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

By D. Jovic, Xue Liang, Hua Zeng, Lin Lin, Fengping Xu, Yonglun Luo. Clinical and Translational Medicine, 2022

1,038 citations recorded by the source corpus.

Abstract 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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4c2cdc09708307e75396530bb76625a0a3e88a32

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In Molecular Biology

1. Wanying Wu
2. Zhang Zhang
3. Lina Ma

Citations in the corpus

• Large Scale Foundation Model on Single-cell Transcriptomics (2023, neutral): “Single-cell RNA sequencing (scRNA-seq) data, also known as single-cell transcriptomics, offer high-throughput observations into cellular systems 2 , providing massive archives of transcriptomic sentences of all types of cells for developing foundation models.”
• Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024 (2023, background): “Moreover, single-cell sequencing technologies have emerged as powerful tools to study cellular heterogeneity ( 5 ), developmental processes ( 6 ), disease mechanisms ( 7 ), and complex biological systems ( 8 ) with unprecedented resolution ( 9 ).”