Chang Yao-Yin, Lai Liang-Chuan, Tsai Mong-Hsun, Chuang Eric Y
Department of Electrical Engineering, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No 1 Sec 4 Roosevelt Road, Taipei, Taiwan.
Bioinformatics and Biostatistics Core, NTU Center of Genomic Medicine, Taipei, Taiwan.
Methods Mol Biol. 2018;1699:99-111. doi: 10.1007/978-1-4939-7435-1_8.
Deep sequencing is an advanced technology in genomic biology to detect the precise order of nucleotides in a strand of DNA/RNA molecule. The analysis of deep sequencing data also requires sophisticated knowledge in both computational software and bioinformatics. In this chapter, the procedures of deep sequencing analysis of microRNA (miRNA) transcriptome in triple-negative breast cancer and adjacent normal tissue are described in detail. As miRNAs are critical regulators of gene expression and many of them were previously reported to be associated with the malignant progression of human cancer, the analytical method that accurately identifies deregulated miRNAs in a specific type of cancer is thus important for the understanding of its tumor behavior. We obtained raw sequence reads of miRNA expression from 24 triple-negative breast cancers and 14 adjacent normal tissues using deep sequencing technology in this work. Expression data of miRNA reads were normalized with the quantile-quantile scaling method and were analyzed statistically. A miRNA expression signature composed of 25 differentially expressed miRNAs showed to be an effective classifier between triple-negative breast cancers and adjacent normal tissues in a hierarchical clustering analysis.
深度测序是基因组生物学中的一项先进技术，用于检测DNA/RNA分子链中核苷酸的精确顺序。深度测序数据分析还需要在计算软件和生物信息学方面具备专业知识。在本章中，将详细描述三阴性乳腺癌及癌旁正常组织中微小RNA（miRNA）转录组的深度测序分析过程。由于miRNA是基因表达的关键调节因子，且先前有许多报道称它们与人类癌症的恶性进展相关，因此准确识别特定类型癌症中失调miRNA的分析方法对于理解其肿瘤行为至关重要。在本研究中，我们使用深度测序技术获得了24例三阴性乳腺癌及14例癌旁正常组织的miRNA表达原始序列读数。miRNA读数的表达数据采用分位数-分位数缩放法进行标准化，并进行统计学分析。在层次聚类分析中，由25个差异表达miRNA组成的miRNA表达特征显示为三阴性乳腺癌与癌旁正常组织之间的有效分类器。
