Identifying fusion transcripts using next generation sequencing

Wiley Interdisciplinary Reviews: RNA

Volumn 7, Issue 6, 2016, Pages 811-823

  Kumar, Shailesh ^a   Razzaq, Sundus Khalid ^a   Vo, Angie Duy ^a   Gautam, Mamta ^a   Li, Hui ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHIMERIC RNA; FUSION TRANSCRIPT; RNA; UNCLASSIFIED DRUG;

CANCER DIAGNOSIS; CANCER PROGNOSIS; CANCER THERAPY; CELL LINE; CHROMOSOME REARRANGEMENT; GENE FUSION; HUMAN; NEXT GENERATION SEQUENCING; PRIORITY JOURNAL; REVIEW; RNA SEQUENCE; RNA SPLICING; SOFTWARE; ANIMAL; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; HIGH THROUGHPUT SEQUENCING; PROCEDURES;

ANIMALS; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE FUSION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; SOFTWARE;

EID: 84991448123     PISSN: 17577004     EISSN: 17577012     Source Type: Journal    
DOI: 10.1002/wrna.1382     Document Type: Review

References (76)

1. Tkachuk DC, Westbrook CA, Andreeff M, Donlon TA, Cleary ML, Suryanarayan K, Homge M, Redner A, Gray J, Pinkel D. Detection of bcr-abl fusion in chronic myelogeneous leukemia by in situ hybridization. Science 1990, 250:559–562.
2. Mitelman F, Johansson B, Mertens F. The impact of translocations and gene fusions on cancer causation. Nat Rev Cancer 2007, 7:233–245.
3. Morgan GJ, Wiedemann LM. Molecular biology of the Philadelphia positive leukaemias. Recenti Prog Med 1989, 80:508–519.
4. Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun X-W, Varambally S, Cao X, Tchinda J, Kuefer R, et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 2005, 310:644–648.
5. Soda M, Choi YL, Enomoto M, Takada S, Yamashita Y, Ishikawa S, Fujiwara S, Watanabe H, Kurashina K, Hatanaka H, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature 2007, 448:561–566.
6. Frattini V, Trifonov V, Chan JM, Castano A, Lia M, Abate F, Keir ST, Ji AX, Zoppoli P, Niola F, et al. The integrated landscape of driver genomic alterations in glioblastoma. Nat Genet 2013, 45:1141–1149.
7. Honeyman JN, Simon EP, Robine N, Chiaroni-Clarke R, Darcy DG, Lim IIP, Gleason CE, Murphy JM, Rosenberg BR, Teegan L, et al. Detection of a recurrent DNAJB1-PRKACA chimeric transcript in fibrolamellar hepatocellular carcinoma. Science 2014, 343:1010–1014.
8. Guffanti A, Iacono M, Pelucchi P, Kim N, Soldà G, Croft LJ, Taft RJ, Rizzi E, Askarian-Amiri M, Bonnal RJ, et al. A transcriptional sketch of a primary human breast cancer by 454 deep sequencing. BMC Genomics 2009, 10:163.
9. Berger MF, Levin JZ, Vijayendran K, Sivachenko A, Adiconis X, Maguire J, Johnson LA, Robinson J, Verhaak RG, Sougnez C, et al. Integrative analysis of the melanoma transcriptome. Genome Res 2010, 20:413–427.
10. Steidl C, Shah SP, Woolcock BW, Rui L, Kawahara M, Farinha P, Johnson NA, Zhao Y, Telenius A, Neriah S Ben, et al. MHC class II transactivator CIITA is a recurrent gene fusion partner in lymphoid cancers. Nature 2011, 471:377–381.
11. McPherson A, Hormozdiari F, Zayed A, Giuliany R, Ha G, Sun MGF, Griffith M, Heravi Moussavi A, Senz J, Melnyk N, et al. deFuse: an algorithm for gene fusion discovery in tumor RNA-Seq data. PLoS Comput Biol 2011, 7:e1001138.
12. Su X, Zhan P, Gavine PR, Morgan S, Womack C, Ni X, Shen D, Bang Y-J, Im S-A, Ho Kim W, et al. FGFR2 amplification has prognostic significance in gastric cancer: results from a large international multicentre study. Br J Cancer 2014, 110:967–975.
13. Dancey JE, Bedard PL, Onetto N, Hudson TJ. The genetic basis for cancer treatment decisions. Cell 2012, 148:409–420.
14. Wolyniec K, Carney DA, Haupt S, Haupt Y. New strategies to direct therapeutic targeting of PML to treat cancers. Front Oncol 2013, 3:124.
15. Gingeras TR. Implications of chimaeric non-co-linear transcripts. Nature 2009, 461:206–211.
16. Li H, Wang J, Ma X, Sklar J. Gene fusions and RNA trans-splicing in normal and neoplastic human cells. Cell Cycle 2009, 8:218–222.
