Analysis options for high-throughput sequencing in miRNA expression profiling

BMC Research Notes

Volumn 7, Issue 1, 2014, Pages

  Stokowy, Tomasz ^a,b   Eszlinger, Markus ^c   Świerniak, Michał ^b,e   Fujarewicz, Krzysztof ^a   Jarza̧b, Barbara ^b   Paschke, Ralf ^c   Krohn, Knut ^d  

^a SILESIAN UNIVERSITY OF TECHNOLOGY   (Poland)

^b INSTITUTE OF ONCOLOGY   (Poland)

^c UNIVERSITY OF LEIPZIG   (Germany)

^d UNIVERSITY HOSPITAL LEIPZIG   (Germany)

^e MEDICAL UNIVERSITY OF WARSAW   (Poland)

Author keywords

Follicular thyroid cancer; High throughput sequencing; Microarrays; miRNA expression

Indexed keywords

MICRORNA; MIRN144 MICRORNA, HUMAN; MIRN197 MICRORNA, HUMAN; MIRN221 MICRORNA, HUMAN; MIRN222 MICRORNA, HUMAN; TUMOR MARKER;

ADENOCARCINOMA; ARTICLE; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; METHODOLOGY; REPRODUCIBILITY; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; SENSITIVITY AND SPECIFICITY; STATISTICS; THYROID TUMOR;

ADENOCARCINOMA, FOLLICULAR; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MICRORNAS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION; SENSITIVITY AND SPECIFICITY; THYROID NEOPLASMS; TUMOR MARKERS, BIOLOGICAL;

EID: 84899064730     PISSN: None     EISSN: 17560500     Source Type: Journal    
DOI: 10.1186/1756-0500-7-144     Document Type: Article

References (44)

