MAGERI: Computational pipeline for molecular-barcoded targeted resequencing

PLoS Computational Biology

Volumn 13, Issue 5, 2017, Pages

  Shugay, Mikhail ^a,b,c   Zaretsky, Andrew R ^a,b,d   Shagin, Dmitriy A ^a,b   Shagina, Irina A ^a,b   Volchenkov, Ivan A ^b,d   Shelenkov, Andrew A ^b,d   Lebedin, Mikhail Y ^a,b,c   Bagaev, Dmitriy V ^a   Lukyanov, Sergey ^a,b   Chudakov, Dmitriy M ^a,b,c,e  

^a SHEMYAKIN OVCHINNIKOV INSTITUTE OF BIOORGANIC CHEMISTRY   (Russian Federation)

^b PIROGOV RUSSIAN NATIONAL RESEARCH MEDICAL UNIVERSITY   (Russian Federation)

^c MASARYK UNIVERSITY   (Czech Republic)

^d Evrogen JSC   (Russian Federation)

^e SKOLKOVO INSTITUTE OF SCIENCE AND TECHNOLOGY   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION PROGRAMS; DIAGNOSIS; PIPELINES; TUMORS;

BENCHMARK DATASETS; CANCER DIAGNOSTICS; DNA SAMPLES; GOLD STANDARDS; HIGH-FIDELITY; HIGH-THROUGHPUT; MULTIPLE AREAS; PERFORMANCE; RARE VARIANTS; RESEQUENCING;

DNA;

ARTICLE; BLOOD SAMPLING; CASE REPORT; CONSENSUS SEQUENCE; CONTROLLED STUDY; DNA DETERMINATION; DNA EXTRACTION; DNA SEQUENCE; GENE FREQUENCY; GENE MUTATION; GENE SEQUENCE; GENETIC VARIABILITY; HIGH THROUGHPUT SEQUENCING; HUMAN; HUMAN TISSUE; MAGERI; MELANOMA; MOLECULAR GENETICS; POLYMERASE CHAIN REACTION; SOFTWARE; BIOLOGY; BLOOD; GENETIC DATABASE; GENETICS; NEOPLASM; PROCEDURES; SEQUENCE ANALYSIS;

TUMOR MARKER; VIRUS RNA;

BIOMARKERS, TUMOR; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; NEOPLASMS; RNA, VIRAL; SEQUENCE ANALYSIS, DNA; SEQUENCE ANALYSIS, RNA; SOFTWARE;

EID: 85020126470     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1005480     Document Type: Article

References (48)

