Spatial single-cell mapping of transcriptional differences across genetic backgrounds in mouse brains

Genetic variation can alter organ structure and function. Comparative statistical analysis of organs across genetic backgrounds requires spatial, single-cell, atlas-scale data in replicates. Here we introduce atlas-scale transcriptome localization using aggregate signatures (ATLAS), a scalable tissue mapping method that learns transcriptional signatures from single-cell RNA sequencing data, encodes them in situ with tens of thousands of oligonucleotide probes and decodes them to infer cell types and imputed transcriptomes. We validated ATLAS against direct MERFISH measurements of marker genes and through quantitative comparisons to four other technologies. We profiled 40 million cells across more than 400 coronal sections from central brains of five male and five female C57BL/6J mice and five male BTBR T⁺tf/J mice, an idiopathic autism model. Our analysis revealed more than 40 significant differences in cell-type distributions and identified 16 regional composition changes across male-female and B6-BTBR comparisons. ATLAS thus enables systematic comparative studies, facilitating organ-level structure-function analysis of disease models.