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生物信息学框架用于单细胞长读测序:解锁异型级分辨率

Saloni Bhatia^1,2, Matt A Field^2,3,4, Lionel Hebbard^2,5,6

¹Computational Biomedicine Lab, College of Science and Engineering, James Cook University, 1 James Cook Drive, Townsville, QLD 4811, Australia.

Briefings in bioinformatics

|December 11, 2025

概括

单细胞长读测序 (SCLR-seq) 在单细胞水平上提供全长异形分辨率. 这种强有力的方法增强了对疾病中的替代拼接的理解,并有助于发现新的诊断和治疗点.

科学领域:

基因组学就是基因组学.
分子生物学分子生物学
生物信息学是一种生物信息学.

背景情况:

替代拼接 (AS) 对于基因表达调节至关重要,并与癌症等疾病有关.
大量RNA测序在捕捉细胞异质性和重建全长异构形式方面存在局限性.
单细胞RNA测序 (scRNA-seq) 提供单细胞分辨率,但受限于用于异形重建的短读长度.

研究的目的:

审查单细胞长读序列 (SCLR-seq) 在研究替代拼接中的实用性.
突出生物信息学工具的进步,用于SCLR-seq数据分析.
讨论SCLR-seq在疾病研究和目标发现中的潜力.

主要方法:

单细胞分辨率与长读RNA测序 (lrRNA-seq) 技术的整合.
开发和应用生物信息管道用于SCLR-seq数据分析.
在单细胞分辨率下对异形多样性,拼接变体和融合转录的表征.

主要成果:

通过提供全长的异形信息,SCLR-seq克服了短读序列的局限性.
能够准确量化异形多样性和识别新型拼接变体.
促进研究人类疾病中细胞特异异性异常拼接事件.

结论:

SCLR-seq是一种用于理解同位体调节和异常拼接的变革性技术.
它提供了前所未有的异形级别分辨率和细胞类型特异性.
具有显著的潜力,在人类疾病中发现新的诊断和治疗点.

关键词:

替代性拼接是一种替代性的拼接.不同的异构形式表达式.异形量化量化量化方法单单细胞长读序列测序

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