1. A uniform system for microRNA annotation. Ambros V, Bartel B, Bartel DP, Burge CB, Carrington JC, Chen X, Dreyfuss G, Eddy SR, Griffiths-Jones S, Marshall M, Matzke M, Ruvkun G, Tuschl T, RNA 2003 9 277 279 10.1261/rna.2183803 12592000
2. MicroRNAs: genomics, biogenesis, mechanism, and function. Bartel DP, Cell 2004 116 281 297 10.1016/S0092-8674(04)00045-5 14744438
3. Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Huntzinger E, Izaurralde E, Nat Rev Genet 2011 12 99 110 10.1038/nrg2936 21245828
4. MicroRNA profiling: approaches and considerations. Pritchard CC, Cheng HH, Tewari M, Nat Rev Genet 2012 13 358 369 22510765
5. MicroRNAs in thyroid cancer. De la Chapelle A, Jazdzewski K, J Clin Endocrinol Metab 2011 96 3326 3336 10.1210/jc.2011-1004 21865360
6. microRNA-Seq reveals cocaine-regulated expression of striatal microRNAs. Eipper-Mains JE, Kiraly DD, Palakodeti D, Mains RE, Eipper BA, Graveley BR, RNA 2011 17 1529 1543 10.1261/rna.2775511 21708909
7. MicroRNA expression profiles classify human cancers. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, Downing JR, Jacks T, Horvitz HR, Golub TR, Nature 2005 435 834 838 10.1038/nature03702 15944708
8. MicroRNAs in tumorigenesis: a primer. Zhang W, Dahlberg JE, Tam W, Am J Pathol 2007 171 728 738 10.2353/ajpath.2007.070070 17724137
9. Proliferation and tumorigenesis of a murine sarcoma cell line in the absence of DICER1. Ravi A, Gurtan AM, Kumar MS, Bhutkar A, Chin C, Lu V, Lees JA, Jacks T, Sharp PA, Cancer Cell 2012 21 848 855 10.1016/j.ccr.2012.04.037 22698408
10. Dynamic linear model for the identification of miRNAs in next-generation sequencing data. Evan Johnson W, Welker NC, Bass BL, Biometrics 2011 67 1206 1214 10.1111/j.1541-0420.2010.01570.x 21385162
11. Bioinformatic analysis of barcoded cDNA libraries for small RNA profiling by next-generation sequencing. Farazi TA, Brown M, Morozov P, Ten Hoeve JJ, Ben-Dov IZ, Hovestadt V, Hafner M, Renwick N, Mihailović A, Wessels LFA, Tuschl T, Methods 2012 58 171 187 10.1016/j.ymeth.2012.07.020 22836126
12. Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. Git A, Dvinge H, Salmon-Divon M, Osborne M, Kutter C, Hadfield J, Bertone P, Caldas C, RNA 2010 16 991 1006 10.1261/rna.1947110 20360395
13. Measuring microRNAs: comparisons of microarray and quantitative PCR measurements, and of different total RNA prep methods. Ach RA, Wang H, Curry B, BMC Biotechnol 2008 8 69 10.1186/1472-6750-8-69 18783629
14. Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis. Chen Y, Gelfond JAL, McManus LM, Shireman PK, BMC Genomics 2009 10 407 10.1186/1471-2164-10-407 19715577
15. Comparison of microarray platforms for measuring differential microRNA expression in paired normal/cancer colon tissues. Callari M, Dugo M, Musella V, Marchesi E, Chiorino G, Grand MM, Pierotti MA, Daidone MG, Canevari S, De Cecco L, PLoS ONE 2012 7 45105 10.1371/journal.pone.0045105 23028787
16. Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing. Willenbrock H, Salomon J, Søkilde R, Barken KB, Hansen TN, Nielsen FC, Møller S, Litman T, RNA 2009 15 2028 2034 10.1261/rna.1699809 19745027
17. Differences in microRNA detection levels are technology and sequence dependent. Leshkowitz D, Horn-Saban S, Parmet Y, Feldmesser E, RNA 2013 19 527 538 10.1261/rna.036475.112 23431331
18. Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs. Pradervand S, Weber J, Lemoine F, Consales F, Paillusson A, Dupasquier M, Thomas J, Richter H, Kaessmann H, Beaudoing E, Hagenbüchle O, Harshman K, Biotechniques 2010 48 219 222 10.2144/000113367 20359303
19. Multi-platform analysis of microRNA expression measurements in RNA from fresh frozen and FFPE tissues. Kolbert CP, Feddersen RM, Rakhshan F, Grill DE, Simon G, Middha S, Jang JS, Simon V, Schultz DA, Zschunke M, Lingle W, Carr JM, Thompson EA, Oberg AL, Eckloff BW, Wieben ED, Li P, Yang P, Jen J, PLoS ONE 2013 8 52517 10.1371/journal.pone.0052517 23382819
20. Molecular signatures of thyroid follicular neoplasia. Borup R, Rossing M, Henao R, Yamamoto Y, Krogdahl A, Godballe C, Winther O, Kiss K, Christensen L, Høgdall E, Bennedbaek F, Nielsen FC, Endocr Relat Cancer 2010 17 691 708 10.1677/ERC-09-0288 20668010
21. Current state and future perspective of molecular diagnosis of fine-needle aspiration biopsy of thyroid nodules. Ferraz C, Eszlinger M, Paschke R, J Clin Endocrinol Metab 2011 96 2016 2026 10.1210/jc.2010-2567 21593119
