No abstract

The combination of single-cell RNA sequencing and microdissection techniques that preserves positional information has become a major tool for spatial transcriptome analyses. However, high costs and time requirements, especially for experiments at the single cell scale, make it challenging for this approach to meet the demand for increased throughput. Therefore, we proposed combinational DNA barcode (CDB)-seq as a medium-throughput, multiplexed approach combining Smart-3SEQ and CDB magnetic microbeads for transcriptome analyses of microdissected tissue samples. We conducted a comprehensive comparison of conditions for CDB microbead preparation and related factors and then applied CDB-seq to RNA extracts, fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) mouse brain tissue samples. CDB-seq transcriptomic profiles of tens of microdissected samples could be obtained in a simple, cost-effective way, providing a promising method for future spatial transcriptomics.

Cells are basic building blocks of life with vast heterogeneity. Nowadays, the rapid development of single‐cell multiomics (scMulti‐Omics) has facilitated comprehensive understanding of gene regulatory networks, cellular characteristics, and temporal dynamics. However, simultaneous analysis of transcriptome and proteome at single‐cell level still faces huge challenges due to their differences in molecular modalities. Recent technological advances in single‐cell manipulations, barcoding, and ultrasensitive instrument recently offer unprecedented opportunities for the co‐profiling of genes and proteins. In this review, multiple types of single‐cell isolation, lysis, and molecular separation technologies are first introduced. Second, various approaches for co‐measurement of transcriptome and proteome in single‐cells are summarized, with their advantages, limitations, and capacity for targeted or unbiased deep analysis. Then we highlight the cutting‐edge spatial multiomics methodologies that operate at the single‐cell or subcellular resolution level, providing a comprehensive understanding of cell function and heterogeneity within the tissue spatial environment. The emerging biomedical applications of multiomics are also discussed. Finally, the challenges and prospects of this field are proposed.