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http://dx.doi.org/10.5808/GI.2020.18.1.e4

Quantitative evaluation of the molecular marker using droplet digital PCR  

Shin, Wonseok (Department of Nanobiomedical Science & BK21 PLUS NBM Global Research Center for Regenerative Medicine, Dankook University)
Kim, Haneul (Department of Nanobiomedical Science & BK21 PLUS NBM Global Research Center for Regenerative Medicine, Dankook University)
Oh, Dong-Yep (Livestock Research Institute)
Kim, Dong Hee (Department of Anesthesiology and Pain Management, Dankook University College of Medicine)
Han, Kyudong (Department of Nanobiomedical Science & BK21 PLUS NBM Global Research Center for Regenerative Medicine, Dankook University)
Abstract
Transposable elements (TEs) constitute approximately half of Bovine genome. They can be a powerful species-specific marker without regression mutations by the structure variation (SV) at the time of genomic evolution. In a previous study, we identified the Hanwoo-specific SV that was generated by a TE-association deletion event using traditional PCR method and Sanger sequencing validation. It could be used as a molecular marker to distinguish different cattle breeds (i.e., Hanwoo vs. Holstein). However, PCR is defective with various final copy quantifications from every sample. Thus, we applied to the droplet digital PCR (ddPCR) platform for accurate quantitative detection of the Hanwoo-specific SV. Although samples have low allele frequency variation within Hanwoo population, ddPCR could perform high sensitive detection with absolute quantification. We aimed to use ddPCR for more accurate quantification than PCR. We suggest that the ddPCR platform is applicable for the quantitative evaluation of molecular markers.
Keywords
droplet digital PCR; Hanwoo-specific marker; structure variation;
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1 Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 2011;83:8604-8610.   DOI
2 Demeke T, Dobnik D. Critical assessment of digital PCR for the detection and quantification of genetically modified organisms. Anal Bioanal Chem 2018;410:4039-4050.   DOI
3 Madic J, Zocevic A, Senlis V, Fradet E, Andre B, Muller S, et al. Three-color crystal digital PCR. Biomol Detect Quantif 2016;10:34-46.   DOI
4 Shehata HR, Li J, Chen S, Redda H, Cheng S, Tabujara N, et al. Droplet digital polymerase chain reaction (ddPCR) assays integrated with an internal control for quantification of bovine, porcine, chicken and turkey species in food and feed. PLoS One 2017;12:e0182872.   DOI
5 Kiselinova M, Pasternak AO, De Spiegelaere W, Vogelaers D, Berkhout B, Vandekerckhove L. Comparison of droplet digital PCR and seminested real-time PCR for quantification of cell-associated HIV-1 RNA. PLoS One 2014;9:e85999.   DOI
6 Strain MC, Lada SM, Luong T, Rought SE, Gianella S, Terry VH, et al. Highly precise measurement of HIV DNA by droplet digital PCR. PLoS One 2013;8:e55943.   DOI
7 Basu AS. Digital assays part I: partitioning statistics and digital PCR. SLAS Technol 2017;22:369-386.   DOI
8 Manoj P. Droplet digital PCR technology promises new applications and research areas. Mitochondrial DNA A DNA Mapp Seq Anal 2016;27:742-746.   DOI
9 Alcaide M, Yu S, Bushell K, Fornika D, Nielsen JS, Nelson BH, et al. Multiplex droplet digital PCR quantification of recurrent somatic mutations in diffuse large B-cell and follicular lymphoma. Clin Chem 2016;62:1238-1247.   DOI
10 Tang H, Cai Q, Li H, Hu P. Comparison of droplet digital PCR to real-time PCR for quantification of hepatitis B virus DNA. Biosci Biotechnol Biochem 2016;80:2159-2164.   DOI
11 Chung KY, Lee SH, Cho SH, Kwon EG, Lee JH. Current situation and future prospects for beef production in South Korea: a review. Asian-Australas J Anim Sci 2018;31:951-960.   DOI
12 Lee SH, Park BH, Sharma A, Dang CG, Lee SS, Choi TJ, et al. Hanwoo cattle: origin, domestication, breeding strategies and genomic selection. J Anim Sci Technol 2014;56:2.   DOI
13 Cheong HS, Kim LH, Namgoong S, Shin HD. Development of discrimination SNP markers for Hanwoo (Korean native cattle). Meat Sci 2013;94:355-359.   DOI
14 Choi JW, Liao X, Stothard P, Chung WH, Jeon HJ, Miller SP, et al. Whole-genome analyses of Korean native and Holstein cattle breeds by massively parallel sequencing. PLoS One 2014;9:e101127.   DOI
15 Lee KT, Chung WH, Lee SY, Choi JW, Kim J, Lim D, et al. Whole-genome resequencing of Hanwoo (Korean cattle) and insight into regions of homozygosity. BMC Genomics 2013;14:519.   DOI
16 Mehrban H, Lee DH, Moradi MH, IlCho C, Naserkheil M, Ibanez-Escriche N. Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture. Genet Sel Evol 2017;49:1.
17 Park J, Shin W, Mun S, Oh MH, Lim D, Oh DY, et al. Investigation of Hanwoo-specific structural variations using whole-genome sequencing data. Genes Genomics 2019;41:233-240.   DOI
18 Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods 2009;6:677-681.   DOI
19 Quinlan AR, Hall IM. Characterizing complex structural variation in germline and somatic genomes. Trends Genet 2012;28:43-53.   DOI
20 Raphael BJ. Chapter 6: Structural variation and medical genomics. PLoS Comput Biol 2012;8:e1002821.   DOI
21 Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing. Genome Biol 2019;20:117.   DOI
22 Garibyan L, Avashia N. Polymerase chain reaction. J Invest Dermatol 2013;133:1-4.   DOI
23 Sanders R, Mason DJ, Foy CA, Huggett JF. Considerations for accurate gene expression measurement by reverse transcription quantitative PCR when analysing clinical samples. Anal Bioanal Chem 2014;406:6471-6483.   DOI
24 Bustin SA, Nolan T. Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. J Biomol Tech 2004;15:155-166.
25 Campomenosi P, Gini E, Noonan DM, Poli A, D'Antona P, Rotolo N, et al. A comparison between quantitative PCR and droplet digital PCR technologies for circulating microRNA quantification in human lung cancer. BMC Biotechnol 2016;16:60.   DOI
26 Zmienko A, Samelak-Czajka A, Goralski M, Sobieszczuk-Nowicka E, Kozlowski P, Figlerowicz M. Selection of reference genes for qPCR- and ddPCR-based analyses of gene expression in Senescing Barley leaves. PLoS One 2015;10:e0118226.   DOI