文献类型: 外文期刊
作者: Zhenzhen Wang;Kehan Tao;Jiaojiao Ji;Changbin Sun;Wei Xu
作者机构:
关键词: (1-1-1)Gene expression;Next-generation sequencing;Quantification;RNA sequencing;Transcriptome
期刊名称: BMC Genomics
ISSN: 1471-2164
年卷期: 2024 年 25 卷 1 期
页码:
收录情况: SCIE(2024版)
摘要: Background: RNA sequencing (RNA-seq) is widely used for gene expression profiling and quantification. Quantitative RNA sequencing usually requires cell counting and spike-in, which is not always applicable to many samples. Here, we present a novel quantitative RNA sequencing method independent of spike-ins or cell counting, named siqRNA-seq, which can be used to quantitatively profile gene expression by utilizing gDNA as an internal control. Single-stranded library preparation used in siqRNA-seq profiles gDNA and cDNA with equal efficiency. Results: To quantify mRNA expression levels, siqRNA-seq constructs libraries for total nucleic acid to establish a model for expression quantification. Compared to Relative Quantification RNA-seq, siqRNA-seq is technically reliable and reproducible for expression profiling but also can sequence reads from gDNA which can be used as an internal reference for accurate expression quantification. Applying siqRNA-seq to investigate the effects of actinomycin D on gene expression in HEK293T cells, we show the advantages of siqRNA-seq in accurately identifying differentially expressed genes between samples with distinct global mRNA levels. Furthermore, we analyzed factors influencing the downward trend of gene expression regulated by ActD using siqRNA-seq and found that mRNA with m6A modification exhibited a faster decay rate compared to mRNA without m6A modification. Additionally, applying this technique to the quantitative analysis of seven tumor cell lines revealed a high degree of diversity in total mRNA expression among tumor cell lines. Conclusions: Collectively, siqRNA-seq is a spike-in independent quantitative RNA sequencing method, which creatively uses gDNA as an internal reference to absolutely quantify gene expression. We consider that siqRNA-seq provides a convenient and versatile method to quantitatively profile the mRNA landscape in various samples.
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