Single-cell RNA sequencing technologies and applications: A brief overview

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  • Dragomirka Jovic
  • Liang, Xue
  • Hua Zeng
  • Lin Lin
  • Fengping Xu
  • Yonglun Luo

Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/organisms. Since its first discovery in 2009, studies based on scRNA-seq provide massive information across different fields making exciting new discoveries in better understanding the composition and interaction of cells within humans, model animals and plants. In this review, we provide a concise overview about the scRNA-seq technology, experimental and computational procedures for transforming the biological and molecular processes into computational and statistical data. We also provide an explanation of the key technological steps in implementing the technology. We highlight a few examples on how scRNA-seq can provide unique information for better understanding health and diseases. One important application of the scRNA-seq technology is to build a better and high-resolution catalogue of cells in all living organism, commonly known as atlas, which is key resource to better understand and provide a solution in treating diseases. While great promises have been demonstrated with the technology in all areas, we further highlight a few remaining challenges to be overcome and its great potentials in transforming current protocols in disease diagnosis and treatment.

Original languageEnglish
Article numbere694
JournalClinical and Translational Medicine
Volume12
Issue number3
Number of pages20
ISSN2001-1326
DOIs
Publication statusPublished - 2022

Bibliographical note

© 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.

    Research areas

  • Animals, Gene Expression Profiling/methods, Sequence Analysis, RNA/methods, Single-Cell Analysis/methods, Technology, Whole Exome Sequencing

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