Review

. 2022 Oct 18;3(6):100342.

doi: 10.1016/j.xinn.2022.100342. eCollection 2022 Nov 8.

Single-cell technologies: From research to application

Lu Wen¹, Guoqiang Li¹, Tao Huang², Wei Geng³, Hao Pei⁴, Jialiang Yang⁵, Miao Zhu⁶, Pengfei Zhang⁷, Rui Hou⁵, Geng Tian⁵, Wentao Su⁸, Jian Chen⁹, Dake Zhang¹⁰, Pingan Zhu¹¹, Wei Zhang¹², Xiuxin Zhang¹³, Ning Zhang¹⁴, Yunlong Zhao^{15

16}, Xin Cao¹⁷, Guangdun Peng⁶, Xianwen Ren¹, Nan Jiang^{18

19}, Caihuan Tian¹³, Zi-Jiang Chen²⁰

Affiliations

¹ Biomedical Pioneering Innovation Centre (BIOPIC), Peking University, Beijing 100871, China.
² Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
³ School of Chemical Engineering and Technology, Sun Yat-Sen University, Zhuhai 519082, China.
⁴ Mozhuo Biotech (Zhejiang) Co., Ltd., Tongxiang, Jiaxing 314500, China.
⁵ Geneis (Beijing) Co., Ltd., Beijing 100102, China.
⁶ Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.
⁷ Department of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
⁸ School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.
⁹ State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
¹⁰ Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing 100083, China.
¹¹ Department of Mechanical Engineering, City University of Hong Kong, Hong Kong 999077, China.
¹² Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
¹³ Center of Peony, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Flower Crops (North China), Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs, Beijing 100081, China.
¹⁴ Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
¹⁵ Advanced Technology Institute, University of Surrey, Guildford, Surrey, GU2 7XH, UK.
¹⁶ National Physical Laboratory, Teddington, Middlesex TW11 0LW, UK.
¹⁷ Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
¹⁸ West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, China.
¹⁹ Jinfeng Laboratory, Chongqing 401329, China.
²⁰ Center for Reproductive Medicine, Shandong University, Jinan, Shandong, 250012, China.

PMID: 36353677
PMCID: PMC9637996
DOI: 10.1016/j.xinn.2022.100342

Review

Single-cell technologies: From research to application

Lu Wen et al. Innovation (Camb). 2022.

. 2022 Oct 18;3(6):100342.

doi: 10.1016/j.xinn.2022.100342. eCollection 2022 Nov 8.

Authors

Affiliations

¹ Biomedical Pioneering Innovation Centre (BIOPIC), Peking University, Beijing 100871, China.
² Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
³ School of Chemical Engineering and Technology, Sun Yat-Sen University, Zhuhai 519082, China.
⁴ Mozhuo Biotech (Zhejiang) Co., Ltd., Tongxiang, Jiaxing 314500, China.
⁵ Geneis (Beijing) Co., Ltd., Beijing 100102, China.
⁶ Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.
⁷ Department of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
⁸ School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China.
⁹ State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
¹⁰ Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing 100083, China.
¹¹ Department of Mechanical Engineering, City University of Hong Kong, Hong Kong 999077, China.
¹² Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
¹³ Center of Peony, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Flower Crops (North China), Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs, Beijing 100081, China.
¹⁴ Department of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
¹⁵ Advanced Technology Institute, University of Surrey, Guildford, Surrey, GU2 7XH, UK.
¹⁶ National Physical Laboratory, Teddington, Middlesex TW11 0LW, UK.
¹⁷ Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
¹⁸ West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, China.
¹⁹ Jinfeng Laboratory, Chongqing 401329, China.
²⁰ Center for Reproductive Medicine, Shandong University, Jinan, Shandong, 250012, China.

PMID: 36353677
PMCID: PMC9637996
DOI: 10.1016/j.xinn.2022.100342

Abstract

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

**Figure 1**
The milestones of single-cell sequencing technologies

**Figure 2**
Illustration of single-cell detection methods

**Figure 3**
Procedure of droplet-based scRNA-seq

**Figure 4**
The bioinformatics analysis for scRNA-seq data

**Figure 5**
The application of single-cell sequencing in oncology

**Figure 6**
The application of single-cell sequencing in assisted reproduction

**Figure 7**
The application of single-cell sequencing in developmental biology

**Figure 8**
The applications of single-cell sequencing in plant biology

**Figure 9**
The sequencing-based and imaging-based spatial transcriptomics

**Figure 10**
The single-cell multi-omics studies

See this image and copyright information in PMC

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Single-cell technologies: From research to application

Affiliations

Single-cell technologies: From research to application

Authors

Affiliations

Abstract

Conflict of interest statement

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