Spatial Total RNA Sequencing of Formalin-Fixed Paraffin Embedded Tissues by spRandom-seq
Liao, Y.; Chen, J.; Zhang, S.; Chen, Y.-s.; Zhu, B.; Chen, H.; Zhu, Y.; Xu, Z.; Yin, Y.; Xiong, X.; Liu, N.; Guo, H.; Wang, Y.
Show abstract
Current oligo(dT) primers-based spatial transcriptomic methods are limited to fresh or fresh-frozen samples due to the low efficiency of oligo(dT) primers in capturing RNAs in degraded or microbial samples. Here, we have developed a random primer-based spatial total RNA sequencing (spRandom-seq) technology for simultaneously capturing whole host and microbial RNAs in formalin-fixed paraffin-embedded (FFPE) tissues. spRandom-seq eliminated 3 or 5 gene-body biases and outperformed oligo(dT)-based 10X Visium with an 8-fold higher capturing rate for lncRNA and other non-polyadenylated RNA biotypes, including miRNA, snRNA and miscRNA. In the clinical FFPE sections of breast cancer, we revealed the inherent heterogeneity within the tumor region. We also simultaneously captured host and microbial RNAs in Klebsiella pneumoniae-infected sections. Totally, spRandom-seq provided a versatile tool for both clinical pathology and infection biology with established spatial platforms, ensuring ease of operation and large-scale applications.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- ST-FFPE-mIF: Integrating Spatial Transcriptomics and Multiplex Immunofluorescence in Formalin-Fixed Paraffin-Embedded Tissues Using Stereo-seq 96%
- Deciphering gene regulatory programs in mouse embryonic skin through single-cell multiomics analysis 94%
- REPIC: A database for exploring N6-methyladenosine methylome 93%
Similar papers in this journal
Similar papers in this journal
- inDrops-2: a flexible, versatile and cost-efficient droplet microfluidics approach for high-throughput scRNA-seq of fresh and preserved clinical samples 95%
- Hybridization-based In Situ Sequencing (HybISS): spatial transcriptomic detection in human and mouse brain tissue 93%
- CellDART: Cell type inference by domain adaptation of single-cell and spatial transcriptomic data 92%