Literature DB >> 19745027

Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing.

Hanni Willenbrock1, Jesper Salomon, Rolf Søkilde, Kim Bundvig Barken, Thomas Nøhr Hansen, Finn Cilius Nielsen, Søren Møller, Thomas Litman.   

Abstract

Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification.

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Year:  2009        PMID: 19745027      PMCID: PMC2764476          DOI: 10.1261/rna.1699809

Source DB:  PubMed          Journal:  RNA        ISSN: 1355-8382            Impact factor:   4.942


  11 in total

1.  Statistical modeling of sequencing errors in SAGE libraries.

Authors:  Tim Beissbarth; Lavinia Hyde; Gordon K Smyth; Chris Job; Wee-Ming Boon; Seong-Seng Tan; Hamish S Scott; Terence P Speed
Journal:  Bioinformatics       Date:  2004-08-04       Impact factor: 6.937

2.  Correction of sequence-based artifacts in serial analysis of gene expression.

Authors:  Viatcheslav R Akmaev; Clarence J Wang
Journal:  Bioinformatics       Date:  2004-02-10       Impact factor: 6.937

3.  RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.

Authors:  John C Marioni; Christopher E Mason; Shrikant M Mane; Matthew Stephens; Yoav Gilad
Journal:  Genome Res       Date:  2008-06-11       Impact factor: 9.043

4.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.

Authors:  Ben Langmead; Cole Trapnell; Mihai Pop; Steven L Salzberg
Journal:  Genome Biol       Date:  2009-03-04       Impact factor: 13.583

5.  Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates.

Authors:  Fang Liu; Tor-Kristian Jenssen; Jeff Trimarchi; Claudio Punzo; Connie L Cepko; Lucila Ohno-Machado; Eivind Hovig; Winston Patrick Kuo
Journal:  BMC Genomics       Date:  2007-06-07       Impact factor: 3.969

6.  Cross-platform comparison of SYBR Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC) study.

Authors:  Emi Arikawa; Yanyang Sun; Jie Wang; Qiong Zhou; Baitang Ning; Stacey L Dial; Lei Guo; Jingping Yang
Journal:  BMC Genomics       Date:  2008-07-11       Impact factor: 3.969

7.  A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis.

Authors:  Junfeng Chen; Vikas Agrawal; Magnus Rattray; Marilyn A L West; Dina A St Clair; Richard W Michelmore; Sean J Coughlan; Blake C Meyers
Journal:  BMC Genomics       Date:  2007-11-12       Impact factor: 3.969

8.  A comparison of global gene expression measurement technologies in Arabidopsis thaliana.

Authors:  Sean J Coughlan; Vikas Agrawal; Blake Meyers
Journal:  Comp Funct Genomics       Date:  2004

9.  Substantial biases in ultra-short read data sets from high-throughput DNA sequencing.

Authors:  Juliane C Dohm; Claudio Lottaz; Tatiana Borodina; Heinz Himmelbauer
Journal:  Nucleic Acids Res       Date:  2008-07-26       Impact factor: 16.971

10.  Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms.

Authors:  Peter A C 't Hoen; Yavuz Ariyurek; Helene H Thygesen; Erno Vreugdenhil; Rolf H A M Vossen; Renée X de Menezes; Judith M Boer; Gert-Jan B van Ommen; Johan T den Dunnen
Journal:  Nucleic Acids Res       Date:  2008-10-15       Impact factor: 16.971

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  68 in total

1.  Influence of RNA labeling on expression profiling of microRNAs.

Authors:  John S Kaddis; Daniel H Wai; Jessica Bowers; Nicole Hartmann; Lukas Baeriswyl; Sheetal Bajaj; Michael J Anderson; Robert C Getts; Timothy J Triche
Journal:  J Mol Diagn       Date:  2011-11-07       Impact factor: 5.568

Review 2.  The miR-15/107 group of microRNA genes: evolutionary biology, cellular functions, and roles in human diseases.

Authors:  John R Finnerty; Wang-Xia Wang; Sébastien S Hébert; Bernard R Wilfred; Guogen Mao; Peter T Nelson
Journal:  J Mol Biol       Date:  2010-08-01       Impact factor: 5.469

3.  Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression.

Authors:  Anna Git; Heidi Dvinge; Mali Salmon-Divon; Michelle Osborne; Claudia Kutter; James Hadfield; Paul Bertone; Carlos Caldas
Journal:  RNA       Date:  2010-04-01       Impact factor: 4.942

4.  Modified least-variant set normalization for miRNA microarray.

Authors:  Chen Suo; Agus Salim; Kee-Seng Chia; Yudi Pawitan; Stefano Calza
Journal:  RNA       Date:  2010-10-27       Impact factor: 4.942

Review 5.  Cardiovascular genomics: a biomarker identification pipeline.

Authors:  John H Phan; Chang F Quo; May Dongmei Wang
Journal:  IEEE Trans Inf Technol Biomed       Date:  2012-05-16

6.  Divergent MicroRNA targetomes of closely related circulating strains of a polyomavirus.

Authors:  Chun Jung Chen; Jennifer E Cox; Rodney P Kincaid; Angel Martinez; Christopher S Sullivan
Journal:  J Virol       Date:  2013-08-07       Impact factor: 5.103

7.  Synthetic spike-in standards for RNA-seq experiments.

Authors:  Lichun Jiang; Felix Schlesinger; Carrie A Davis; Yu Zhang; Renhua Li; Marc Salit; Thomas R Gingeras; Brian Oliver
Journal:  Genome Res       Date:  2011-08-04       Impact factor: 9.043

8.  A wholly defined Agilent microarray spike-in dataset.

Authors:  Qianqian Zhu; Jeffrey C Miecznikowski; Marc S Halfon
Journal:  Bioinformatics       Date:  2011-03-16       Impact factor: 6.937

9.  Nuclear and cytoplasmic localization of neural stem cell microRNAs.

Authors:  Clark D Jeffries; Howard M Fried; Diana O Perkins
Journal:  RNA       Date:  2011-03-01       Impact factor: 4.942

10.  miR-17, miR-19b, miR-20a, and miR-106a are down-regulated in human aging.

Authors:  Matthias Hackl; Stefan Brunner; Klaus Fortschegger; Carina Schreiner; Lucia Micutkova; Christoph Mück; Gerhard T Laschober; Günter Lepperdinger; Natalie Sampson; Peter Berger; Dietmar Herndler-Brandstetter; Matthias Wieser; Harald Kühnel; Alois Strasser; Mark Rinnerthaler; Michael Breitenbach; Michael Mildner; Leopold Eckhart; Erwin Tschachler; Andrea Trost; Johann W Bauer; Christine Papak; Zlatko Trajanoski; Marcel Scheideler; Regina Grillari-Voglauer; Beatrix Grubeck-Loebenstein; Pidder Jansen-Dürr; Johannes Grillari
Journal:  Aging Cell       Date:  2010-01-18       Impact factor: 9.304

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