Detailed Information

Cited 10 time in webofscience Cited 13 time in scopus
Metadata Downloads

Comparison of Seven Commercial TaqMan Master Mixes and Two Real-Time PCR Platforms Regarding the Rapid Detection of Porcine DNAopen access

Authors
Kang, Soo JiJang, Chan SongSon, Ji MinHong, Kwang Won
Issue Date
2021
Publisher
KOREAN SOC FOOD SCIENCE ANIMAL RESOURCES
Keywords
master mix; real-time PCR; species identification; porcine DNA
Citation
FOOD SCIENCE OF ANIMAL RESOURCES, v.41, no.1, pp 85 - 94
Pages
10
Indexed
SCIE
SCOPUS
KCI
Journal Title
FOOD SCIENCE OF ANIMAL RESOURCES
Volume
41
Number
1
Start Page
85
End Page
94
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/5649
DOI
10.5851/kosfa.2020.e80
ISSN
2636-0772
2636-0780
Abstract
A pig-specific real-time PCR assay based on the mitochondrial ND5 gene was developed to detect porcine material in food and other products. To optimize the performance of assay, seven commercial TaqMan master mixes and two real-time PCR platforms (Applied Biosystems StepOnePlus and Bio-rad CFX Connect) were used to evaluate the limit of detection (LOD) as well as the PCR efficiency and specificity. The LODs and PCR efficiencies for the seven master mixes on two platforms were 0.5-5 pg/reaction and 84.96%-108.80%, respectively. Additionally, non-specific amplifications of DNA from other animal samples (human, dog, cow, and chicken) were observed for four master mixes. These results imply that the sensitivity and specificity of a real-time PCR assay may vary depending on master mix and platform used. The best combination of master mix and real-time PCR platform can accurately detect 0.5 pg porcine DNA, with a PCR efficiency of 100.49%.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Life Science and Biotechnology > Department of Food Science & Biotechnology > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE