Most mammalian cells are diploid, but polyploidy occurs in specific organs to enable specialized physiological functions, notably in hepatocytes, myocytes and mammary epithelial cells. However, elucidating these polyploid subtypes and profiling their distinct transcriptomes has long been constrained by technical limitations. To overcome this challenge, we used Stereo-cell, a spatially resolved single-cell sequencing method utilizing high-density DNA nanoball (DNB)-patterned arrays to allow for simultaneous transcriptome profiling and ploidy determination within the same cell, overcoming fundamental limitations of conventional approaches. Here, we detail a comprehensive method for the Stereo-cell imaging-based ploidy identification (SCIPI) pipeline. Our multimodal classification framework combines bright-field cell contour delineation, DAPI-guided nuclear area, and UMI-barcoded transcriptional profiling to precisely resolve four key hepatocyte subtypes: mononucleated diploid, binucleated tetraploid, mononucleated tetraploid, and binucleated octoploid, and their differential gene expression pattern. This SCIPI strategy is broadly applicable to polyploidy tissues, unlocking unprecedented ploidy-resolved analysis across diverse biological scenarios.
杨咏青(Yang Yongqing) (Thu,) studied this question.