仿形(计算机编程)
转录组
计算生物学
多样性(政治)
细胞生物学
计算机科学
生物
政治学
遗传学
基因
基因表达
法学
操作系统
作者
Hiroyuki Okada,Yuta Terui,Masahide Seki,Asuka Terashima,Shoichiro Tani,Daisuke Motooka,Sanshiro Kanazawa,Masahiro Hosonuma,Junya Miyahara,Kenta Makabe,Yasunori Omata,Shoko Onodera,Fumiko Yano,Hiroshi Kajiya,Francesca Gori,Taku Saito,Koji Okabe,Yutaka Suzuki,Roland Baron,Ung‐il Chung,Sakae Tanaka,Hironori Hojo
标识
DOI:10.1101/2022.09.05.506360
摘要
SUMMARY Single-cell RNA-seq (scRNA-seq) has clarified cellular heterogeneity within cell populations. However, scRNA-seq and spatial transcriptomics cannot capture the dynamic transcriptomic changes inside living cells. To decode subcellular gene expression, we developed intra-single cell sequencing (iSCseq), a novel approach that combines confocal imaging, repeatedly picking up cellular components inside living cells, and next-generation sequencing (intra single-cell RNA-seq; iSCseq). iSCseq illustrated the subcellular heterogeneity of gene expression. iSCseq revealed not only multiple differentiation stages embedded in the same cell, but also physical cytoskeletal connections, physiological activity of mitochondria, and intracellular calcium, as confirmed by transcriptomic evidence. Inclusive iSCseq with in vivo scRNA-seq datasets identified new osteoclast subsets in physiological and pathological bones. Network analysis with centrality provided insights into the connection between subcellular components, and clearly divided differentiation and fusion processes in multinucleation. The iSCseq approach has the potential to enhance cell biology at subcellular resolution and identify new therapeutic targets. Graphical abstract In brief intra-single cell sequencing (iSCseq) enhances single-cell technology by combining live cell imaging, subcellular sampling from living cells and sequencing, offering deeper insights into cell functions and pathology at subcellular resolution through inclusive analysis with scRNA-seq and advanced centrality-focused network analysis. Highlights intra-single cell sequencing (iSCseq) clarifies subcellular heterogeneity iSCseq connects morphological and physiological features with transcriptome Inclusive iSCseq unveils osteoclast subsets in physiological and pathological bones Linkage at subcellular resolution reveals key players in characteristic fusion
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