Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling

被引:113
|
作者
Giraldez, Maria D. [1 ]
Spengler, Ryan M. [1 ]
Etheridge, Alton [2 ]
Godoy, Paula M. [3 ]
Barczak, Andrea J. [3 ]
Srinivasan, Srimeenakshi [4 ,5 ]
De Hoff, Peter L. [4 ,5 ]
Tanriverdi, Kahraman [6 ]
Courtright, Amanda [7 ]
Lu, Shulin [8 ]
Khoory, Joseph [8 ]
Rubio, Renee [9 ]
Baxter, David [10 ]
Driedonks, Tom A. P. [11 ]
Buermans, Henk P. J. [12 ]
Nolte-'t Hoen, Esther N. M. [11 ]
Jiang, Hui [13 ,14 ]
Wang, Kai [10 ]
Ghiran, Ionita [8 ]
Wang, Yaoyu E. [9 ]
Van Keuren-Jensen, Kendall [7 ]
Freedman, Jane E. [6 ]
Woodruff, Prescott G. [15 ,16 ]
Laurent, Louise C. [4 ,5 ]
Erle, David J. [3 ]
Galas, David J. [2 ]
Tewari, Muneesh [1 ,13 ,17 ,18 ]
机构
[1] Univ Michigan, Dept Internal Med, Div Hematol Oncol, Ann Arbor, MI 48109 USA
[2] Pacific Northwest Res Inst, Seattle, WA 98122 USA
[3] Univ Calif San Francisco, Dept Med, Lung Biol Ctr, San Francisco, CA USA
[4] Univ Calif San Diego, Dept Obstet Gynecol & Reprod Sci, La Jolla, CA 92093 USA
[5] Univ Calif San Diego, Sanford Consortium Regenerat Med, La Jolla, CA 92093 USA
[6] Univ Massachusetts, Sch Med, Dept Med, Div Cardiovasc Med, Worcester, MA USA
[7] Translat Genom Res Inst TGen, Neurogen, Phoenix, AZ USA
[8] Harvard Med Sch, Dept Med, Beth Israel Deaconess Med Ctr, Boston, MA USA
[9] Dana Farber Canc Inst, Ctr Canc Computat Biol, Boston, MA 02115 USA
[10] Inst Syst Biol, Seattle, WA USA
[11] Univ Utrecht, Dept Biochem & Cell Biol, Fac Vet Med, Utrecht, Netherlands
[12] Leiden Univ, Dept Human Genet, Leiden Genome Technol Ctr, Med Ctr, Leiden, Netherlands
[13] Univ Michigan, Ctr Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
[14] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
[15] Univ Calif San Francisco, Cardiovasc Res Inst, San Francisco, CA USA
[16] Univ Calif San Francisco, Dept Med, Div Pulm Crit Care Sleep & Allergy, San Francisco, CA USA
[17] Univ Michigan, Dept Biomed Engn, Ann Arbor, MI 48109 USA
[18] Univ Michigan, Biointerfaces Inst, Ann Arbor, MI 48109 USA
基金
欧洲研究理事会;
关键词
DIFFERENTIAL EXPRESSION ANALYSIS; GENE-EXPRESSION; MICRORNA; REPRODUCIBILITY;
D O I
10.1038/nbt.4183
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
RNA-seq is increasingly used for quantitative profiling of small RNAs (for example, microRNAs, piRNAs and snoRNAs) in diverse sample types, including isolated cells, tissues and cell-free biofluids. The accuracy and reproducibility of the currently used small RNA-seq library preparation methods have not been systematically tested. Here we report results obtained by a consortium of nine labs that independently sequenced reference, 'ground truth' samples of synthetic small RNAs and human plasma-derived RNA. We assessed three commercially available library preparation methods that use adapters of defined sequence and six methods using adapters with degenerate bases. Both protocol- and sequence-specific biases were identified, including biases that reduced the ability of small RNA-seq to accurately measure adenosine-to-inosine editing in microRNAs. We found that these biases were mitigated by library preparation methods that incorporate adapters with degenerate bases. MicroRNA relative quantification between samples using small RNA-seq was accurate and reproducible across laboratories and methods.
引用
收藏
页码:746 / +
页数:19
相关论文
共 50 条
  • [21] Comprehensive RNA-Seq profiling to evaluate lactating sheep mammary gland transcriptome
    Aroa Suárez-Vega
    Beatriz Gutiérrez-Gil
    Christophe Klopp
    Gwenola Tosser-Klopp
    Juan-José Arranz
    Scientific Data, 3
  • [22] Transcriptomic profiling of rat liver samples in a comprehensive study design by RNA-Seq
    Gong, Binsheng
    Wang, Charles
    Su, Zhenqiang
    Hong, Huixiao
    Thierry-Mieg, Jean
    Thierry-Mieg, Danielle
    Shi, Leming
    Auerbach, Scott S.
    Tong, Weida
    Xu, Joshua
    SCIENTIFIC DATA, 2014, 1
  • [23] Comprehensive RNA-Seq profiling to evaluate lactating sheep mammary gland transcriptome
    Suarez-Vega, Aroa
    Gutierrez-Gil, Beatriz
    Klopp, Christophe
    Tosser-Klopp, Gwenola
    Arranz, Juan-Jose
    SCIENTIFIC DATA, 2016, 3
  • [24] A real-world multi-center RNA-seq benchmarking study using the Quartet and MAQC reference materials
    Wang, Duo
    Liu, Yaqing
    Zhang, Yuanfeng
    Chen, Qingwang
    Han, Yanxi
    Hou, Wanwan
    Liu, Cong
    Yu, Ying
    Li, Ziyang
    Li, Ziqiang
    Zhao, Jiaxin
    Shi, Leming
    Zheng, Yuanting
    Li, Jinming
    Zhang, Rui
    NATURE COMMUNICATIONS, 2024, 15 (01)
  • [26] RNA-Seq profiling of circular RNAs in human small cell lung cancer
    Zhang, Chenxi
    Zhang, Bin
    Yuan, Baiyin
    Chen, Caiping
    Zhou, Ying
    Zhang, Yu
    Sheng, Zhihong
    Sun, Nan
    Wu, Xiaoyuan
    EPIGENOMICS, 2020, 12 (08) : 685 - 700
  • [27] RNA-seq and miRNA-seq profiling analyses reveal molecular mechanisms underlying the progression of polycystic ovary syndrome
    Bai, Xue
    Zheng, Chunyang
    Yu, Yuexin
    Zhang, Jinyan
    Cao, Shiyue
    Hou, Cong
    Wang, Sihan
    GENE REPORTS, 2024, 35
  • [28] MICRORNA PROFILING USING SMALL RNA-SEQ IN PAEDIATRIC LOW GRADE GLIOMAS
    Jeyapalan, Jennie N.
    Jones, Tania A.
    Tatevossian, Ruth G.
    Qaddoumi, Ibrahim
    Ellison, DavidW.
    Sheer, Denise
    NEURO-ONCOLOGY, 2014, 16
  • [29] Comprehensive RNA-seq profiling to evaluate the rabbit mammary gland transcriptome after mastitis
    Wu, Yingjie
    Zhao, Lihua
    Qin, Yinghe
    JOURNAL OF ANIMAL SCIENCE, 2023, 101
  • [30] Comprehensive RNA-Seq profiling of the lung transcriptome of Bashbay sheep in response to experimentalMycoplasma ovipneumoniaeinfection
    Du, Zhihui
    Sun, Yanming
    Wang, Jixue
    Liu, Haiyan
    Yang, Yi
    Zhao, Ning
    PLOS ONE, 2020, 15 (07):