A next generation semiconductor based sequencing approach for the identification of meat species in DNA mixtures

PLoS One. 2015 Apr 29;10(4):e0121701. doi: 10.1371/journal.pone.0121701. eCollection 2015.

Abstract

The identification of the species of origin of meat 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 from DNA mixtures containing DNA from all 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 from 0.0003 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cattle / genetics
  • Chickens / genetics
  • DNA / genetics*
  • Ducks / genetics
  • Geese / genetics
  • Horses / genetics
  • Humans
  • Meat / analysis*
  • Meat Products / analysis*
  • Quail / genetics
  • Rabbits / genetics
  • Rats
  • Semiconductors*
  • Sequence Analysis, DNA / methods*
  • Sheep / genetics
  • Swine / genetics
  • Turkeys / genetics

Substances

  • DNA

Grants and funding

This work was supported by University of Bologna RFO funds, Italian MiPAAF Innovagen project, and PAN lab European Project PONa3_00166/F1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.