17. Zhang Y, Gong M, Yuan H, Park HG, Frierson HF, Li H. Chimeric transcript generated by cis-splicing of adjacent genes regulates prostate cancer cell proliferation. Cancer Discov 2012, 2:598–607.
18. Qin F, Song Z, Babiceanu M, Song Y, Facemire L, Singh R, Adli M, Li H. Discovery of CTCF-sensitive cis-spliced fusion RNAs between adjacent genes in human prostate cells. PLoS Genet 2015, 11:e1005001.
19. Babiceanu M, Qin F, Xie Z, Jia Y, Lopez K, Janus N, Facemire L, Kumar S, Pang Y, Qi Y, et al. Recurrent chimeric fusion RNAs in non-cancer tissues and cells. Nucleic Acids Res 2016, 44:2859–2872.
20. Magrangeas F, Pitiot G, Dubois S, Bragado-Nilsson E, Chérel M, Jobert S, Lebeau B, Boisteau O, Lethé B, Mallet J, et al. Cotranscription and intergenic splicing of human galactose-1-phosphate uridylyltransferase and interleukin-11 receptor alpha-chain genes generate a fusion mRNA in normal cells. Implication for the production of multidomain proteins during evolution. J Biol Chem 1998, 273:16005–16010.
21. Frenkel-Morgenstern M, Lacroix V, Ezkurdia I, Levin Y, Gabashvili A, Prilusky J, Del Pozo A, Tress M, Johnson R, Guigo R, et al. Chimeras taking shape: potential functions of proteins encoded by chimeric RNA transcripts. Genome Res 2012, 22:1231–1242.
22. Carrara M, Beccuti M, Lazzarato F, Cavallo F, Cordero F, Donatelli S, Calogero RA. State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues? BMC Bioinformatics 2013, 14(Suppl 7):S2.
23. Campbell PJ, Stephens PJ, Pleasance ED, O'Meara S, Li H, Santarius T, Stebbings LA, Leroy C, Edkins S, Hardy C, et al. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat Genet 2008, 40:722–729.
24. Hampton OA, Den Hollander P, Miller CA, Delgado DA, Li J, Coarfa C, Harris RA, Richards S, Scherer SE, Muzny DM, et al. A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome. Genome Res 2009, 19:167–177.
25. Levin JZ, Berger MF, Adiconis X, Rogov P, Melnikov A, Fennell T, Nusbaum C, Garraway LA, Gnirke A. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biol 2009, 10:R115.
26. Maher CA, Kumar-Sinha C, Cao X, Kalyana-Sundaram S, Han B, Jing X, Sam L, Barrette T, Palanisamy N, Chinnaiyan AM. Transcriptome sequencing to detect gene fusions in cancer. Nature 2009, 458:97–101.
27. Maher CA, Palanisamy N, Brenner JC, Cao X, Kalyana-Sundaram S, Luo S, Khrebtukova I, Barrette TR, Grasso C, Yu J, et al. Chimeric transcript discovery by paired-end transcriptome sequencing. Proc Natl Acad Sci U S A 2009, 106:12353–12358.
28. Edgren H, Murumagi A, Kangaspeska S, Nicorici D, Hongisto V, Kleivi K, Rye IH, Nyberg S, Wolf M, Borresen-Dale A-L, et al. Identification of fusion genes in breast cancer by paired-end RNA-sequencing. Genome Biol 2011, 12:R6.
29. Sboner A, Habegger L, Pflueger D, Terry S, Chen DZ, Rozowsky JS, Tewari AK, Kitabayashi N, Moss BJ, Chee MS, et al. FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data. Genome Biol 2010, 11:R104.
30. Zhang J, White NM, Schmidt HK, Fulton RS, Tomlinson C, Warren WC, Wilson RK, Maher CA. INTEGRATE: gene fusion discovery using whole genome and transcriptome data. Genome Res 2016, 26:108–118.
31. Hoogstrate Y, Böttcher R, Hiltemann S, van der Spek P, Jenster G, Stubbs AP. FuMa: reporting overlap in RNA-seq detected fusion genes. Bioinformatics 2015, 32:1226–1228.
32. Weirather JL, Afshar PT, Clark TA, Tseng E, Powers LS, Underwood JG, Zabner J, Korlach J, Wong WH, Au KF. Characterization of fusion genes and the significantly expressed fusion isoforms in breast cancer by hybrid sequencing. Nucleic Acids Res 2015, 43:e116.
33. Davidson NM, Majewski IJ, Oshlack A. JAFFA: High sensitivity transcriptome-focused fusion gene detection. Genome Med 2015, 7:43.
34. Chuang T-J, Wu C-S, Chen C-Y, Hung L-Y, Chiang T-W, Yang M-Y. NCLscan: accurate identification of non-co-linear transcripts (fusion, trans-splicing and circular RNA) with a good balance between sensitivity and precision. Nucleic Acids Res 2015, 44:e29.
