Fig. 1: scIVNL-seq detects single-cell new RNA in vivo.

A Overview of scIVNL-seq. S⁴U was injected into mice via tail vein injection. BM cells were collected and re-suspended. Single-cell suspensions were loaded onto microfluidic device, followed by cell lysis and mRNA capture. S⁴U integrated in new RNA was converted into cytidine analogs and was further recognized as cytosine by reverse transcriptase. cDNAs were amplified and libraries were sequenced. New RNA was identified by T-to-C substitutions. The schematic diagrams were created with Adobe Photoshop (Version 22.0.0) (B) New RNA (red) imaging of femur sections, co-stained with CD45 (green), CD31 (cyan) antibodies and DAPI (blue). Scale bar, 100 μm. C UMAP showing cell type clusters (left), UMI counts of new RNA and NTRs (right) in bone marrow CD45⁺ immune cells. The uniform manifold approximation and projection (UMAP) method was used for dimension reduction. Unique molecular identifier (UMI) counts per cell are shown as ln(count+1). Ratios of new RNA to total RNA are shown as NTRs. HSPC, hematopoietic stem and progenitor cell; Mono, monocyte; Mφ, macrophage; Neu, neutrophil; Baso, basophil; NK, natural killer cell; DC, dendritic cell; Pre B, Pre-B cell; B, B cell; T, T cell. D Violin plot of NTR for each BM cell type. E Signature gene expression of new RNA (left) and total RNA (right) for each cell type. Genes in the heatmap were the same between new RNA and total RNA. Expressions were log-normalized. F Total RNA and new RNA expression (log-normalized) of Ptprc, Ccr2, Camp and Rpl13. G Scatter plot of transcription rate (α, normalized RNA counts per cells/h) and RNA half-life (t_1/2, h) of genes expressed in BM cells. H UMAP projection of BM cell types with new RNA. Cells with new RNA data were clustered by unsupervised classification. Cell types identified with total RNA data were mapped back on UMAP projection. Source data are provided as a Source Data file.