1. Diehl F, Schmidt K, Durkee KH, Moore KJ, Goodman SN, et al. (2008) Analysis of mutations in DNA isolated from plasma and stool of colorectal cancer patients. Gastroenterology135: 489–498. doi: 10.1053/j.gastro.2008.05.039 18602395
2. Fan HC, Blumenfeld YJ, Chitkara U, Hudgins L, Quake SR, (2008) Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A105: 16266–16271. doi: 10.1073/pnas.0808319105 18838674
3. Burrell RA, Swanton C, (2014) The evolution of the unstable cancer genome. Curr Opin Genet Dev24: 61–67. doi: 10.1016/j.gde.2013.11.011 24657538
4. Colman RE, Schupp JM, Hicks ND, Smith DE, Buchhagen JL, et al. (2015) Detection of Low-Level Mixed-Population Drug Resistance in Mycobacterium tuberculosis Using High Fidelity Amplicon Sequencing. PLoS One10: e0126626. doi: 10.1371/journal.pone.0126626 25970423
5. Van Laethem K, Theys K, Vandamme AM, (2015) HIV-1 genotypic drug resistance testing: digging deep, reaching wide?Curr Opin Virol14: 16–23. doi: 10.1016/j.coviro.2015.06.001 26114581
6. Faith JJ, Guruge JL, Charbonneau M, Subramanian S, Seedorf H, et al. (2013) The long-term stability of the human gut microbiota. Science341: 1237439. doi: 10.1126/science.1237439 23828941
7. Barrick JE, Lenski RE, (2013) Genome dynamics during experimental evolution. Nat Rev Genet14: 827–839. doi: 10.1038/nrg3564 24166031
8. Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med6: 224ra224.
9. Fernandez-Cuesta L, Perdomo S, Avogbe PH, Leblay N, Delhomme TM, et al. (2016) Identification of Circulating Tumor DNA for the Early Detection of Small-cell Lung Cancer. EBioMedicine10: 117–123. doi: 10.1016/j.ebiom.2016.06.032 27377626
10. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, et al. (2012) VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res22: 568–576. doi: 10.1101/gr.129684.111 22300766
11. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, et al. (2013) Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol31: 213–219. doi: 10.1038/nbt.2514 23396013
12. Harismendy O, Schwab RB, Bao L, Olson J, Rozenzhak S, et al. (2011) Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing. Genome Biol12: R124. doi: 10.1186/gb-2011-12-12-r124 22185227
13. Diehl F, Li M, Dressman D, He Y, Shen D, et al. (2005) Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proc Natl Acad Sci U S A102: 16368–16373. doi: 10.1073/pnas.0507904102 16258065
14. Fleischhacker M, Schmidt B, (2007) Circulating nucleic acids (CNAs) and cancer—a survey. Biochim Biophys Acta1775: 181–232. doi: 10.1016/j.bbcan.2006.10.001 17137717
15. Chen Z, Feng J, Buzin CH, Liu Q, Weiss L, et al. (2009) Analysis of cancer mutation signatures in blood by a novel ultra-sensitive assay: monitoring of therapy or recurrence in non-metastatic breast cancer. PLoS One4: e7220. doi: 10.1371/journal.pone.0007220 19789704
16. Tie J, Kinde I, Wang Y, Wong HL, Roebert J, et al. (2015) Circulating tumor DNA as an early marker of therapeutic response in patients with metastatic colorectal cancer. Ann Oncol26: 1715–1722. doi: 10.1093/annonc/mdv177 25851626
17. Newman AM, Bratman SV, To J, Wynne JF, Eclov NC, et al. (2014) An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med20: 548–554. doi: 10.1038/nm.3519 24705333
18. Blomquist T, Crawford EL, Yeo J, Zhang X, Willey JC, (2015) Control for stochastic sampling variation and qualitative sequencing error in next generation sequencing. Biomol Detect Quantif5: 30–37. doi: 10.1016/j.bdq.2015.08.003 26693143
19. Richardson AL, Iglehart JD, (2012) BEAMing up personalized medicine: mutation detection in blood. Clin Cancer Res18: 3209–3211. doi: 10.1158/1078-0432.CCR-12-0871 22550168
20. Casbon JA, Osborne RJ, Brenner S, Lichtenstein CP, (2011) A method for counting PCR template molecules with application to next-generation sequencing. Nucleic Acids Res39: e81. doi: 10.1093/nar/gkr217 21490082
21. Kinde I, Wu J, Papadopoulos N, Kinzler KW, Vogelstein B, (2011) Detection and quantification of rare mutations with massively parallel sequencing. Proc Natl Acad Sci U S A108: 9530–9535. doi: 10.1073/pnas.1105422108 21586637
22. Kivioja T, Vaharautio A, Karlsson K, Bonke M, Enge M, et al. (2012) Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods9: 72–74.
23. Grun D, Kester L, van Oudenaarden A, (2014) Validation of noise models for single-cell transcriptomics. Nat Methods11: 637–640. doi: 10.1038/nmeth.2930 24747814
24. Gout JF, Thomas WK, Smith Z, Okamoto K, Lynch M, (2013) Large-scale detection of in vivo transcription errors. Proc Natl Acad Sci U S A110: 18584–18589. doi: 10.1073/pnas.1309843110 24167253
25. Deakin CT, Deakin JJ, Ginn SL, Young P, Humphreys D, et al. (2014) Impact of next-generation sequencing error on analysis of barcoded plasmid libraries of known complexity and sequence. Nucleic Acids Res42: e129. doi: 10.1093/nar/gku607 25013183
26. Vollmers C, Sit RV, Weinstein JA, Dekker CL, Quake SR, (2013) Genetic measurement of memory B-cell recall using antibody repertoire sequencing. Proc Natl Acad Sci U S A110: 13463–13468. doi: 10.1073/pnas.1312146110 23898164
