A characteristic feature of the liver is the presence of numerous polyploid hepatocytes. However, the functional distinctions among diploid, tetraploid, and octoploid hepatocytes remain poorly understood. In this study, we employed the spatially resolved single-cell sequencing technology, Stereo-cell, to dissect the transcriptomic and functional heterogeneity across hepatocyte ploidy subtypes. We detail the development of Stereo-cell Imaging-based ploidy Identification (SCIPI), a technical pipeline that integrates bright-field cell contour recognition, DAPI-based nuclear area and number quantification, and UMI-barcoded single-cell transcriptomics. This approach enables precise identification of six core hepatocyte subtypes: mononucleated diploid (2n×1), mononucleated tetraploid (4n×1), binucleated tetraploid (2n×2), mononucleated octoploid (8n×1), binucleated octoploid (4n×2), and binucleated hexadecaploid (8n×2) hepatocytes. Single-cell transcriptomic analysis based on ploidy annotation revealed that gene expression levels scale positively with increasing ploidy and nuclear number. Metabolic pathway-associated genes were significantly upregulated in polyploid cells, suggesting that cellular polyploidization enhances the metabolic activity of hepatocytes. Furthermore, this SCIPI strategy is broadly applicable to the study of various polyploid tissues, offering a novel and versatile framework for innovative ploidy-resolved research across diverse biological researches.
Yang et al. (Sat,) studied this question.