A multiplex ligation‑dependent probe amplification‑based next‑generation sequencing approach for the detection of copy number variations in the human genome

Yang,Yongchen; Xia,Chaoran; Zhou,Zaiwei; Wei,Dongkai; Xu,Kangping; Jia,Jia; Xu,Wuhen; Zhang,Hong

doi:10.3892/mmr.2018.9581

A multiplex ligation‑dependent probe amplification‑based next‑generation sequencing approach for the detection of copy number variations in the human genome

Authors:
- Yongchen Yang
- Chaoran Xia
- Zaiwei Zhou
- Dongkai Wei
- Kangping Xu
- Jia Jia
- Wuhen Xu
- Hong Zhang
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Affiliations: Department of Laboratory Medicine, Children's Hospital of Shanghai, Shanghai Jiao Tong University, Shanghai 200040, P.R. China, Shanghai Institute of Medical Genetics, Children's Hospital of Shanghai, Shanghai Jiao Tong University, Shanghai 200040, P.R. China, Product Department, WuXi Health Net Co., Ltd., Shanghai 200131, P.R. China, BasePair Biotechnology Co., Ltd., Suzhou, Jiangsu 215028, P.R. China, Shanghai Center for Bioinformation Technology, Shanghai Institutes of Biomedicine, Shanghai Academy of Science and Technology, Shanghai 201203, P.R. China
Published online on: October 24, 2018 https://doi.org/10.3892/mmr.2018.9581
Pages: 5823-5833

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Abstract

The aim of the present study was to describe a multiplex ligation‑dependent probe amplification (MLPA)‑based next‑generation sequencing (NGS) assay that exhibited a significantly higher efficiency in detecting copy number variations (CNVs) and known single‑nucleotide variants, compared with traditional MLPA. MLPA polymerase chain reaction products were used to construct a library with indexed adapters, which was subsequently tested on an NGS platform, and the resulting data were analyzed by a series of analytical software. The reads from each probe reflected genetic variations in the target regions, and fragment differentiation was based on the specific base composition of the sequences, rather than fragment length, which was determined by capillary electrophoresis. The results of this approach were not only consistent with the MLPA results following capillary electrophoresis, but also coincided with the CNV results from the single‑nucleotide polymorphism array chip. This method allowed high‑throughput screening for the number of fragments and samples by integrating additional indices for detection. Furthermore, this technology precisely and accurately performed large‑scale detection and quantification of DNA variations, thereby serving as an effective and sensitive method for diagnosing genetic disorders caused by CNVs and known single‑nucleotide variations. Notably, MLPA‑NGS circumvents the problems associated with the inaccuracies of NGS in CNV detection due to the use of target sequence capture.