35. Fernandez-Cuesta L, Sun R, Menon R, George J, Lorenz S, Meza-Zepeda LA, Peifer M, Plenker D, Heuckmann JM, Leenders F, et al. Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data. Genome Biol 2015, 16:7.
36. Qadir MA, Zhan SH, Kwok B, Bruestle J, Drees B, Popescu O-E, Sorensen PH. ChildSeq-RNA: A next-generation sequencing-based diagnostic assay to identify known fusion transcripts in childhood sarcomas. J Mol Diagn 2014, 16:361–370.
37. Nicorici D, Satalan M, Edgren H, Kangaspeska S, Murumagi A, Kallioniemi O, Virtanen S, Kilkku O. FusionCatcher – a tool for finding somatic fusion genes in paired-end RNA-sequencing data. BioRxiv 2014. doi: http://dx.doi.org/10.1101/011650
38. Abate F, Zairis S, Ficarra E, Acquaviva A, Wiggins CH, Frattini V, Lasorella A, Iavarone A, Inghirami G, Rabadan R. Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer. BMC Syst Biol 2014, 8:97.
39. Torres-Garcia W, Zheng S, Sivachenko A, Vegesna R, Wang Q, Yao R, Berger MF, Weinstein JN, Getz G, Verhaak RGW. PRADA: pipeline for RNA sequencing data analysis. Bioinformatics 2014, 30:2224–2226.
40. Philippe N, Salson M, Commes T, Rivals E. CRAC: an integrated approach to the analysis of RNA-seq reads. Genome Biol 2013, 14:R30.
41. Liu C, Ma J, Chang CJ, Zhou X. FusionQ: a novel approach for gene fusion detection and quantification from paired-end RNA-Seq. BMC Bioinformatics 2013, 14:193.
42. Jia W, Qiu K, He M, Song P, Zhou Q, Zhou F, Yu Y, Zhu D, Nickerson ML, Wan S, et al. SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data. Genome Biol 2013, 14:R12.
43. Abate F, Acquaviva A, Paciello G, Foti C, Ficarra E, Ferrarini A, Delledonne M, Iacobucci I, Soverini S, Martinelli G, et al. Bellerophontes: an RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model. Bioinformatics 2012, 28:2114–2121.
44. Chen K, Wallis JW, Kandoth C, Kalicki-Veizer JM, Mungall KL, Mungall AJ, Jones SJ, Marra MA, Ley TJ, Mardis ER, et al. BreakFusion: targeted assembly-based identification of gene fusions in whole transcriptome paired-end sequencing data. Bioinformatics 2012, 28:1923–1924.
45. Supper J, Gugenmus C, Wollnik J, Drueke T, Scherf M, Hahn A, Grote K, Bretschneider N, Klocke B, Zinser C, et al. Detecting and visualizing gene fusions. Methods 2013, 59:S24–S28.
46. Yorukoglu D, Hach F, Swanson L, Collins CC, Birol I, Sahinalp SC. Dissect: detection and characterization of novel structural alterations in transcribed sequences. Bioinformatics 2012, 28:i179–i187.
47. Benelli M, Pescucci C, Marseglia G, Severgnini M, Torricelli F, Magi A. Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript. Bioinformatics 2012, 28:3232–3239.
48. Piazza R, Pirola A, Spinelli R, Valletta S, Redaelli S, Magistroni V, Gambacorti-Passerini C. FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery. Nucleic Acids Res 2012, 40:e123.
49. Francis RW, Thompson-Wicking K, Carter KW, Anderson D, Kees UR, Beesley AH. FusionFinder: a software tool to identify expressed gene fusion candidates from RNA-Seq data. PLoS One 2012, 7:e39987.
50. McPherson A, Wu C, Wyatt AW, Shah S, Collins C, Sahinalp SC. nFuse: discovery of complex genomic rearrangements in cancer using high-throughput sequencing. Genome Res 2012, 22:2250–2261.
51. Iyer MK, Chinnaiyan AM, Maher CA. ChimeraScan: a tool for identifying chimeric transcription in sequencing data. Bioinformatics 2011, 27:2903–2904.
52. McPherson A, Wu C, Hajirasouliha I, Hormozdiari F, Hach F, Lapuk A, Volik S, Shah S, Collins C, Sahinalp SC. Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data. Bioinformatics 2011, 27:1481–1488.
53. Li Y, Chien J, Smith DI, Ma J. FusionHunter: identifying fusion transcripts in cancer using paired-end RNA-seq. Bioinformatics 2011, 27:1708–1710.
