Single-cell RNA Sequencing: Current Progresses and Future Perspectives

Abstract

During the last few years, advancements in the areas of biochemistry, the science of the material world, engineering, and computer-aided testing have been directed toward the development of high-throughput tools for profiling information encoded in genes. Single-cell RNA sequencing (scRNA-seq) tools are capable of examining sequence data from individual cells, revealing population variety and allowing exploration of cell conditions and transformations with extreme resolution. These tools can potentially identify cell subtypes or gene expression fluctuations that are obscured in mass sequencing processes, which provide population-averaged evaluations. However, a major disadvantage of this tool is the inability to pinpoint location-related details of the RNA transcriptome, as this requires tissue detachment and cell isolation. Location-based transcript determination represents an advancement in medical biotechnology, as it can identify molecules, such as RNA datasets, in their intact physical placement within tissue segments with spatial context at the single-cell scale. This capability is highly advantageous compared to traditional single-cell sequencing techniques. These approaches offer valuable insights into various sub-disciplines of the biomedical field, including neurology, embryology, carcinoma studies, immune cell investigation, and histological activities. This review primarily focuses on single-cell sequencing methods, technology development, observed challenges, different expression data analysis mechanisms, and their applications in various areas, such as cancer research, microbes, the central nervous system, reproductive organs, and immunobiology. It underscores the importance of sequencing tools at the single-cell level for characterizing highly dynamic individual cells.