A Next Generation Semiconductor Based Sequencing Approach for the Identification of Meat Species in DNA Mixtures
Articolo
Data di Pubblicazione:
2015
Abstract:
The identification of the species of origin ofmeat and meat products is an important issue to
prevent and detect frauds that might have economic, ethical and health implications. In this
paper we evaluated the potential of the next generation semiconductor based sequencing
technology (Ion Torrent Personal Genome Machine) for the identification of DNA from meat
species (pig, horse, cattle, sheep, rabbit, chicken, turkey, pheasant, duck, goose and pigeon)
as well as from human and rat in DNA mixtures through the sequencing of PCR products obtained
from different couples of universal primers that amplify 12S and 16S rRNA mitochondrial
DNA genes. Six libraries were produced including PCR products obtained separately
from 13 species or fromDNA mixtures containing DNA fromall species or only avian or only
mammalian species at equimolar concentration or at 1:10 or 1:50 ratios for pig and horse
DNA. Sequencing obtained a total of 33,294,511 called nucleotides of which 29,109,688 with
Q20 (87.43%) in a total of 215,944 reads. Different alignment algorithms were used to assign
the species based on sequence data. Error rate calculated after confirmation of the obtained
sequences by Sanger sequencing ranged from0.0003 to 0.02 for the different species. Correlation
about the number of reads per species between different libraries was high for mammalian
species (0.97) and lower for avian species (0.70). PCR competition limited the efficiency
of amplification and sequencing for avian species for some primer pairs. Detection of low
level of pig and horse DNA was possible with reads obtained from different primer pairs. The
sequencing of the products obtained from different universal PCR primers could be a useful
strategy to overcome potential problems of amplification. Based on these results, the Ion Torrent
technology can be applied for the identification of meat species in DNA mixtures.
Tipologia CRIS:
14.a.1 Articolo su rivista
Keywords:
NGS, identification species, molecular genetics
Elenco autori:
Bertolini, Francesca; Ghionda, Marco Ciro; D'Alessandro, Enrico; Geraci, Claudia; Chiofalo, Vincenzo; Fontanesi, Luca
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