Image-seq: spatially-resolved single cell sequencing guided by in situ and in vivo imaging

We collected bone marrow samples from mice using the Image-seq technology that we developed for spatial transcriptomics. We isolated samples from the anatomically distinct D, M and R cavities that were recently identified by in vivo imaging (Christodoulou et al, Nature, 2020, 578, 278-283). We compared these samples in aggregated form (i.e. all Image-seq to all WT control) to whole calvarial bone marrow samples from wild-type (WT) mice and mice injected with a combination of tetracycline and alizarin red (used also to identify different cavity types). The transcriptional composition of all samples was assessed using single-cell RNA-seq (scRNA-seq). We collected bone marrow samples from mice using the Image-seq technology that we developed for spatial transcriptomics. We isolated samples from regions with proliferating, non-proliferating and intermediate AML cells (see manuscript for details), and sorted single GFP+ AML cells into individual wells filled with lysis buffer by flow cytometry. We analyzed the transcriptional composition of each individual cell using single-cell RNA-seq. Bone marrow were disaggregated and profiled by 10X Genomics Single cell 3 gene expression V2. Smartseq v4 protocol were used (https://www.takarabio.com) to profile rare (<0.01% leukemic burden) acute myeloid leukemia (AML) cells and BM stromal cells.