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1	Shaikh TH: Copy number variation disorders. Curr Genet Med Rep. 5:183–190. 2017. View Article : Google Scholar : PubMed/NCBI
2	Hastings PJ, Lupski JR, Rosenberg SM and Ira G: Mechanisms of change in gene copy number. Nat Rev Genet. 10:551–564. 2009. View Article : Google Scholar : PubMed/NCBI
3	Zhang F, Gu W, Hurles ME and Lupski JR: Copy number variation in human health, disease, and evolution. Annu Rev Genomics Hum Genet. 10:451–481. 2009. View Article : Google Scholar : PubMed/NCBI
4	Girirajan S, Campbell CD and Eichler EE: Human copy number variation and complex genetic disease. Annu Rev Genet. 45:203–226. 2011. View Article : Google Scholar : PubMed/NCBI
5	Iourov IY, Vorsanova SG and Yurov YB: Molecular cytogenetics and cytogenomics of brain diseases. Curr Genomics. 9:452–465. 2008. View Article : Google Scholar : PubMed/NCBI
6	Zhang X, Du R, Li S, Zhang F, Jin L and Wang H: Evaluation of copy number variation detection for a SNP array platform. BMC Bioinformatics. 15:502014. View Article : Google Scholar : PubMed/NCBI
7	Stuppia L, Antonucci I, Palka G and Gatta V: Use of the MLPA assay in the molecular diagnosis of gene copy number alterations in human genetic diseases. Int J Mol Sci. 13:3245–3276. 2012. View Article : Google Scholar : PubMed/NCBI
8	Tsuchiya KD, Shaffer LG, Aradhya S, Gastier-Foster JM, Patel A, Rudd MK, Biggerstaff JS, Sanger WG, Schwartz S, Tepperberg JH, et al: Variability in interpreting and reporting copy number changes detected by array-based technology in clinical laboratories. Genet Med. 11:866–873. 2009. View Article : Google Scholar : PubMed/NCBI
9	Manning M and Hudgins L: Professional Practice and Guidelines Committee: Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med. 12:742–745. 2010. View Article : Google Scholar : PubMed/NCBI
10	Schouten JP, McElgunn CJ, Waaijer R, Zwijnenburg D, Diepvens F and Pals G: Relative quantification of 40 nucleic acid sequences by multiplex ligation-dependent probe amplification. Nucleic Acids Res. 30:e572002. View Article : Google Scholar : PubMed/NCBI
11	Banerjee S, Oldridge D, Poptsova M, Hussain WM, Chakravarty D and Demichelis F: A computational framework discovers new copy number variants with functional importance. PLoS One. 6:e175392011. View Article : Google Scholar : PubMed/NCBI
12	Eijk-Van Os PG and Schouten JP: Multiplex ligation-dependent probe amplification (MLPA^®) for the detection of copy number variation in genomic sequences. Methods Mol Biol. 688:97–126. 2011. View Article : Google Scholar : PubMed/NCBI
13	Deveson IW, Chen WY, Wong T, Hardwick SA, Andersen SB, Nielsen LK, Mattick JS and Mercer TR: Representing genetic variation with synthetic DNA standards. Nat Methods. 13:784–791. 2016. View Article : Google Scholar : PubMed/NCBI
14	Zhang X, Xu Y, Liu D, Geng J, Chen S, Jiang Z, Fu Q and Sun K: A modified multiplex ligation-dependent probe amplification method for the detection of 22q11.2 copy number variations in patients with congenital heart disease. BMC Genomics. 16:3642015. View Article : Google Scholar : PubMed/NCBI
15	Gross SJ, Ryan A and Benn P: Noninvasive prenatal testing for 22q11.2 deletion syndrome: Deeper sequencing increases the positive predictive value. Am J Obstet Gynecol. 213:254–255. 2015. View Article : Google Scholar : PubMed/NCBI
16	Chung JH, Cai J, Suskin BG, Zhang Z, Coleman K and Morrow BE: Whole-genome sequencing and integrative genomic analysis approach on two 22q11.2 deletion syndrome family trios for genotype to phenotype correlations. Hum Mutat. 36:797–807. 2015. View Article : Google Scholar : PubMed/NCBI
