Targeted Transcriptome Sequencing Enables Exponential Scaling of Combinatorial Barcoding in Leukemia Samples.

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