Literature DB >> 31966025

Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.

Zachary T Herbert1, Jyothi Thimmapuram2, Shaojun Xie2, Jamie P Kershner3, Fred W Kolling4, Carol S Ringelberg4, Ashley LeClerc5, Yuriy O Alekseyev5,6, Jun Fan7, Jessica W Podnar8, Holly S Stevenson8, Gary Sommerville1, Shipra Gupta1, Maura Berkeley1, Julie Koeman9, Anoja Perera10, Allison R Scott10, Jennifer K Grenier11, Jeffrey Malik12, John M Ashton12, Kara L Pivarski13, Xinkun Wang13, Gina Kuffel14, Tania E Mesa15, Andrew T Smith15, Jianjun Shen16, Yoko Takata16, Thomas L Volkert17, Jennifer A Love17, Yanping Zhang18, Jun Wang19, Xiaoling Xuei19, Marie Adams9, Stuart S Levine20.   

Abstract

Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs in vivo. Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest. © Association of Biomolecular Resource Facilities.

Keywords:  small RNA sequencing, miRNA sequencing, RNA sequencing, Illumina Library Prep

Mesh:

Substances:

Year:  2020        PMID: 31966025      PMCID: PMC6953595          DOI: 10.7171/jbt.20-3102-001

Source DB:  PubMed          Journal:  J Biomol Tech        ISSN: 1524-0215


  14 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2006-03-20       Impact factor: 11.205

3.  Limitations and possibilities of small RNA digital gene expression profiling.

Authors:  Sam E V Linsen; Elzo de Wit; Georges Janssens; Sheila Heater; Laura Chapman; Rachael K Parkin; Brian Fritz; Stacia K Wyman; Ewart de Bruijn; Emile E Voest; Scott Kuersten; Muneesh Tewari; Edwin Cuppen
Journal:  Nat Methods       Date:  2009-07       Impact factor: 28.547

Review 4.  Metazoan MicroRNAs.

Authors:  David P Bartel
Journal:  Cell       Date:  2018-03-22       Impact factor: 41.582

5.  Proliferation and tumorigenesis of a murine sarcoma cell line in the absence of DICER1.

Authors:  Arvind Ravi; Allan M Gurtan; Madhu S Kumar; Arjun Bhutkar; Christine Chin; Victoria Lu; Jacqueline A Lees; Tyler Jacks; Phillip A Sharp
Journal:  Cancer Cell       Date:  2012-06-12       Impact factor: 31.743

6.  miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades.

Authors:  Marc R Friedländer; Sebastian D Mackowiak; Na Li; Wei Chen; Nikolaus Rajewsky
Journal:  Nucleic Acids Res       Date:  2011-09-12       Impact factor: 16.971

7.  Bias in ligation-based small RNA sequencing library construction is determined by adaptor and RNA structure.

Authors:  Ryan T Fuchs; Zhiyi Sun; Fanglei Zhuang; G Brett Robb
Journal:  PLoS One       Date:  2015-05-05       Impact factor: 3.240

8.  Decreasing miRNA sequencing bias using a single adapter and circularization approach.

Authors:  Sergio Barberán-Soler; Jenny M Vo; Ryan E Hogans; Anne Dallas; Brian H Johnston; Sergei A Kazakov
Journal:  Genome Biol       Date:  2018-09-03       Impact factor: 13.583

9.  Addressing Bias in Small RNA Library Preparation for Sequencing: A New Protocol Recovers MicroRNAs that Evade Capture by Current Methods.

Authors:  Jeanette Baran-Gale; C Lisa Kurtz; Michael R Erdos; Christina Sison; Alice Young; Emily E Fannin; Peter S Chines; Praveen Sethupathy
Journal:  Front Genet       Date:  2015-12-22       Impact factor: 4.599

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

Authors:  Maria D Giraldez; Ryan M Spengler; Alton Etheridge; Paula M Godoy; Andrea J Barczak; Srimeenakshi Srinivasan; Peter L De Hoff; Kahraman Tanriverdi; Amanda Courtright; Shulin Lu; Joseph Khoory; Renee Rubio; David Baxter; Tom A P Driedonks; Henk P J Buermans; Esther N M Nolte-'t Hoen; Hui Jiang; Kai Wang; Ionita Ghiran; Yaoyu E Wang; Kendall Van Keuren-Jensen; Jane E Freedman; Prescott G Woodruff; Louise C Laurent; David J Erle; David J Galas; Muneesh Tewari
Journal:  Nat Biotechnol       Date:  2018-07-16       Impact factor: 54.908

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1.  Quantitative mapping of the cellular small RNA landscape with AQRNA-seq.

Authors:  Jennifer F Hu; Daniel Yim; Duanduan Ma; Sabrina M Huber; Nick Davis; Jo Marie Bacusmo; Sidney Vermeulen; Jieliang Zhou; Thomas J Begley; Michael S DeMott; Stuart S Levine; Valérie de Crécy-Lagard; Peter C Dedon; Bo Cao
Journal:  Nat Biotechnol       Date:  2021-04-15       Impact factor: 54.908

2.  Physiological Fitness and the Pathophysiology of Chronic Lymphocytic Leukemia (CLL).

Authors:  Andrea Sitlinger; Michael A Deal; Erwin Garcia; Dana K Thompson; Tiffany Stewart; Grace A MacDonald; Nicolas Devos; David Corcoran; Janet S Staats; Jennifer Enzor; Kent J Weinhold; Danielle M Brander; J Brice Weinberg; David B Bartlett
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Review 3.  Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis.

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  3 in total

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