Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis

被引:52
|
作者
Benesova, Sarka [1 ,2 ]
Kubista, Mikael [1 ,3 ]
Valihrach, Lukas [1 ]
机构
[1] Inst Biotechnol, CAS, Gene Express Lab, BIOCEV, Vestec 25250, Czech Republic
[2] Univ Chem & Technol, Fac Chem Technol, Lab Informat & Chem, Prague 16628, Czech Republic
[3] TATAA Biocenter, S-41103 Gothenburg, AB, Sweden
关键词
small RNA-seq; miRNA; diagnostics; MICRORNA EXPRESSION; GENE-EXPRESSION; ISOMIRS; BIASES; SEQ; TECHNOLOGIES; SIGNATURES; KNOWLEDGE; ACCURACY; GENOMICS;
D O I
10.3390/diagnostics11060964
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol's performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research.
引用
收藏
页数:19
相关论文
共 50 条
  • [21] Reassessment of miRNA variant (isomiRs) composition by small RNA sequencing
    Gomez-Martin, Cristina
    Aparicio-Puerta, Ernesto
    Eijndhoven, Monique A. J. van
    Medina, Jose M.
    Hackenberg, Michael
    Pegtel, Michiel
    CELL REPORTS METHODS, 2023, 3 (05):
  • [22] Analysis of Nasal Polyp Neutrophils by Single Cell RNA-Sequencing
    Iwasaki, Naruhito
    Poposki, Julie
    Klinger, Aiko
    Norton, James
    Suh, Lydia
    Stevens, Whitney
    Tan, Bruce
    Peters, Anju
    Grammer, Leslie
    Welch, Kevin
    Smith, Stephanie
    Conley, David
    Kern, Robert
    Schleimer, Robert
    Kato, Atsushi
    JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, 2023, 151 (02) : AB218 - AB218
  • [23] Transcriptomic Analysis of Different Stages of Pigeon Ovaries by RNA-Sequencing
    Xu, Xiaoqin
    Zhao, Xuting
    Lu, Lizhi
    Duan, Xiujun
    Qin, Haorong
    Du, Xue
    Li, Guoqin
    Tao, Zhengrong
    Zhong, Shengliang
    Wang, Genlin
    MOLECULAR REPRODUCTION AND DEVELOPMENT, 2016, 83 (07) : 640 - 648
  • [24] Experimental Considerations for Single-Cell RNA Sequencing Approaches
    Nguyen, Quy H.
    Pervolarakis, Nicholas
    Nee, Kevin
    Kessenbrock, Kai
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2018, 6
  • [25] 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 - +
  • [26] Combined statistics for differential expression analysis of RNA-sequencing data
    Fanidis, Dionysios
    Moulos, Panagiotis
    2019 IEEE 19TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE), 2019, : 170 - 173
  • [27] REPAC: analysis of alternative polyadenylation from RNA-sequencing data
    Eddie L. Imada
    Christopher Wilks
    Ben Langmead
    Luigi Marchionni
    Genome Biology, 24
  • [28] Comprehensive RNA-sequencing analysis of colorectal cancer in a Korean cohort
    Lee, Jaeim
    Kim, Jong-Hwan
    Chu, Hoang Bao Khanh
    Oh, Seong-Taek
    Kang, Sung-Bum
    Lee, Sejoon
    Kim, Duck -Woo
    Oh, Heung-Kwon
    Park, Ji-Hwan
    Kim, Jisu
    Kang, Jisun
    Lee, Jin-Young
    Cho, Sheehyun
    Shim, Hyeran
    Lee, Hong Seok
    Kim, Seon-Young
    Kim, Young-Joon
    Yang, Jin Ok
    Lee, Kil-yong
    MOLECULES AND CELLS, 2024, 47 (03)
  • [29] 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
  • [30] Power analysis of single-cell RNA-sequencing experiments
    Svensson, Valentine
    Natarajan, Kedar Nath
    Ly, Lam-Ha
    Miragaia, Ricardo J.
    Labalette, Charlotte
    Macaulay, Iain C.
    Cvejic, Ana
    Teichmann, Sarah A.
    NATURE METHODS, 2017, 14 (04) : 381 - +