Comparison of two methods for the quantitative assessment of genetically modified soybeans

Detalhes bibliográficos
Autor(a) principal: CHEN,Chen
Data de Publicação: 2022
Outros Autores: ZHANG,Yan, ZHANG,Rui, ZHANG,Yalun, ZHANG,Tao, ZHANG,Zilun, SHI,Guohua, ZHOU,Wei
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Food Science and Technology (Campinas)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101340
Resumo: Abstract Genetically modified soybean strains are trade monitoring object by China. Currently, the genetically modified soybean MON89788 has been approved in China to be imported as processing raw material. Therefore, there is an urgent need to establish a method to quantitatively assess MON89788. This study used droplet digital PCR technology to quantitatively detect MON89788. The results showed that the genomic DNA concentration and its copy number of genetically modified soybeans showed a certain linear relationship. The formula was y = 2.5967x + 3.1437, where R2 = 0.999. When the same 4.5% genetically modified sample was contained, the results of the droplet digital PCR ratio and linear methods were 5.88% and 3.599%, respectively. Comparing the two results showed that the droplet digital PCR ratio method has a larger error than the linear relationship method. The novel droplet digital PCR linear relationship method established in this study has high sensitivity and specificity, and thus is a good prospect for quantitative research.
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spelling Comparison of two methods for the quantitative assessment of genetically modified soybeansdigital PCRquantitative detectionMON89788Abstract Genetically modified soybean strains are trade monitoring object by China. Currently, the genetically modified soybean MON89788 has been approved in China to be imported as processing raw material. Therefore, there is an urgent need to establish a method to quantitatively assess MON89788. This study used droplet digital PCR technology to quantitatively detect MON89788. The results showed that the genomic DNA concentration and its copy number of genetically modified soybeans showed a certain linear relationship. The formula was y = 2.5967x + 3.1437, where R2 = 0.999. When the same 4.5% genetically modified sample was contained, the results of the droplet digital PCR ratio and linear methods were 5.88% and 3.599%, respectively. Comparing the two results showed that the droplet digital PCR ratio method has a larger error than the linear relationship method. The novel droplet digital PCR linear relationship method established in this study has high sensitivity and specificity, and thus is a good prospect for quantitative research.Sociedade Brasileira de Ciência e Tecnologia de Alimentos2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101340Food Science and Technology v.42 2022reponame:Food Science and Technology (Campinas)instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)instacron:SBCTA10.1590/fst.69921info:eu-repo/semantics/openAccessCHEN,ChenZHANG,YanZHANG,RuiZHANG,YalunZHANG,TaoZHANG,ZilunSHI,GuohuaZHOU,Weieng2022-09-22T00:00:00Zoai:scielo:S0101-20612022000101340Revistahttp://www.scielo.br/ctaONGhttps://old.scielo.br/oai/scielo-oai.php||revista@sbcta.org.br1678-457X0101-2061opendoar:2022-09-22T00:00Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)false
dc.title.none.fl_str_mv Comparison of two methods for the quantitative assessment of genetically modified soybeans
title Comparison of two methods for the quantitative assessment of genetically modified soybeans
spellingShingle Comparison of two methods for the quantitative assessment of genetically modified soybeans
CHEN,Chen
digital PCR
quantitative detection
MON89788
title_short Comparison of two methods for the quantitative assessment of genetically modified soybeans
title_full Comparison of two methods for the quantitative assessment of genetically modified soybeans
title_fullStr Comparison of two methods for the quantitative assessment of genetically modified soybeans
title_full_unstemmed Comparison of two methods for the quantitative assessment of genetically modified soybeans
title_sort Comparison of two methods for the quantitative assessment of genetically modified soybeans
author CHEN,Chen
author_facet CHEN,Chen
ZHANG,Yan
ZHANG,Rui
ZHANG,Yalun
ZHANG,Tao
ZHANG,Zilun
SHI,Guohua
ZHOU,Wei
author_role author
author2 ZHANG,Yan
ZHANG,Rui
ZHANG,Yalun
ZHANG,Tao
ZHANG,Zilun
SHI,Guohua
ZHOU,Wei
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv CHEN,Chen
ZHANG,Yan
ZHANG,Rui
ZHANG,Yalun
ZHANG,Tao
ZHANG,Zilun
SHI,Guohua
ZHOU,Wei
dc.subject.por.fl_str_mv digital PCR
quantitative detection
MON89788
topic digital PCR
quantitative detection
MON89788
description Abstract Genetically modified soybean strains are trade monitoring object by China. Currently, the genetically modified soybean MON89788 has been approved in China to be imported as processing raw material. Therefore, there is an urgent need to establish a method to quantitatively assess MON89788. This study used droplet digital PCR technology to quantitatively detect MON89788. The results showed that the genomic DNA concentration and its copy number of genetically modified soybeans showed a certain linear relationship. The formula was y = 2.5967x + 3.1437, where R2 = 0.999. When the same 4.5% genetically modified sample was contained, the results of the droplet digital PCR ratio and linear methods were 5.88% and 3.599%, respectively. Comparing the two results showed that the droplet digital PCR ratio method has a larger error than the linear relationship method. The novel droplet digital PCR linear relationship method established in this study has high sensitivity and specificity, and thus is a good prospect for quantitative research.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101340
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101340
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/fst.69921
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência e Tecnologia de Alimentos
publisher.none.fl_str_mv Sociedade Brasileira de Ciência e Tecnologia de Alimentos
dc.source.none.fl_str_mv Food Science and Technology v.42 2022
reponame:Food Science and Technology (Campinas)
instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron:SBCTA
instname_str Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron_str SBCTA
institution SBCTA
reponame_str Food Science and Technology (Campinas)
collection Food Science and Technology (Campinas)
repository.name.fl_str_mv Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
repository.mail.fl_str_mv ||revista@sbcta.org.br
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