Cancer Genetics and Epigenetics 2024, Vol.12, No.3, 157-165 http://medscipublisher.com/index.php/cge 160 2.1.1 Next-Generation Sequencing (NGS) technology Next-Generation Sequencing (NGS) is a high-throughput sequencing technology that has been widely applied in biological and medical research (Wu et al., 2019). The principle of NGS involves fragmenting DNA or RNA molecules into small segments, then sequencing these fragments in parallel, and finally assembling them into complete genomic or transcriptomic information (Figure 2). Figure 2 principle of next generation sequencing (NGS) technology NGS technology boasts high throughput capabilities, enabling the simultaneous sequencing of a large number of DNA or RNA fragments. This allows it to generate vast amounts of data and quickly analyze entire genomes or transcriptomes. NGS technology employs parallel sequencing, which means sequencing multiple DNA or RNA fragments simultaneously. This increases sequencing speed, reduces costs, and makes sample processing more efficient. NGS can be used for various applications, including whole-genome sequencing, whole-exome sequencing, RNA sequencing, methylation sequencing, and ChIP sequencing. It is widely applied in genomics, transcriptomics, and epigenetics. NGS technology plays a crucial role in cancer research, genetics research, pathogen identification, and drug development. It is used to detect gene mutations, discover new genes, analyze expression profiles, and uncover disease mechanisms. NGS technology holds great potential in personalized medicine and precision medicine. It can be used to diagnose diseases, guide treatment choices, monitor therapeutic efficacy, and predict disease risk. The large volume of data generated by NGS requires complex data analysis methods. The development of bioinformatics tools and algorithms is essential for extracting useful information from raw sequencing data. 2.1.2 Single-cell sequencing Single-cell sequencing is a highly precise genomic technology used to analyze and sequence the genome, transcriptome, and epigenome of individual cells. Unlike traditional bulk sequencing methods, single-cell sequencing can reveal genetic and expression differences between individual cells and the cellular heterogeneity within a population. Single-cell sequencing provides high-resolution information at the cellular level, uncovering genetic and expression differences between cells, which helps in understanding cellular heterogeneity. This technology can help researchers discover new cell types or subtypes that might be hidden in traditional sequencing. By tracking gene expression changes in individual cells, single-cell sequencing can aid in studying cellular development and differentiation processes. It can decompose a complex cell population into distinct subgroups, identifying key genes and biological characteristics within each subgroup. Single-cell sequencing can be used to study the genetic and expression differences among different cell subpopulations within tumors, identify potential therapeutic targets, and understand tumor progression mechanisms. In immunology research, single-cell sequencing can reveal the diversity of immune cells, including T cells, B cells, macrophages, and their roles in infection and immune response. It can also be used in neuroscience to study different types of neurons in the brain and explore the mechanisms of neurological diseases.
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