications and challenges associated with NGS data analysis and interpretation. Materials and methods: The present article is a review paper, conducted through content analysis by searching for keywords related to Next-Generation Sequencing (NGS), types of NGS sequencing, NGS data analysis, and the applications of NGS in relevant articles found in online databases such as PubMed, Web of Science, Google Scholar, and Scopus. Results: This study aims to provide a comprehensive guide for the efficient and optimal analysis of NGS data by thoroughly reviewing first-, second-, and third-generation sequencing methods, examining NGS data analysis pipelines, and exploring the broad applications of NGS in various fields, including cereal research. The first section reviews first-generation sequencing (Maxam-Gilbert and Sanger), second-generation sequencing (Illumina, ABI/SOLID, Roche/454 pyrosequencing, Ion Torrent), and third-generation sequencing (Heliscope, SMRT, and Oxford Nanopore). The second section introduces various NGS sequencing methods, such as Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), Bulk RNA-Seq, and others, and examines their analysis pathways. The subsequent discussion elaborates on the application of NGS in diverse areas, including the identification of structural genomic variations (SVs), the study of epigenetic changes, microbial population analysis, and agriculture (with an emphasis on cereal breeding). Finally, the advantages and challenges of NGS are discussed. Conclusion: As a revolutionary technology in genomics, Next-Generation Sequencing has profoundly impacted life sciences research. The reduction in sequencing costs, coupled with increased accuracy and the development of new methods, has positioned NGS as a critical tool for a deeper understanding of genetics and the development of personalized therapeutic strategies. With ongoing advancements in this field and the integration of NGS with artificial intelligence, the future of NGS in enhancing the precision of genetic data analysis and improving therapeutic processes appears promising. [ABSTRACT FROM AUTHOR]