27. Britanova OV, Putintseva EV, Shugay M, Merzlyak EM, Turchaninova MA, et al. (2014) Age-related decrease in TCR repertoire diversity measured with deep and normalized sequence profiling. J Immunol192: 2689–2698. doi: 10.4049/jimmunol.1302064 24510963
28. Shugay M, Britanova OV, Merzlyak EM, Turchaninova MA, Mamedov IZ, et al. (2014) Towards error-free profiling of immune repertoires. Nat Methods11: 653–655. doi: 10.1038/nmeth.2960 24793455
29. He L, Sok D, Azadnia P, Hsueh J, Landais E, et al. (2014) Toward a more accurate view of human B-cell repertoire by next-generation sequencing, unbiased repertoire capture and single-molecule barcoding. Sci Rep4: 6778. doi: 10.1038/srep06778 25345460
30. Egorov ES, Merzlyak EM, Shelenkov AA, Britanova OV, Sharonov GV, et al. (2015) Quantitative profiling of immune repertoires for minor lymphocyte counts using unique molecular identifiers. J Immunol194: 6155–6163. doi: 10.4049/jimmunol.1500215 25957172
31. Bottcher R, Amberg R, Ruzius FP, Guryev V, Verhaegh WF, et al. (2012) Using a priori knowledge to align sequencing reads to their exact genomic position. Nucleic Acids Res40: e125. doi: 10.1093/nar/gks393 22581774
32. Dominguez PL, Kolodney MS, (2005) Wild-type blocking polymerase chain reaction for detection of single nucleotide minority mutations from clinical specimens. Oncogene24: 6830–6834. doi: 10.1038/sj.onc.1208832 16116485
33. Bernard PS, Lay MJ, Wittwer CT, (1998) Integrated amplification and detection of the C677T point mutation in the methylenetetrahydrofolate reductase gene by fluorescence resonance energy transfer and probe melting curves. Anal Biochem255: 101–107. doi: 10.1006/abio.1997.2427 9448847
34. Chiu RW, Chan LY, Lam NY, Tsui NB, Ng EK, et al. (2003) Quantitative analysis of circulating mitochondrial DNA in plasma. Clin Chem49: 719–726. 12709361
35. Shcherbo D, Shemiakina IIRyabova AV, Luker KE, Schmidt BT, et al. (2010) Near-infrared fluorescent proteins. Nat Methods7: 827–829. doi: 10.1038/nmeth.1501 20818379
36. Matz M, Shagin D, Bogdanova E, Britanova O, Lukyanov S, et al. (1999) Amplification of cDNA ends based on template-switching effect and step-out PCR. Nucleic Acids Res27: 1558–1560. 10037822
37. Zhou S, Jones C, Mieczkowski P, Swanstrom R, (2015) Primer ID Validates Template Sampling Depth and Greatly Reduces the Error Rate of Next-Generation Sequencing of HIV-1 Genomic RNA Populations. J Virol89: 8540–8555. doi: 10.1128/JVI.00522-15 26041299
38. Kou R, Lam H, Duan H, Ye L, Jongkam N, et al. (2016) Benefits and Challenges with Applying Unique Molecular Identifiers in Next Generation Sequencing to Detect Low Frequency Mutations. PLoS One11: e0146638. doi: 10.1371/journal.pone.0146638 26752634
39. Hovelson DH, McDaniel AS, Cani AK, Johnson B, Rhodes K, et al. (2015) Development and validation of a scalable next-generation sequencing system for assessing relevant somatic variants in solid tumors. Neoplasia17: 385–399. doi: 10.1016/j.neo.2015.03.004 25925381
40. D'Haene N, Le Mercier M, De Neve N, Blanchard O, Delaunoy M, et al. (2015) Clinical Validation of Targeted Next Generation Sequencing for Colon and Lung Cancers. PLoS One10: e0138245. doi: 10.1371/journal.pone.0138245 26366557
41. Rubinstein JC, Sznol M, Pavlick AC, Ariyan S, Cheng E, et al. (2010) Incidence of the V600K mutation among melanoma patients with BRAF mutations, and potential therapeutic response to the specific BRAF inhibitor PLX4032. J Transl Med8: 67. doi: 10.1186/1479-5876-8-67 20630094
42. Schmitt MW, Kennedy SR, Salk JJ, Fox EJ, Hiatt JB, et al. (2012) Detection of ultra-rare mutations by next-generation sequencing. Proc Natl Acad Sci U S A109: 14508–14513. doi: 10.1073/pnas.1208715109 22853953
43. Schmitt MW, Fox EJ, Prindle MJ, Reid-Bayliss KS, True LD, et al. (2015) Sequencing small genomic targets with high efficiency and extreme accuracy. Nat Methods12: 423–425. doi: 10.1038/nmeth.3351 25849638
44. Shao W, Boltz VF, Spindler JE, Kearney MF, Maldarelli F, et al. (2013) Analysis of 454 sequencing error rate, error sources, and artifact recombination for detection of Low-frequency drug resistance mutations in HIV-1 DNA. Retrovirology10: 18. doi: 10.1186/1742-4690-10-18 23402264
45. Yeo ZX, Chan M, Yap YS, Ang P, Rozen S, et al. (2012) Improving indel detection specificity of the Ion Torrent PGM benchtop sequencer. PLoS One7: e45798. doi: 10.1371/journal.pone.0045798 23029247
46. Schirmer M, D'Amore R, Ijaz UZ, Hall N, Quince C, (2016) Illumina error profiles: resolving fine-scale variation in metagenomic sequencing data. BMC Bioinformatics17: 125. doi: 10.1186/s12859-016-0976-y 26968756
47. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, et al. (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin)6: 80–92.
48. Usuyama N, Shiraishi Y, Sato Y, Kume H, Homma Y, et al. (2014) HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations. Bioinformatics30: 3302–3309. doi: 10.1093/bioinformatics/btu537 25123903