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Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples
Food and feed samples were randomly collected from different sources, including local and imported materials from the Syrian local market. These included maize, barley, soybean, fresh food samples and raw material. GMO detection was conducted by PCR and nested PCR-based techniques using specific pri...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4773575/ https://www.ncbi.nlm.nih.gov/pubmed/26958644 http://dx.doi.org/10.1016/j.dib.2016.02.035 |
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author | Alasaad, Noor Alzubi, Hussein Kader, Ahmad Abdul |
author_facet | Alasaad, Noor Alzubi, Hussein Kader, Ahmad Abdul |
author_sort | Alasaad, Noor |
collection | PubMed |
description | Food and feed samples were randomly collected from different sources, including local and imported materials from the Syrian local market. These included maize, barley, soybean, fresh food samples and raw material. GMO detection was conducted by PCR and nested PCR-based techniques using specific primers for the most used foreign DNA commonly used in genetic transformation procedures, i.e., 35S promoter, T-nos, epsps, cryIA(b) gene and nptII gene. The results revealed for the first time in Syria the presence of GM foods and feeds with glyphosate-resistant trait of P35S promoter and NOS terminator in the imported soybean samples with high frequency (5 out of the 6 imported soybean samples). While, tests showed negative results for the local samples. Also, tests revealed existence of GMOs in two imported maize samples detecting the presence of 35S promoter and nos terminator. Nested PCR results using two sets of primers confirmed our data. The methods applied in the brief data are based on DNA analysis by Polymerase Chain Reaction (PCR). This technique is specific, practical, reproducible and sensitive enough to detect up to 0.1% GMO in food and/or feedstuffs. Furthermore, all of the techniques mentioned are economic and can be applied in Syria and other developing countries. For all these reasons, the DNA-based analysis methods were chosen and preferred over protein-based analysis. |
format | Online Article Text |
id | pubmed-4773575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-47735752016-03-08 Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples Alasaad, Noor Alzubi, Hussein Kader, Ahmad Abdul Data Brief Data Article Food and feed samples were randomly collected from different sources, including local and imported materials from the Syrian local market. These included maize, barley, soybean, fresh food samples and raw material. GMO detection was conducted by PCR and nested PCR-based techniques using specific primers for the most used foreign DNA commonly used in genetic transformation procedures, i.e., 35S promoter, T-nos, epsps, cryIA(b) gene and nptII gene. The results revealed for the first time in Syria the presence of GM foods and feeds with glyphosate-resistant trait of P35S promoter and NOS terminator in the imported soybean samples with high frequency (5 out of the 6 imported soybean samples). While, tests showed negative results for the local samples. Also, tests revealed existence of GMOs in two imported maize samples detecting the presence of 35S promoter and nos terminator. Nested PCR results using two sets of primers confirmed our data. The methods applied in the brief data are based on DNA analysis by Polymerase Chain Reaction (PCR). This technique is specific, practical, reproducible and sensitive enough to detect up to 0.1% GMO in food and/or feedstuffs. Furthermore, all of the techniques mentioned are economic and can be applied in Syria and other developing countries. For all these reasons, the DNA-based analysis methods were chosen and preferred over protein-based analysis. Elsevier 2016-02-20 /pmc/articles/PMC4773575/ /pubmed/26958644 http://dx.doi.org/10.1016/j.dib.2016.02.035 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Alasaad, Noor Alzubi, Hussein Kader, Ahmad Abdul Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title | Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title_full | Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title_fullStr | Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title_full_unstemmed | Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title_short | Data in support of the detection of genetically modified organisms (GMOs) in food and feed samples |
title_sort | data in support of the detection of genetically modified organisms (gmos) in food and feed samples |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4773575/ https://www.ncbi.nlm.nih.gov/pubmed/26958644 http://dx.doi.org/10.1016/j.dib.2016.02.035 |
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