17	Wang H, Nettleton D and Ying K: Copy number variation detection using next generation sequencing read counts. BMC Bioinformatics. 15:1092014. View Article : Google Scholar : PubMed/NCBI
18	Bunyan DJ, Skinner AC, Ashton EJ, Sillibourne J, Brown T, Collins AL, Cross NC, Harvey JF and Robinson DO: Simultaneous MLPA-based multiplex point mutation and deletion analysis of the dystrophin gene. Mol Biotechnol. 35:135–140. 2007. View Article : Google Scholar : PubMed/NCBI
19	Naoufal R, Legendre M, Couet D, Gilbert-Dussardier B, Kitzis A, Bilan F and Harbuz R: Association of structural and numerical anomalies of chromosome 22 in a patient with syndromic intellectual disability. Eur J Med Genet. 59:483–487. 2016. View Article : Google Scholar : PubMed/NCBI
20	Xiong B, Tan K, Tan YQ, Gong F, Zhang SP, Lu CF, Luo KL, Lu GX and Lin G: Using SNP array to identify aneuploidy and segmental imbalance in translocation carriers. Genom Data. 2:92–95. 2014. View Article : Google Scholar : PubMed/NCBI
21	Belfield EJ, Brown C, Gan X, Jiang C, Baban D, Mithani A, Mott R, Ragoussis J and Harberd NP: Microarray-based optimization to detect genomic deletion mutations. Genom Data. 2:53–54. 2014. View Article : Google Scholar : PubMed/NCBI
22	Gilbert DC, McIntyre A, Summersgill B, Missiaglia E, Goddard NC, Chandler I, Huddart RA and Shipley J: Minimum regions of genomic imbalance in stage I testicular embryonal carcinoma and association of 22q loss with relapse. Genes Chromosomes Cancer. 50:186–195. 2011. View Article : Google Scholar : PubMed/NCBI
23	Chan LF, Campbell DC, Novoselova TV, Clark AJ and Metherell LA: Whole-exome sequencing in the differential diagnosis of primary adrenal insufficiency in children. Front Endocrinol (Lausanne). 6:1132015.PubMed/NCBI
24	Nimkarn S, Gangishetti PK, Yau M and New MI: 21-hydroxylase-deficient congenital adrenal hyperplasiaGeneReviews^®. Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Stephens K and Amemiya A: Seattle (WA): 1993
25	Wong A, Martin Lese C, Heretis K, Ruffalo T, Wilber K, King W and Ledbetter DH: Detection and calibration of microdeletions and microduplications by array-based comparative genomic hybridization and its applicability to clinical genetic testing. Genet Med. 7:264–271. 2005. View Article : Google Scholar : PubMed/NCBI
26	Aten E, White SJ, Kalf ME, Vossen RH, Thygesen HH, Ruivenkamp CA, Kriek M, Breuning MH and den Dunnen JT: Methods to detect CNVs in the human genome. Cytogenet Genome Res. 123:313–321. 2008. View Article : Google Scholar : PubMed/NCBI
27	Shen Y and Wu BL: Designing a simple multiplex ligation-dependent probe amplification (MLPA) assay for rapid detection of copy number variants in the genome. J Genet Genomics. 36:257–265. 2009. View Article : Google Scholar : PubMed/NCBI
28	Bremer A, Giacobini M, Nordenskjöld M, Brøndum-Nielsen K, Mansouri M, Dahl N, Anderlid B and Schoumans J: Screening for copy number alterations in loci associated with autism spectrum disorders by two-color multiplex ligation-dependent probe amplification. Am J Med Genet B Neuropsychiatr Genet. 153B:280–285. 2010.PubMed/NCBI
29	Cai G, Edelmann L, Goldsmith JE, Cohen N, Nakamine A, Reichert JG, Hoffman EJ, Zurawiecki DM, Silverman JM, Hollander E, et al: Multiplex ligation-dependent probe amplification for genetic screening in autism spectrum disorders: Efficient identification of known microduplications and identification of a novel microduplication in ASMT. BMC Med Genomics. 1:502008. View Article : Google Scholar : PubMed/NCBI
30	Slater H, Bruno D, Ren H, La P, Burgess T, Hills L, Nouri S, Schouten J and Choo KH: Improved testing for CMT1A and HNPP using multiplex ligation-dependent probe amplification (MLPA) with rapid DNA preparations: Comparison with the interphase FISH method. Hum Mutat. 24:164–171. 2004. View Article : Google Scholar : PubMed/NCBI
