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基于中值的JS散度可变剪接差异分析研究

刘文斌 王兵 方刚 石晓龙 许鹏

刘文斌, 王兵, 方刚, 石晓龙, 许鹏. 基于中值的JS散度可变剪接差异分析研究[J]. 电子与信息学报, 2020, 42(6): 1392-1400. doi: 10.11999/JEIT190941
引用本文: 刘文斌, 王兵, 方刚, 石晓龙, 许鹏. 基于中值的JS散度可变剪接差异分析研究[J]. 电子与信息学报, 2020, 42(6): 1392-1400. doi: 10.11999/JEIT190941
Wenbin LIU, Bing WANG, Gang FANG, Xiaolong SHI, Peng XU. Study on the Differential Analysis of Alternative Splicing Based on the Median Value Jensen-Shannon Divergence[J]. Journal of Electronics & Information Technology, 2020, 42(6): 1392-1400. doi: 10.11999/JEIT190941
Citation: Wenbin LIU, Bing WANG, Gang FANG, Xiaolong SHI, Peng XU. Study on the Differential Analysis of Alternative Splicing Based on the Median Value Jensen-Shannon Divergence[J]. Journal of Electronics & Information Technology, 2020, 42(6): 1392-1400. doi: 10.11999/JEIT190941

基于中值的JS散度可变剪接差异分析研究

doi: 10.11999/JEIT190941
基金项目: 国家重点研发计划(2019YFA0706402),国家自然科学基金(61572367, 61573017, 61972107, 61972109)
详细信息
    作者简介:

    刘文斌:男,1969年生,教授,研究方向为生物信息学

    王兵:男,1993年生,硕士生,研究方向为生物信息学

    方刚:男,1969年生,教授,研究方向为生物信息学

    石晓龙:男,1975年生,教授,研究方向为生物信息学

    许鹏:男,1986年生,博士后,研究方向为生物信息学

    通讯作者:

    刘文斌 wbliu6910@126.com

  • 中图分类号: TP391

Study on the Differential Analysis of Alternative Splicing Based on the Median Value Jensen-Shannon Divergence

Funds: The National Key R&D Program of China (2019YFA0706402), The National Natural Science Foundation of China (61572367, 61573017, 61972107, 61972109)
  • 摘要: 可变剪接是一种广泛存在于生物体中造成蛋白质多样性的重要机制,它对细胞的增殖、分化、发育、凋亡等一系列重要的生物过程具有重要精细调控的作用。近年来,人们发现多种复杂疾病的产生往往伴随着剪接异构体的紊乱表达。为了研究剪接异构体在整体分布上的差异,该文提出一种基于中值的JS散度可变剪接(AS)差异分析方法。结果表明,该文的方法能够发现大量在剪接异构体整体分布上具有显著差异的基因。这些基因不仅富集在一些癌症密切相关的通路,而且也富集在一些基于可变剪接调控的信号通路、细胞分裂过程和蛋白质功能等通路。此外,与基因层次的差异分析相比,可变剪接显著差异的基因在生存分析方面也具有更好的性能。总之,该文提出基于中值的JS散度可变剪接差异分析方法,将为进一步揭示可变剪接在癌症中的机制奠定基础。
  • 图  1  4种方法差异基因的韦恩图

    图  2  乳腺癌驱动基因的PPI网络

    图  3  癌症分类结果比较

    图  4  差异基因生存分析曲线

    表  1  癌症数据集统计信息

    癌症癌症样本正常样本基因个数异构体个数
    BRCA11001121017833481
    LIHC37350887126234
    UCEC11724976530953
    下载: 导出CSV

