Current sequencing-based spatial transcriptomic methods have been widely used to resolve gene expression; however, these methods are limited to fresh or fresh-frozen samples due to the low efficiency of oligo(dT) primers in capturing RNA transcripts in degraded samples. Here, we have developed a random primer-based spatial total RNA sequencing (spRandom-seq) technology for capturing full-length total RNAs in partially degraded (low RIN values) formalin-fixed paraffin-embedded (FFPE) tissues. Our spRandom-seq approach exhibited no discernible biases at the 3’- or 5’-ends within gene bodies and could be integrated with the commercially available 10X Visium and other well-established sequencing-based spatial transcriptomic platforms. Our spRandom-seq approach outperformed oligo(dT)-based 10X Visium with an 8-fold higher capturing rate for long-non-coding RNA (lncRNA) and other non-polyadenylated RNA biotypes, including miRNA, snRNA, and miscRNA. The unsupervised clustering with solely non