Desta, G.M.; Birhanu, A.G. Single-Cell RNA Sequencing, Current Progresses and Future Perspectives. Preprints2024, 2024021281. https://doi.org/10.20944/preprints202402.1281.v1
APA Style
Desta, G.M., & Birhanu, A.G. (2024). Single-Cell RNA Sequencing, Current Progresses and Future Perspectives. Preprints. https://doi.org/10.20944/preprints202402.1281.v1
Chicago/Turabian Style
Desta, G.M. and Alemayehu Godana Birhanu. 2024 "Single-Cell RNA Sequencing, Current Progresses and Future Perspectives" Preprints. https://doi.org/10.20944/preprints202402.1281.v1
Abstract
During the last few years, advancement in the area of biochemistry, science of the material world, engineering and computer-aided testing has directed towards advancement of high-throughput tools for the sake of profiling information encoded in a gene. Single-cell RNA-sequencing (scRNA-seq) tools capable to examine the sequence data from each individual cells and it shows within population variety and permit exploring of cell conditions and transformation by extreme resolution, possibly give out cell sub-types or gene expression fluctuations that are shaded in mass sequencing processes, which shows population-averaged evaluations. Yet, the major disadvantage for this tool is the lack of success to pick out location related details of the RNA transcriptome, as this needs tissue detachment and cell isolation. Location based transcript determination is among the advancements in the area of medical biotechnology as this can find out the molecules like RNA dataset in their intact physical placement in tissue segment with spatial context at the scale of a single-cell, which is very advantageous as compare to single-cell sequencing techniques. These approaches give key observation in the areas of biomedical field sub-disciplines like neurology, embryology, carcinoma study, immune cell investigation and histological activities. Generally, this review mainly focused towards single-cell sequencing methods, technology development, its challenges observed, different expression data analysis mechanisms and their applications in different areas, such as in cancer research, microbes, central nervous system, sex organs and immune-biology, intensifying the essentiality of sequencing tools at single-cell level for the characterization of extremely dynamic individual cells.
Keywords
Single cell RNA sequencing; Transcriptome; high-throughput; spatial transcriptomics
Subject
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
