Detection of structural DNA variation from next generation sequencing data: A review of informatic approaches

Cancer Genetics

Volumn 206, Issue 12, 2013, Pages 432-440

  Abel, Haley J ^a   Duncavage, Eric J ^a  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Copy number variation; Informatics; Massively paralleled sequencing; Next generation sequencing; Structural DNA variation

Indexed keywords

COPY NUMBER VARIATION; INFORMATICS; MASSIVELY PARALLELED SEQUENCING; NEXT GENERATION SEQUENCING; STRUCTURAL DNA VARIATION;

DNA COPY NUMBER VARIATIONS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; INFORMATICS; SEQUENCE ANALYSIS, DNA;

EID: 84893864009     PISSN: 22107762     EISSN: 22107770     Source Type: Journal    
DOI: 10.1016/j.cancergen.2013.11.002     Document Type: Review

References (63)

1. Rowley J.D. Letter: a new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature 1973, 243:290-293.
2. Lejeune J., Gautier M., Turpin R. Study of somatic chromosomes from 9 mongoloid children. CR Hebd Seances Acad Sci 1959, 248:1721-1722. [in French].
3. Freeman J., Perry G.H., Feuk L., et al. Copy number variation: new insights in genome diversity. Genome Res 2006, 16:949-961.
4. Cools J., DeAngelo D.J., Gotlib J., et al. Atyrosine kinase created by fusion of the PDGFRA and FIP1L1 genes as a therapeutic target of imatinib in idiopathic hypereosinophilic syndrome. NEngl J Med 2003, 348:1201-1214.
5. de Jesus Marques-Salles T., Liehr T., Mkrtchyan H., et al. Anew chromosomal three-way rearrangement involving MLL masked by a t(9;19)(p11;p13) in an infant with acute myeloid leukemia. Cancer Genet Cytogenet 2009, 189:59-62.
6. Welch J.S., Westervelt P., Ding L., et al. Use of whole-genome sequencing to diagnose a cryptic fusion oncogene. JAMA 2011, 305:1577-1584.
7. Soda M., Choi Y.L., Enomoto M., et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature 2007, 448:561-566.
8. Brodeur G.M., Seeger R.C., Schwab M., et al. Amplification of N-myc in untreated human neuroblastomas correlates with advanced disease stage. Science 1984, 224(4653):1121-1124.
9. von Deimling A., Louis D.N., von Ammon K., et al. Evidence for a tumor suppressor gene on chromosome 19q associated with human astrocytomas, oligodendrogliomas, and mixed gliomas. Cancer Res 1992, 52:4277-4279.
10. Zhou X., Rao N.P., Cole S.W., et al. Progress in concurrent analysis of loss of heterozygosity and comparative genomic hybridization utilizing high density single nucleotide polymorphism arrays. Cancer Genet Cytogenet 2005, 159:53-57.
11. Wiltgen M., Tilz G.P. DNA microarray analysis: principles and clinical impact. Hematology 2007, 12:271-287.
12. Mardis E.R. New strategies and emerging technologies for massively parallel sequencing: applications in medical research. Genome Med 2009, 1:40.
13. Mardis E.R. Next generation sequencing platforms. Annu Rev Anal Chem (Palo Alto Calif) 2013, 6:287-303.
14. Ellis M.J., Ding L., Shen D., et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 2012, 486:353-360.
15. Mardis E.R., Ding L., Dooling D.J., et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. NEngl J Med 2009, 361:1058-1066.
16. Govindan R., Ding L., Griffith M., et al. Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell 2012, 150:1121-1134.
17. Vignot S., Frampton G.M., Soria J.C., et al. Next generation sequencing reveals high concordance of recurrent somatic alterations between primary tumor and metastases from patients with non-small-cell lung cancer. JClin Oncol 2013, 31:2167-2172.
18. Worthey E.A., Mayer A.N., Syverson G.D., et al. Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet Med 2010, 13:255-262.
19. Pritchard C.C., Smith C., Salipante S.J., et al. ColoSeq provides comprehensive lynch and polyposis syndrome mutational analysis using massively parallel sequencing. JMol Diagn 2012, 14:357-366.
20. Clark M.J., Chen R., Lam H.Y., et al. Performance comparison of exome DNA sequencing technologies. Nat Biotechnol 2011, 29:908-914.
21. Walter M.J., Shen D., Ding L., et al. Clonal architecture of secondary acute myeloid leukemia. NEngl J Med 2012, 366:1090-1098.
22. Spencer D.H., Abel H.J., Lockwood C.M., et al. Detection of FLT3 internal tandem duplication in targeted, short-read-length, next generation sequencing data. JMol Diagn 2012, 15:81-93.
23. Duncavage E.J., Abel H.J., Szankasi P., et al. Targeted next generation sequencing of clinically significant gene mutations and translocations in leukemia. Mod Pathol 2012, 25:795-804.
24. Hormozdiari F., Hajirasouliha I., Dao P., et al. Next generation VariationHunter: combinatorial algorithms for transposon insertion discovery. Bioinformatics 2010, 26:i350-i357.
25. Chen K., Wallis J.W., McLellan M.D., et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods 2009, 6:677-681.
26. Quinlan A.R., Clark R.A., Sokolova S., et al. Genome-wide mapping and assembly of structural variant breakpoints in the mouse genome. Genome Res 2010, 20:623-635.
27. Korbel J.O., Abyzov A., Mu X.J., et al. PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data. Genome Biol 2009, 10:R23.
