Comparison of RNA-Sequencing Methods for Degraded RNA

被引:1
|
作者
Ura, Hiroki [1 ,2 ]
Niida, Yo [1 ,2 ]
机构
[1] Kanazawa Med Univ Hosp, Ctr Clin Genom, 1-1 Daigaku, Uchinada, Ishikawa 9200293, Japan
[2] Kanazawa Med Univ, Med Res Inst, Dept Adv Med, Div Genom Med, 1-1 Daigaku, Uchinada, Kahoku 9200293, Japan
基金
日本学术振兴会;
关键词
transcriptome; RNA-Seq; degraded RNA; gene expression; TRANSCRIPTOME; SEQ;
D O I
10.3390/ijms25116143
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] A comparison between ribo-minus RNA-sequencing and polyA-selected RNA-sequencing
    Cui, Peng
    Lin, Qiang
    Ding, Feng
    Xin, Chengqi
    Gong, Wei
    Zhang, Lingfang
    Geng, Jianing
    Zhang, Bing
    Yu, Xiaomin
    Yang, Jin
    Hu, Songnian
    Yu, Jun
    GENOMICS, 2010, 96 (05) : 259 - 265
  • [2] RNA-sequencing in toxicogenomics
    Kleinjans, J.
    TOXICOLOGY LETTERS, 2015, 238 (02) : S35 - S36
  • [3] Comparison of Computational Methods for Imputing Single-Cell RNA-Sequencing Data
    Zhang, Lihua
    Zhang, Shihua
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2020, 17 (02) : 376 - 389
  • [4] A comparison of survival analysis methods for cancer gene expression RNA-Sequencing data
    Raman, Pichai
    Zimmerman, Samuel
    Rathi, Komal S.
    de Torrente, Laurence
    Sarmady, Mahdi
    Wu, Chao
    Leipzig, Jeremy
    Taylor, Deanne M.
    Tozeren, Aydin
    Mar, Jessica C.
    CANCER GENETICS, 2019, 235 : 1 - 12
  • [5] A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments
    Wynn, Elizabeth A.
    Vestal, Brian E.
    Fingerlin, Tasha E.
    Moore, Camille M.
    BMC MEDICAL RESEARCH METHODOLOGY, 2022, 22 (01)
  • [6] A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments
    Elizabeth A. Wynn
    Brian E. Vestal
    Tasha E. Fingerlin
    Camille M. Moore
    BMC Medical Research Methodology, 22
  • [7] HCC: RNA-Sequencing in Cirrhosis
    Wang, Haoyu
    Shi, Wenjie
    Lu, Jing
    Liu, Yuan
    Zhou, Wei
    Yu, Zekun
    Qin, Shengying
    Fan, Junwei
    BIOMOLECULES, 2023, 13 (01)
  • [8] Quantitative assessment of single-cell RNA-sequencing methods
    Angela R Wu
    Norma F Neff
    Tomer Kalisky
    Piero Dalerba
    Barbara Treutlein
    Michael E Rothenberg
    Francis M Mburu
    Gary L Mantalas
    Sopheak Sim
    Michael F Clarke
    Stephen R Quake
    Nature Methods, 2014, 11 : 41 - 46
  • [9] Comprehensive comparative analysis of 5'-end RNA-sequencing methods
    Adiconis, Xian
    Haber, Adam L.
    Simmons, Sean K.
    Moonshine, Ami Levy
    Ji, Zhe
    Busby, Michele A.
    Shi, Xi
    Jacques, Justin
    Lancaster, Madeline A.
    Pan, Jen Q.
    Regev, Aviv
    Levin, Joshua Z.
    NATURE METHODS, 2018, 15 (07) : 505 - +
  • [10] Comprehensive comparative analysis of 5′-end RNA-sequencing methods
    Xian Adiconis
    Adam L. Haber
    Sean K. Simmons
    Ami Levy Moonshine
    Zhe Ji
    Michele A. Busby
    Xi Shi
    Justin Jacques
    Madeline A. Lancaster
    Jen Q. Pan
    Aviv Regev
    Joshua Z. Levin
    Nature Methods, 2018, 15 : 505 - 511