22. Expression profiling of microRNAs by deep sequencing. Creighton CJ, Reid JG, Gunaratne PH, Brief Bioinform 2009 10 490 497 10.1093/bib/bbp019 19332473
23. Next generation sequencing of miRNAs-strategies, resources and methods. Motameny S, Wolters S, Nürnberg P, Schumacher B, Genes 2010 1 70 84 10.3390/genes1010070
24. Fast gapped-read alignment with Bowtie 2. Langmead B, Salzberg SL, Nat Methods 2012 9 357 359 10.1038/nmeth.1923 22388286
25. miRBase: integrating microRNA annotation and deep-sequencing data. Kozomara A, Griffiths-Jones S, Nucleic Acids Res 2011 39 Database issue 152 D157 21037258
26. BEDTools: a flexible suite of utilities for comparing genomic features. Quinlan AR, Hall IM, Bioinformatics 2010 26 841 842 10.1093/bioinformatics/ btq033 20110278
27. MicroRNA expression profiling of thyroid tumors: biological significance and diagnostic utility. Nikiforova MN, Tseng GC, Steward D, Diorio D, Nikiforov YE, J Clin Endocrinol Metab 2008 93 1600 1608 10.1210/jc.2007-2696 18270258
28. A limited set of human MicroRNA is deregulated in follicular thyroid carcinoma. Weber F, Teresi RE, Broelsch CE, Frilling A, Eng C, J Clin Endocrinol Metab 2006 91 3584 3591 10.1210/jc.2006-0693 16822819
29. Down-regulation of microRNAs controlling tumourigenic factors in follicular thyroid carcinoma. Rossing M, Borup R, Henao R, Winther O, Vikesaa J, Niazi O, Godballe C, Krogdahl A, Glud M, Hjort-Sørensen C, Kiss K, Bennedbæk FN, Nielsen FC, J Mol Endocrinol 2012 48 11 23 10.1530/JME-11-0039 22049245
30. Cutadapt removes adapter sequences from high-throughput sequencing reads. Martin M, EMBnet J 2011 17 10 12
31. The sequence alignment/Map format and SAMtools. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Bioinformatics 2009 25 2078 2079 10.1093/bioinformatics/btp352 19505943
32. Bioconductor: open software development for computational biology and bioinformatics. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J, Genome Biol 2004 5 80 10.1186/gb-2004-5-10-r80 15461798
33. ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data. Morgan M, Anders S, Lawrence M, Aboyoun P, Pagès H, Gentleman R, Bioinformatics 2009 25 2607 2608 10.1093/bioinformatics/btp450 19654119
34. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B, Nat Methods 2008 5 621 628 10.1038/nmeth.1226 18516045
35. Differential expression analysis for sequence count data. Anders S, Huber W, Genome Biol 2010 11 106 10.1186/gb-2010-11-10-r106 20979621
36. A scaling normalization method for differential expression analysis of RNA-seq data. Robinson MD, Oshlack A, Genome Biol 2010 11 25 10.1186/gb-2010-11-3-r25 20196867
37. Identification of novel microRNA-like-coding sites on the long-stem microRNA precursors in Arabidopsis. Shao C, Wu Q, Qiu J, Jin S, Zhang B, Qian J, Chen M, Meng Y, Gene 2013 527 477 483 10.1016/j.gene.2013.06.070 23850578
38. High-throughput sequencing reveals differential expression of miRNAs in intestine from sea cucumber during aestivation. Chen M, Zhang X, Liu J, Storey KB, PLoS ONE 2013 8 76120 10.1371/journal.pone.0076120 24143179
39. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N, Nucleic Acids Res 2012 40 37 52 10.1093/nar/gkr688 21911355
40. Principles of microRNA-target recognition. Brennecke J, Stark A, Russell RB, Cohen SM, PLoS Biol 2005 3 85 10.1371/journal.pbio.0030085 15723116
41. Formation, regulation and evolution of Caenorhabditis elegans 3′UTRs. Jan CH, Friedman RC, Ruby JG, Bartel DP, Nature 2011 469 97 101 10.1038/nature09616 21085120
42. Inverse correlation of miRNA and cell cycle-associated genes suggests influence of miRNA on benign thyroid nodule tumorigenesis. Ferraz C, Lorenz S, Wojtas B, Bornstein SR, Paschke R, Eszlinger M, J Clin Endocrinol Metab 2013 98 8 E16 10.1210/jc.2012-2564 23144465
43. Analysis of the accessibility of CLIP bound sites reveals that nucleation of the miRNA:mRNA pairing occurs preferentially at the 3′-end of the seed match. Marín RM, Voellmy F, von Erlach T, Vaníček J, RNA 2012 18 1760 1770 10.1261/rna.033282.112 22915600
44. Evaluation of candidate diagnostic microRNAs in thyroid fine-needle aspiration biopsy samples. Kitano M, Rahbari R, Patterson EE, Steinberg SM, Prasad NB, Wang Y, Zeiger MA, Kebebew E, Thyroid 2012 22 285 291 10.1089/thy.2011.0313 22304369