28. Sindi S.S., Onal S., Peng L.C., et al. An integrative probabilistic model for identification of structural variation in sequencing data. Genome Biol 2012, 13:R22.
29. Li H., Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010, 26:589-595.
30. Wang J., Mullighan C.G., Easton J., et al. CREST maps somatic structural variation in cancer genomes with base-pair resolution. Nat Methods 2011, 8:652-654.
31. Suzuki S., Yasuda T., Shiraishi Y., et al. ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information. BMC Bioinformatics 2011, 12(Suppl 14):S7.
32. Abel H.J., Duncavage E.J., Becker N., et al. SLOPE: a quick and accurate method for locating non-SNP structural variation from targeted next generation sequence data. Bioinformatics 2010, 26:2684-2688.
33. Ye K., Schulz M.H., Long Q., et al. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 2009, 25:2865-2871.
34. Yoon S., Xuan Z., Makarov V., et al. Sensitive and accurate detection of copy number variants using read depth of coverage. Genome Res 2009, 19:1586-1592.
35. Bentley D.R., Balasubramanian S., Swerdlow H.P., et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature 2008, 456:53-59.
36. Chiang D.Y., Getz G., Jaffe D.B., et al. High-resolution mapping of copy-number alterations with massively parallel sequencing. Nat Methods 2009, 6(1):99-103.
37. Abyzov A., Urban A.E., Snyder M., et al. CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing. Genome Res 2011, 21:974-984.
38. Ivakhno S., Royce T., Cox A.J., et al. CNAseg-a novel framework for identification of copy number changes in cancer from second-generation sequencing data. Bioinformatics 2011, 26:3051-3058.
39. Xie C., Tammi M.T. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics 2009, 10:80.
40. Olshen A.B., Venkatraman E.S., Lucito R., et al. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 2004, 5:557-572.
41. Nord A.S., Lee M., King M.C., et al. Accurate and exact CNV identification from targeted high-throughput sequence data. BMC Genomics 2011, 12:184.
42. Li J., Lupat R., Amarasinghe K.C., et al. CONTRA: copy number analysis for targeted resequencing. Bioinformatics 2012, 28:1307-1313.
43. Amarasinghe K.C., Li J., Halgamuge S.K. CoNVEX: copy number variation estimation in exome sequencing data using HMM. BMC Bioinformatics 2013, 14(Suppl 2):S2.
44. Sathirapongsasuti J.F., Lee H., Horst B.A., et al. Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV. Bioinformatics 2011, 27:2648-2654.
45. Fromer M., Moran J.L., Chambert K., et al. Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet 2012, 91:597-607.
46. Krumm N., Sudmant P.H., Ko A., et al. Copy number variation detection and genotyping from exome sequence data. Genome Res 2012, 22:1525-1532.
47. Feuk L., Carson A.R., Scherer S.W. Structural variation in the human genome. Nat Rev Genet 2006, 7:85-97.
48. Walsh T., McClellan J.M., McCarthy S.E., et al. Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia. Science 2008, 320:539-543.
49. Sebat J., Lakshmi B., Malhotra D., et al. Strong association of de novo copy number mutations with autism. Science 2007, 316:445-449.
50. Falini B., Mecucci C., Tiacci E., et al. Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. NEngl J Med 2005, 352:254-266.
51. Paschka P., Marcucci G., Ruppert A.S., et al. Adverse prognostic significance of KIT mutations in adult acute myeloid leukemia with inv(16) and t(8;21): a Cancer and Leukemia Group B. Study. J Clin Oncol 2006, 24:3904-3911.
52. Nakao M., Yokota S., Iwai T., et al. Internal tandem duplication of the flt3 gene found in acute myeloid leukemia. Leukemia 1996, 10:1911-1918.
53. Sequist L.V., Martins R.G., Spigel D., et al. First-line gefitinib in patients with advanced non-small-cell lung cancer harboring somatic EGFR mutations. JClin Oncol 2008, 26:2442-2449.
54. DePristo M.A., Banks E., Poplin R., et al. Aframework for variation discovery and genotyping using next generation DNA sequencing data. Nat Genet 2011, 43(5):491-498.
55. Koboldt D.C., Zhang Q., Larson D.E., et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 2012, 22:568-576.
56. Li H., Handsaker B., Wysoker A., et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25:2078-2079.
57. Li H., Ruan J., Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 2008, 18:1851-1858.
58. Zhang Z.D., Du J., Lam H., et al. Identification of genomic indels and structural variations using split reads. BMC Genomics 2011, 12:375.
59. Albers C.A., Lunter G., MacArthur D.G., et al. Dindel: accurate indel calls from short-read data. Genome Res 2011, 21:961-973.
60. Medvedev P., Stanciu M., Brudno M. Computational methods for discovering structural variation with next generation sequencing. Nat Methods 2009, 6(11 Suppl):S13-S20.
61. Hamada M., Wijaya E., Frith M.C., et al. Probabilistic alignments with quality scores: an application to short-read mapping toward accurate SNP/indel detection. Bioinformatics 2011, 27:3085-3092.
62. O'Rawe J., Jiang T., Sun G., et al. Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing. Genome Med 2013, 5:28.
63. Grimm D., Hagmann J., Koenig D., et al. Accurate indel prediction using paired-end short reads. BMC Genomics 2013, 14:132.