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.
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