    表  2  KEGG通路分析

    癌症通路(Gen Model)通路(AS Model)
    Focal adhesionCell cycle
    PI3K-Akt signaling pathwayp53 signaling pathway
    Tight junctionPathways in cancer
    Regulation of lipolysis in adipocytesOocyte meiosis
    BRCAPathways in cancerViral carcinogenesis
    Rap1 signaling pathwayAdherens junction
    cAMP signaling pathwayPurine metabolism
    ABC transportersPI3K-Akt signaling pathway
    Cell adhesion molecules (CAMs)Hippo signaling pathway
    Leukocyte transendothelial migrationMetabolic pathways
    Metabolic pathwaysMetabolic pathways
    Fatty acid degradationPhagosome
    Protein processing in endoplasmic reticulumFc gamma R-mediated phagocytosis
    ProteasomeLeishmaniasis
    LIHCmTOR signaling pathwayHomologous recombination
    AMPK signaling pathwaySphingolipid metabolism
    Valine, leucine and isoleucine degradationECM-receptor interaction
    SpliceosomeCell cycle
    Ubiquitin mediated proteolysisFanconi anemia pathway
    Insulin signaling pathwayRibosome biogenesis in eukaryotes
    Vascular smooth muscle contractionOsteoclast differentiation
    cGMP-PKG signaling pathwayCell cycle
    Focal adhesionAdherens junction
    MAPK signaling pathwayAxon guidance
    UCECProteoglycans in cancerPhagosome
    Calcium signaling pathwayRheumatoid arthritis
    Platelet activationAMPK signaling pathway
    Adherens junctionPPAR signaling pathway
    Oxytocin signaling pathwayECM-receptor interaction
    Ras signaling pathwayPlatelet activation
    下载: 导出CSV
  • WANG E T, SANDBERG R, LUO Shujun, et al. Alternative isoform regulation in human tissue transcriptomes[J]. Nature, 2008, 456(7221): 470–476. doi: 10.1038/nature07509
    ZHOU Yujie, ZHU Guiqi, ZHANG Qingwei, et al. Survival-associated alternative messenger RNA splicing signatures in pancreatic ductal adenocarcinoma: A study based on RNA-sequencing data[J]. DNA and Cell Biology, 2019, 38(11): 1207–1222. doi: 10.1089/dna.2019.4862
    XIE Zucheng, WU Huayu, DANG Yiwu, et al. Role of alternative splicing signatures in the prognosis of glioblastoma[J]. Cancer Medicine, 2019, 8(18): 7623–7636. doi: 10.1002/cam4.2666
    LI Mingxue, WANG Dun, HE Jianhua, et al. Bcl-XL: A multifunctional anti-apoptotic protein[J]. Pharmacological Research, 2020, 151: 104547. doi: 10.1016/j.phrs.2019.104547
    KOLE R, KRAINER A R, and ALTMAN S. RNA therapeutics: Beyond RNA interference and antisense oligonucleotides[J]. Nature Reviews Drug Discovery, 2012, 11(2): 125–140. doi: 10.1038/nrd3625
    SONG Jukun, LIU Yongda, SU Jiaming, et al. Systematic analysis of alternative splicing signature unveils prognostic predictor for kidney renal clear cell carcinoma[J]. Journal of Cellular Physiology, 2019, 234(12): 22753–22764. doi: 10.1002/jcp.28840
    DOU Tonghai, XU Jiaxi, GAO Yuan, et al. Evolution of peroxisome proliferator-activated receptor gamma alternative splicing[J]. Frontiers in Bioscience (Elite Edition) , 2010, 2: 1334–1343. doi: 10.2741/e193
    LI Ji, CHOI P S, CHAFFER C L, et al. An alternative splicing switch in FLNB promotes the mesenchymal cell state in human breast cancer[J]. eLife, 2018, 7: e37184. doi: 10.7554/eLife.37184
    SHEN Shihao, PARK J W, LU Zhixiang, et al. rMATS: Robust and flexible detection of differential alternative splicing from replicate RNA-Seq data[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(51): E5593–E5601. doi: 10.1073/pnas.1419161111
    欧书华, 刘学军, 张礼. 基于KL散度的RNA-Seq数据差异异构体比例检测[J]. 计算机工程与科学, 2017, 39(1): 158–164. doi: 10.3969/j.issn.1007-130X.2017.01.022

    OU Shuhua, LIU Xuejun, and ZHANG Li. Differential isoform ratio detection based on KL divergence for RNA-Seq data[J]. Computer Engineering &Science, 2017, 39(1): 158–164. doi: 10.3969/j.issn.1007-130X.2017.01.022
    LIU Jingwei, LI Hao, SHEN Shixuan, et al. Alternative splicing events implicated in carcinogenesis and prognosis of colorectal cancer[J]. Journal of Cancer, 2018, 9(10): 1754–1764. doi: 10.7150/jca.24569
    ZONG Zhen, LI Hui, YI Chenghao, et al. Genome-wide profiling of prognostic alternative splicing signature in colorectal cancer[J]. Frontiers in Oncology, 2018, 8: 537. doi: 10.3389/fonc.2018.00537
    ZHANG Zijun, PAN Zhicheng, YING Yi, et al. Deep-learning augmented RNA-seq analysis of transcript splicing[J]. Nature Methods, 2019, 16(4): 307–310. doi: 10.1038/s41592-019-0351-9
    WHITFIELD M L, GEORGE L K, GRANT G D, et al. Common markers of proliferation[J]. Nature Reviews Cancer, 2006, 6(2): 99–106. doi: 10.1038/nrc1802
    INOUE K and FRY E A. Aberrant splicing of the DMP1-ARF-MDM2-p53 pathway in cancer[J]. International Journal of Cancer, 2016, 139(1): 33–41. doi: 10.1002/ijc.30003
    MUNDING E M, SHIUE L, KATZMAN S, et al. Competition between pre-mRNAs for the splicing machinery drives global regulation of splicing[J]. Molecular Cell, 2013, 51(3): 338–348. doi: 10.1016/j.molcel.2013.06.012
    CHU Xiufeng, ZHANG Ting, WANG Jie, et al. Alternative splicing variants of human Fbx4 disturb cyclin D1 proteolysis in human cancer[J]. Biochemical and Biophysical Research Communications, 2014, 447(1): 158–164. doi: 10.1016/j.bbrc.2014.03.129
    BAILEY M H, TOKHEIM C, PORTA-PARDO E, et al. Comprehensive characterization of cancer driver genes and mutations[J]. Cell, 2018, 173(2): 371–385. e18. doi: 10.1016/j.cell.2018.02.060
    曾勇, 舒欢, 胡江平, 等. 基于BP神经网络的自适应伪最近邻分类[J]. 电子与信息学报, 2016, 38(11): 2774–2779. doi: 10.11999/JEIT160133

    ZENG Yong, SHU Huan, HU Jiangping, et al. Adaptive pseudo nearest neighbor classification based on BP neural network[J]. Journal of Electronics &Information Technology, 2016, 38(11): 2774–2779. doi: 10.11999/JEIT160133
    陈素根, 吴小俊. 基于特征值分解的中心支持向量机算法[J]. 电子与信息学报, 2016, 38(3): 557–564. doi: 10.11999/JEIT150693

    CHEN Sugen and WU Xiaojun. Eigenvalue proximal support vector machine algorithm based on eigenvalue decoposition[J]. Journal of Electronics &Information Technology, 2016, 38(3): 557–564. doi: 10.11999/JEIT150693
    ZHANG Yangjun, YAN Libin, ZENG Jin, et al. Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers[J]. Oncogene, 2019, 38(40): 6678–6695. doi: 10.1038/s41388-019-0910-7
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出版历程
  • 收稿日期:  2019-11-22
  • 修回日期:  2020-04-24
  • 网络出版日期:  2020-05-13
  • 刊出日期:  2020-06-22

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