Patho-DBiT is a novel method for spatial whole transcriptome sequencing in archival formalin-fixed paraffin-embedded (FFPE) tissues, enabling the simultaneous profiling of various RNA species such as mRNA, microRNA, tRNA, splicing isoforms, and single-nucleotide RNA variants. This method combines in situ polyadenylation and computational innovations to overcome the challenges of FFPE samples, including RNA fragmentation and degradation. Patho-DBiT allows for high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for up to 5 years, revealing region-specific splicing isoforms and detailed RNA dynamics. It also captures genome-wide single-nucleotide RNA variants to distinguish malignant subclones from non-malignant cells in human lymphomas. The method has been applied to mouse embryo and lymphoma sections, demonstrating its ability to map gene expression, RNA processing, and microRNA regulatory networks. Additionally, Patho-DBiT can dissects spatiotemporal cellular dynamics in lymphomagenesis at the single-cell level, providing valuable insights into tumor clonal architecture and progression. The integration of Patho-DBiT with high-resolution histology further enhances the resolution of tissue architecture, allowing for the identification of vasculature, lymphatics, and plasma cells. Patho-DBiT also enables the detection of somatic large-scale chromosomal copy number variations and the analysis of microRNA regulatory networks, contributing to a comprehensive understanding of RNA biology in FFPE tissues.Patho-DBiT is a novel method for spatial whole transcriptome sequencing in archival formalin-fixed paraffin-embedded (FFPE) tissues, enabling the simultaneous profiling of various RNA species such as mRNA, microRNA, tRNA, splicing isoforms, and single-nucleotide RNA variants. This method combines in situ polyadenylation and computational innovations to overcome the challenges of FFPE samples, including RNA fragmentation and degradation. Patho-DBiT allows for high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for up to 5 years, revealing region-specific splicing isoforms and detailed RNA dynamics. It also captures genome-wide single-nucleotide RNA variants to distinguish malignant subclones from non-malignant cells in human lymphomas. The method has been applied to mouse embryo and lymphoma sections, demonstrating its ability to map gene expression, RNA processing, and microRNA regulatory networks. Additionally, Patho-DBiT can dissects spatiotemporal cellular dynamics in lymphomagenesis at the single-cell level, providing valuable insights into tumor clonal architecture and progression. The integration of Patho-DBiT with high-resolution histology further enhances the resolution of tissue architecture, allowing for the identification of vasculature, lymphatics, and plasma cells. Patho-DBiT also enables the detection of somatic large-scale chromosomal copy number variations and the analysis of microRNA regulatory networks, contributing to a comprehensive understanding of RNA biology in FFPE tissues.