Single-cell differential splicing analysis reveals high heterogeneity of liver tumor-infiltrating T cells

被引:17
|
作者
Liu, Shang [1 ,2 ,3 ]
Zhou, Biaofeng [1 ,2 ,3 ]
Wu, Liang [1 ,2 ,3 ]
Sun, Yan [1 ,2 ,3 ]
Chen, Jie [1 ,2 ]
Liu, Shiping [2 ,3 ]
机构
[1] Univ Chinese Acad Sci UCAS, BGI Educ Ctr, Shenzhen 518083, Peoples R China
[2] BGI Shenzhen, Shenzhen 518083, Peoples R China
[3] China Natl GeneBank, Shenzhen Key Lab Single Cell Om, Shenzhen 518120, Peoples R China
关键词
EXPRESSION; QUANTIFICATION; LANDSCAPE; DESIGN; CANCER; CTLA-4; GENES;
D O I
10.1038/s41598-021-84693-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent advances in single-cell RNA sequencing (scRNA-seq) have improved our understanding of the association between tumor-infiltrating lymphocyte (TILs) heterogeneity and cancer initiation and progression. However, studies investigating alternative splicing (AS) as an important regulatory factor of heterogeneity remain limited. Here, we developed a new computational tool, DESJ-detection, which accurately detects differentially expressed splicing junctions (DESJs) between cell groups at the single-cell level. We analyzed 5063 T cells of hepatocellular carcinoma (HCC) and identified 1176 DESJs across 11 T cell subtypes. Interestingly, DESJs were enriched in UTRs, and have putative effects on heterogeneity. Cell subtypes with a similar function closely clustered together at the AS level. Meanwhile, we identified a novel cell state, pre-activation with the isoform markers ARHGAP15-205. In summary, we present a comprehensive investigation of alternative splicing differences, which provided novel insights into T cell heterogeneity and can be applied to other full-length scRNA-seq datasets.
引用
收藏
页数:12
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