54. Ge H, Liu K, Juan T, Fang F, Newman M, Hoeck W. FusionMap: Detecting fusion genes from next-generation sequencing data at base-pair resolution. Bioinformatics 2011, 27:1922–1928.
55. Kinsella M, Harismendy O, Nakano M, Frazer KA, Bafna V. Sensitive gene fusion detection using ambiguously mapping RNA-Seq read pairs. Bioinformatics 2011, 27:1068–1075.
56. Asmann YW, Hossain A, Necela BM, Middha S, Kalari KR, Sun Z, Chai H-S, Williamson DW, Radisky D, Schroth GP, et al. A novel bioinformatics pipeline for identification and characterization of fusion transcripts in breast cancer and normal cell lines. Nucleic Acids Res 2011, 39:e100.
57. Kim D, Salzberg SL. TopHat-Fusion: an algorithm for discovery of novel fusion transcripts. Genome Biol 2011, 12:R72.
58. Wang K, Singh D, Zeng Z, Coleman SJ, Huang Y, Savich GL, He X, Mieczkowski P, Grimm SA, Perou CM, et al. MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res 2010, 38:e178.
59. Li H, Wang J, Mor G, Sklar J. A neoplastic gene fusion mimics trans-splicing of RNAs in normal human cells. Science 2008, 321:1357–1361.
60. Yuan H, Qin F, Movassagh M, Park H, Golden W, Xie Z, Zhang P, Sklar J, Li H. A chimeric RNA characteristic of rhabdomyosarcoma in normal myogenesis process. Cancer Discov 2013, 3:1394–1403.
61. Pleasance ED, Stephens PJ, O'Meara S, McBride DJ, Meynert A, Jones D, Lin M-L, Beare D, Lau KW, Greenman C, et al. A small-cell lung cancer genome with complex signatures of tobacco exposure. Nature 2010, 463:184–190.
62. Totoki Y, Tatsuno K, Yamamoto S, Arai Y, Hosoda F, Ishikawa S, Tsutsumi S, Sonoda K, Totsuka H, Shirakihara T, et al. High-resolution characterization of a hepatocellular carcinoma genome. Nat Genet 2011, 43:464–469.
63. Link DC, Schuettpelz LG, Shen D, Wang J, Walter MJ, Kulkarni S, Payton JE, Ivanovich J, Goodfellow PJ, Le Beau M, et al. Identification of a novel TP53 cancer susceptibility mutation through whole-genome sequencing of a patient with therapy-related AML. JAMA 2011, 305:1568–1576.
64. Taylor BS, Ladanyi M. Clinical cancer genomics: how soon is now? J Pathol 2011, 223:318–326.
65. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 2010, 28:511–515.
66. Mills RE, Walter K, Stewart C, Handsaker RE, Chen K, Alkan C, Abyzov A, Yoon SC, Ye K, Cheetham RK, et al. Mapping copy number variation by population-scale genome sequencing. Nature 2011, 470:59–65.
67. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008, 18:821–829.
68. Schulz MH, Zerbino DR, Vingron M, Birney E. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics 2012, 28:1086–1092.
69. Ha KCH, Lalonde E, Li L, Cavallone L, Natrajan R, Lambros MB, Mitsopoulos C, Hakas J, Kozarewa I, Fenwick K, et al. Identification of gene fusion transcripts by transcriptome sequencing in BRCA1-mutated breast cancers and cell lines. BMC Med Genomics 2011, 4:75.
70. Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med 2013, 368:2059–2074.
71. Liu S, Tsai W-H, Ding Y, Chen R, Fang Z, Huo Z, Kim S, Ma T, Chang T-Y, Priedigkeit NM, et al. Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data. Nucleic Acids Res. 2015, 44:e47.
72. Kumar S, Vo AD, Qin F, Li H. Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data. Sci Rep 2016, 6:21597.
73. Luo J-H, Liu S, Zuo Z-H, Chen R, Tseng GC, Yu YP. Discovery and classification of fusion transcripts in prostate cancer and normal prostate tissue. Am J Pathol 2015, 185:1834–1845.
74. Wang Y, Wu N, Liu J, Wu Z, Dong D. FusionCancer: a database of cancer fusion genes derived from RNA-seq data. Diagn Pathol 2015, 10:131.
75. Carrara M, Beccuti M, Lazzarato F, Cavallo F, Cordero F, Donatelli S, Calogero RA. State-of-the-art fusion-finder algorithms sensitivity and specificity. Biomed Res Int 2013, 2013:340620.
76. Latysheva NS, Babu MM. Discovering and understanding oncogenic gene fusions through data intensive computational approaches. Nucleic Acids Res 2016, 44:4487–4503.