Targeted transcriptome sequencing enables exponential scaling of combinatorial barcoding in leukemia samples.

Abstract Single-cell RNA-sequencing (scRNA-seq) has rapidly spread across multiple research fields, leading to new discoveries. Many applications of scRNA-seq are focused on cell type identification, gene regulatory networks, or biomarker discovery which require the interrogation specific sets well-characterized genes. In these cases, sequencing entire transcriptome may be adding unnecessary project costs. To increase throughput and minimize costs, development a targeted enrichment method is required. Here, we extend our whole (WT) split-pool combinatorial barcoding technology enrich subset genes in 16 libraries representing hundreds thousands human bone marrow mononuclear cells (BMMCs) from three acute myeloid leukemia (AML) one lymphocytic (ALL) donors. We used 1,000 immune panel canonical markers pathways. Our increased percent reads target as low 7% 75% libraries. Furthermore, despite nearly ten-fold reduction between unenriched enriched libraries, resulting clustering yielded high concordance identities preserved leukemia-specific signatures such FLT3, MKI67, CD19. Overall, demonstrate modular strategy preserves biological structure allows for deep characterization health disease. envision approach will enable researchers simultaneously reduce costs while drastically scaling up number samples experiments.