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Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Chen Haide, Fang Xiunan, Shao Jikai, Zhang Qi, Xu Liwei, Chen Jiaye, Mei Yuqing, Jiang Mengmeng, Wang Yuting, Li Zhouyang, Chen Zihang, Chen Yang, Yu Chengxuan, Ma Lifeng, Zhang Peijing, Zhang Tianyu, Liao Yuan, Lv Yuexiao, Wang Xueyi, Yang Lei, Fu Yuting, Chen Daobao, Jiang Liming, Yan Feng, Lu Wei, Chen Gao, Shen Huahao, Wang Jingjing, Wang Changchun, Liang Tingbo, Han Xiaoping, Wang Yongcheng, Guo Guoji

Аннотация

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты