DOI QR코드

DOI QR Code

Massive Parallel Sequencing for Diagnostic Genetic Testing of BRCA Genes - a Single Center Experience

  • Published : 2015.12.03

Abstract

The aim of this study was to implement massive parallel sequencing (MPS) technology in clinical genetics testing. We developed and tested an amplicon-based method for resequencing the BRCA1 and BRCA2 genes on an Illumina MiSeq to identify disease-causing mutations in patients with hereditary breast or ovarian cancer (HBOC). The coding regions of BRCA1 and BRCA2 were resequenced in 96 HBOC patient DNA samples obtained from different sample types: peripheral blood leukocytes, whole blood drops dried on paper, and buccal wash epithelia. A total of 16 random DNA samples were characterized using standard Sanger sequencing and applied to optimize the variant calling process and evaluate the accuracy of the MPS-method. The best bioinformatics workflow included the filtration of variants using GATK with the following cut-offs: variant frequency >14%, coverage ($>25{\times}$) and presence in both the forward and reverse reads. The MPS method had 100% sensitivity and 94.4% specificity. Similar accuracy levels were achieved for DNA obtained from the different sample types. The workflow presented herein requires low amounts of DNA samples (170 ng) and is cost-effective due to the elimination of DNA and PCR product normalization steps.

Keywords

References

  1. Abecasis GR, Altshuler D, Auton A, et al (2010). A map of human genome variation from population-scale sequencing. Nature, 467, 1061-73. https://doi.org/10.1038/nature09534
  2. Albert TJ, Molla MN, Muzny DM, et al (2007). Direct selection of human genomic loci by microarray hybridization. Nat Methods, 4, 903-5. https://doi.org/10.1038/nmeth1111
  3. Chan M, Ji SM, Yeo ZX, et al (2012). Development of a next-generation sequencing method for BRCA mutation screening: a comparison between a high-throughput and a benchtop platform. J Mol Diagn, 14, 602-12. https://doi.org/10.1016/j.jmoldx.2012.06.003
  4. De Leeneer K, Hellemans J, De Schrijver J, et al (2011). Massive parallel amplicon sequencing of the breast cancer genes BRCA1 and BRCA2: opportunities, challenges, and limitations. Hum Mutat, 32, 335-44. https://doi.org/10.1002/humu.21428
  5. Diego S (2014). Entire document and oligonucleotide $sequences^{(c)}$ 2007-2013 Illumina, Inc. All rights reserved. 1-28
  6. Euhus DM, Smith KC, Robinson L, et al (2002). Pretest prediction of BRCA1 or BRCA2 mutation by risk counselors and the computer model BRCAPRO. J Natl Cancer Inst, 94, 844-51. https://doi.org/10.1093/jnci/94.11.844
  7. Feliubadalo L, Lopez-Doriga A, Castellsague E, et al (2013). Next-generation sequencing meets genetic diagnostics: development of a comprehensive workflow for the analysis of BRCA1 and BRCA2 genes. Eur J Hum Genet, 21, 864-70. https://doi.org/10.1038/ejhg.2012.270
  8. Garrison E, Marth G (2012). Haplotype-based variant detection from short-read sequencing. 1-9
  9. Gnirke A, Melnikov A, Maguire J, et al (2009). Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nat Biotechnol, 27, 182-9. https://doi.org/10.1038/nbt.1523
  10. Hernan I, Borras E, de Sousa Dias M, et al (2012). Detection of genomic variations in BRCA1 and BRCA2 genes by long-range PCR and next-generation sequencing. J Mol Diagn, 14, 286-93. https://doi.org/10.1016/j.jmoldx.2012.01.013
  11. Johansson H, Isaksson M, Sorqvist EF, et al (2011). Targeted resequencing of candidate genes using selector probes. Nucleic Acids Res, 39, 8.
  12. King M-C, Marks JH, Mandell JB (2003). Breast and ovarian cancer risks due to inherited mutations in BRCA1 and BRCA2. Science, 302, 643-6. https://doi.org/10.1126/science.1088759
  13. Kumar P, Henikoff S, Ng PC (2009). Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc, 4, 1073-81. https://doi.org/10.1038/nprot.2009.86
  14. Li H, Durbin R (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25, 1754-60. https://doi.org/10.1093/bioinformatics/btp324
  15. Li H, Handsaker B, Wysoker A, Fennell T, et al (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25, 2078-9. https://doi.org/10.1093/bioinformatics/btp352
  16. McKenna A, Hanna M, Banks E, et al (2010). The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res, 20, 1297-303. https://doi.org/10.1101/gr.107524.110
  17. Montagna M, Dalla Palma M, Menin C, et al (2003). Genomic rearrangements account for more than one-third of the BRCA1 mutations in northern Italian breast/ovarian cancer families. Hum Mol Genet, 12, 1055-61. https://doi.org/10.1093/hmg/ddg120
  18. Morgan JE, Carr IM, Sheridan E, et al (2010). Genetic diagnosis of familial breast cancer using clonal sequencing. Hum Mutat, 31, 484-91. https://doi.org/10.1002/humu.21216
  19. Ng SB, Turner EH, Robertson PD, et al (2009). Targeted capture and massively parallel sequencing of 12 human exomes. Nature, 461, 272-6. https://doi.org/10.1038/nature08250
  20. Okou DT, Steinberg KM, Middle C, et al (2007). Microarraybased genomic selection for high-throughput resequencing. Nat Methods, 4, 907-9. https://doi.org/10.1038/nmeth1109
  21. Thomassen M, Gerdes AM, Cruger D, Jensen PKA, Kruse TA (2006). Low frequency of large genomic rearrangements of BRCA1 and BRCA2 in western Denmark. Cancer Genet Cytogenet, 168, 168-71. https://doi.org/10.1016/j.cancergencyto.2005.12.016
  22. Thompson JF, Reifenberger JG, Giladi E, et al (2012). Singlestep capture and sequencing of natural DNA for detection of BRCA1 mutations. Genome Res, 22, 340-5. https://doi.org/10.1101/gr.122192.111
  23. Walsh T, Casadei S, Coats KH, et al (2006). Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer. JAMA, 295, 1379-88. https://doi.org/10.1001/jama.295.12.1379
  24. Walsh T, Lee MK, Casadei S, et al (2010). Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci USA, 107, 12629-33. https://doi.org/10.1073/pnas.1007983107
  25. Wang K, Li M, Hakonarson H (2010). ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res, 38, 164. https://doi.org/10.1093/nar/gkq603
  26. Zvelebil M, Baum J (2007). Understanding Bioinformatic. Garland Science, New York, 356.

Cited by

  1. cutPrimers: A New Tool for Accurate Cutting of Primers from Reads of Targeted Next Generation Sequencing vol.24, pp.11, 2017, https://doi.org/10.1089/cmb.2017.0096
  2. Loss of Heterozygosity in BRCA1 and BRCA2 Genes in Patients with Ovarian Cancer and Probability of Its Use for Clinical Classification of Variations vol.165, pp.1, 2018, https://doi.org/10.1007/s10517-018-4107-9