We evaluated the ability of Glycan-seq in a comparative analysis of the following bulk samples: human-induced pluripotent stem cells (hiPSCs) vs. human dermal fibroblasts (hFibs), Chinese hamster ovary cells vs. glycosylation-defective Chinese hamster lectins. analyzed by scGlycan-seq (left panel), flow cytometry (middle panel), and principal component analysis (PCA)(right panel).Development of a nondestructive system to analyze disease-associated glycomesHiroaki TatenoFigure 1. Single cell glycan and RNA sequencing (scGR-seq) (A) Principle of the conversion of the glycan information into gene information by DNA-barcoded (B) Schematic experimental flow of scGR-seq.(C) hiPSCs after 0- (red), 4- (green), 11-day differentiation (blue) into neural progenitor cells were (D) Dimensional reduction and clustering. UMAP visualization based on only the scRNA-seq data (left panel) andonly the scGlycan-seq (middle panel), both scRNA-seq and scGlycan-seq (scGR-seq, right panel) data of hiPSCs (n = 53, red) and NPCs (n = 43, green). Figures are reprinted from Minoshima et al., 20211).recovered, amplified by PCR, and analyzed by next-generation sequencer to count the DNA barcodes2). We referred to this method as Glycan-seq. 56
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