31	Herodez Stangler S, Zagradisnik B, Skerget Erjavec A, Zagorac A and Vokac Kokalj N: Molecular diagnosis of PMP22 gene duplications and deletions: Comparison of different methods. J Int Med Res. 37:1626–1631. 2009. View Article : Google Scholar : PubMed/NCBI
32	Zhang Q and Keleş S: CNV-guided multi-read allocation for ChIP-seq. Bioinformatics. 30:2860–2867. 2014. View Article : Google Scholar : PubMed/NCBI
33	Duan J, Zhang JG, Deng HW and Wang YP: Detection of common copy number variation with application to population clustering from next generation sequencing data. Conf Proc IEEE Eng Med Biol Soc. 2012:1246–1249. 2012.PubMed/NCBI
34	de Ligt J, Boone PM, Pfundt R, Vissers LE, de Leeuw N, Shaw C, Brunner HG, Lupski JR, Veltman JA and Hehir-Kwa JY: Platform comparison of detecting copy number variants with microarrays and whole-exome sequencing. Genom Data. 2:144–146. 2014. View Article : Google Scholar : PubMed/NCBI
35	de Ligt J, Boone PM, Pfundt R, Vissers LE, Richmond T, Geoghegan J, O'Moore K, de Leeuw N, Shaw C, Brunner HG, et al: Detection of clinically relevant copy number variants with whole-exome sequencing. Hum Mutat. 34:1439–1448. 2013. View Article : Google Scholar : PubMed/NCBI
36	Tan R, Wang Y, Kleinstein SE, Liu Y, Zhu X, Guo H, Jiang Q, Allen AS and Zhu M: An evaluation of copy number variation detection tools from whole-exome sequencing data. Hum Mutat. 35:899–907. 2014. View Article : Google Scholar : PubMed/NCBI
37	Samarakoon PS, Sorte HS, Kristiansen BE, Skodje T, Sheng Y, Tjønnfjord GE, Stadheim B, Stray-Pedersen A, Rødningen OK and Lyle R: Identification of copy number variants from exome sequence data. BMC Genomics. 15:6612014. View Article : Google Scholar : PubMed/NCBI
38	Fromer M, Moran JL, Chambert K, Banks E, Bergen SE, Ruderfer DM, Handsaker RE, McCarroll SA, O'Donovan MC, Owen MJ, et al: Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet. 91:597–607. 2012. View Article : Google Scholar : PubMed/NCBI
39	Wu J, Grzeda KR, Stewart C, Grubert F, Urban AE, Snyder MP and Marth GT: Copy number variation detection from 1000 Genomes project exon capture sequencing data. BMC Bioinformatics. 13:3052012. View Article : Google Scholar : PubMed/NCBI
40	Guo Y, Sheng Q, Samuels DC, Lehmann B, Bauer JA, Pietenpol J and Shyr Y: Comparative study of exome copy number variation estimation tools using array comparative genomic hybridization as control. Biomed Res Int. 2013:9156362013. View Article : Google Scholar : PubMed/NCBI
41	Sathya B, Dharshini AP and Kumar GR: NGS meta data analysis for identification of SNP and INDEL patterns in human airway transcriptome: A preliminary indicator for lung cancer. Appl Transl Genom. 4:4–9. 2014.PubMed/NCBI
42	Liu B, Madduri RK, Sotomayor B, Chard K, Lacinski L, Dave UJ, Li J, Liu C and Foster IT: Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses. J Biomed Inform. 49:119–133. 2014. View Article : Google Scholar : PubMed/NCBI
43	Li H and Durbin R: Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics. 25:1754–1760. 2009. View Article : Google Scholar : PubMed/NCBI
44	Brandariz-Fontes C, Camacho-Sanchez M, Vilà C, Vega-Pla JL, Rico C and Leonard JA: Effect of the enzyme and PCR conditions on the quality of high-throughput DNA sequencing results. Sci Rep. 5:80562015. View Article : Google Scholar : PubMed/NCBI
45	Chen CP, Huang JP, Chen YY, Chern SR, Wu PS, Su JW, Chen YT, Chen WL and Wang W: Chromosome 22q11.2 deletion syndrome: Prenatal diagnosis, array comparative genomic hybridization characterization using uncultured amniocytes and literature review. Gene. 527:405–409. 2013. View Article : Google Scholar : PubMed/NCBI