Recent advances in spatially resolved transcriptomics: challenges and opportunities

Jongwon Lee, Minsu Yoo, Jungmin Choi

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at singlemolecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 μm resolution. Unfortunately, neither imaging-based technology nor capturebased method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research.

Original languageEnglish
Pages (from-to)113-124
Number of pages12
JournalBMB reports
Issue number3
Publication statusPublished - 2022

Bibliographical note

Funding Information:
The authors are grateful to Junho Song for critical reading of the manuscript. This research was supported by the National Research Foundation of Korea (NRF) grants funded by the South Korean government (2020R1F1A1076705)

Publisher Copyright:
© 2022. by the The Korean Society for Biochemistry and Molecular Biology


  • Integrative computational algorithm
  • Multimodal data analysis
  • Single-cell rna sequencing
  • Spatially resolved transcriptomics

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology


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